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Hydraulic Lifting Keel On Beneteau Oceanis 34.1

Best of both worlds.

The expert design team at Beneteau Sailboats has implemented a safe, stable, & convenient system to package the advantages of both deep and shallow draft keels. A hydraulic lifting keel offered on the Oceanis 34.1 maximizes the hull’s potential when deployed, yet gives access to shores with shallow waters when retracted.

When deployed, the lifting keel brings the performance of a very deep ballast in all points of sail. Without a weighted bulb on the bottom of the keel, this design also saves weight and limits drag.

The option is ideal for sailors who want the critical performance boost a deeper keel offers but also need shoal draft to get to their marina. Pensacola Bay, for instance, is extremely deep yet the marinas and bayous get shallow quickly and require a compromise.

When deployed, the performance draft is 8’4″

When retracted, the draft measures in at 4’1″

Ballast weight: 3,319 lbs (down from 4,099 lbs on the shoal draft)

The top of the keel pivots on a casing molded along the outside of the hull. This centerboard remains outside the hull & gives us a completely watertight structure. *For maximum stability and hold, the top of the keel pivots in a car inside of the casing*. A linear arm lifts keel up and down at the push of a button and is hidden inside of the dinette table.

The keel locks at one of 2 fixed positions – either fully deployed or fully tucked. The keel can only be deployed when the engine is underway, negating the risk of a badly positioned keel under sail. The ability to lock the keel in adds to the stability compared to operating it halfway deployed strictly on hydraulic pressure. It is important to understand that the draft cannot be adjusted to fit within the current depth and you must sail at one of the two positions (8’4″ or 4’1″).

In addition to adding performance and access, the system is a very safe one. In the event of a collision, the hydraulic cylinder pressure is released, freeing the keel so as to prevent damage.

The system is extremely easy to operate, with straightforward controls to raise and lower the keel. The control box is located near the throttle at the starboard helm station, and has all of the controls you need to operate your lifting keel.

See below placement of control:

The below tutorial video gives an overview of the keel operation and controls.

The popular new 34 foot cruiser has three keel options: a shoal draft, deep draft, and a lifting keel designed for the best of both.

The performance lifting keel is a safe, stable, & convenient system using hydraulics to lock the keel at one of 2 fixed positions – either fully deployed or fully tucked.

When deployed, the performance draft is 8’4″, when retracted, the draft measures in at 4’1″ …

The keel pivots on a structural support on the hull, keeping the entire system watertight.

The keel will deploy in under 30 seconds and retract in 20 seconds.

Other Keel Options

The popular new 34 foot cruiser has two other keel options in addition to the lifting keel, a shoal draft and a deep draft. See below outline for different options.

For more information about the Oceanis 34.1 or her keel options, fill out the contact form below

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For sale: Beneteau First 24 SE (2021) – Excellent and immaculate condition

For sale - 2021 Beneteau First 24 SE - Excellent and immaculate condition.

Lightly used about 50 times - only in freshwater lakes. The sailboat, located in northern Idaho, USA, was custom ordered by me as the original owner, and has a custom-built trailer. This First 24 SE fully loaded with options and is ready to sail.

Possibilities: Depending on location, I may be able to deliver the boat and provide rigging and sailing instruction for the boat.

A comprehensive 23-video of this First 24 SE can be viewed on YouTube at: https://www.youtube.com/watch?v=cv6PXTYDSB4

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Beneteau First 28 Lifting Keel for sale in Pornic, France

Pornic, France

Make & Model

Beneteau First 28 Lifting Keel

MEASUREMENTS

Description.

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ADDITIONAL INFORMATION

NAVIGATION EQUIPMENT

Depth Instrument

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ABOUT BENETEAU FIRST 28 LIFTING KEEL

The Beneteau First 28 Lifting Keel is 28 feet long and has a 9.8 feet beam. This 1982 diesel Beneteau First 28 Lifting Keel with 15 horsepower. The Beneteau First 28 Lifting Keelas well as being equipped with autopilot, depth instrument, speed instrument, vhf.

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2004 Beneteau 37 | Serendipitous Atlantic Highlands, New Jersey, United States

2006 Beneteau 50 | Attitude Adjustment Pompano Beach, Florida, United States

2007 Beneteau 43.14 | Kasoumai Rodney Bay, Saint Lucia, Caribbean

2021 Beneteau 24 | Lucky Boy Moscow, Idaho, United States

1986 Beneteau 51 | Shameles Charlotte Amalie, United States Virgin Islands, Caribbean

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1989 Beneteau 30 | Lollygag Junction City, Kansas, United States

2003 Beneteau 33 | OASIS Miami, Florida, United States

2017 Beneteau 41 St Maarten, Sint Maarten, Caribbean

2008 Beneteau 43 | SUNQUEST Miami, Florida, United States

1994 Beneteau 44 | Rout'Deau Melbourne, Florida, United States

1986 Beneteau 40.5 | LOIS Santa Cruz de Tenerife, Santa Cruz de Tenerife, Spain

2007 Beneteau 43 | Ocean Echo 1 Vancouver, British Columbia, Canada

2007 Beneteau 43.14 | Ocean Echo 1 Vancouver, British Columbia, Canada

2005 Beneteau 47 | Picaro Bocas del Toro, Bocas del Toro, Panama

2002 Beneteau 42 | Fredom Cacique , Colón, Panama

2005 Beneteau 34 Ventura, California, United States

1987 Beneteau 51 | Radio Flyer St. Augustine, Florida, United States

2000 Beneteau 32 El Dorado, Kansas, United States

2006 Beneteau 35 Glades, Florida, United States

1999 Beneteau 35 | Terre a Terre Lake Champlain, New York, United States

literature review in abstract

The Guide to Literature Reviews

What is a Literature Review?

• The Purpose of Literature Reviews
• Guidelines for Writing a Literature Review
• How to Organize a Literature Review?
• Software for Literature Reviews
• Using Artificial Intelligence for Literature Reviews
• How to Conduct a Literature Review?
• Common Mistakes and Pitfalls in a Literature Review
• Methods for Literature Reviews
• What is a Systematic Literature Review?
• What is a Narrative Literature Review?
• What is a Descriptive Literature Review?
• What is a Scoping Literature Review?
• What is a Realist Literature Review?
• What is a Critical Literature Review?
• Meta Analysis vs. Literature Review
• What is an Umbrella Literature Review?
• Differences Between Annotated Bibliographies and Literature Reviews
• Literature Review vs. Theoretical Framework
• How to Write a Literature Review?
• How to Structure a Literature Review?
• How to Make a Cover Page for a Literature Review?
• Importance of a literature review abstract

How to write a literature review abstract?

Key reminders when writing a literature review abstract.

• How to Write a Literature Review Introduction?
• How to Write the Body of a Literature Review?
• How to Write a Literature Review Conclusion?
• How to Make a Literature Review Bibliography?
• How to Format a Literature Review?
• How Long Should a Literature Review Be?
• Examples of Literature Reviews
• How to Present a Literature Review?
• How to Publish a Literature Review?

How to Write a Literature Review Abstract?

A well-crafted abstract is the initial point of contact between your research and its potential audience. It is crucial to present your work in the best possible light. A literature review abstract is a concise summary of the key points and findings of a literature review that is published as a full paper. It serves as a snapshot of the review, providing readers with a quick overview of the research topic, objectives, main findings, and implications.

Unlike the full literature review, the abstract does not delve into detailed analysis or discussion but highlights the most critical aspects. An abstract helps readers decide whether the full article is relevant to their interests and needs by encapsulating the essence of the literature review. A literature review abstract offers a condensed version of the study that helps researchers identify the review's relevance to their work. This is important in academic settings, where individuals often revise numerous journal articles and papers to find pertinent information. A clear and informative abstract saves time and effort.

Here are the steps we recommend when writing abstracts for literature reviews:

Introduce the research topic : Begin by stating the subject of your literature review. Explain its significance and relevance in your field. Provide context that highlights the broader impact and necessity of your review. For example, "This literature review focuses on the impact of climate change on coastal ecosystems and its significance in developing sustainable management strategies."

State objectives : Clearly outline the literature review's main objectives or purposes. Specify what you aim to achieve, such as identifying gaps in the literature, synthesizing existing research, or proposing new directions for future studies. For instance, "This review aims to identify key areas where climate change impacts coastal ecosystems and to propose future research directions."

Summarize key findings : Provide a concise summary of the data collection methods and results. Include primary findings, trends, or insights from your review. Highlight the most important conclusions and previous research contributions, and explain their implications for the field. An example might be, "The review reveals significant changes in species composition due to rising sea temperatures, suggesting the need for adaptive management strategies."

Use clear and concise language : Ensure your abstract covers the main points of your literature review, using straightforward language and avoiding complex terminology or jargon. Write in the third person to maintain objectivity, and structure your abstract logically to improve readability. For example, avoid first-person phrases like "I found that..." and use "The review indicates that..." Keep your abstract concise, typically between 150-250 words. Make it comprehensive, offering a clear view of the review’s scope and significance without overwhelming readers with too much detail. Conciseness is key in abstract writing, as it allows readers to quickly grasp the essence of your review without wading through unnecessary information.

Optimize search engines : Incorporate relevant search terms and phrases to enhance discoverability through search engines. Choose a descriptive title that includes key phrases from your literature review. This makes your work more likely to appear with the search results and makes it more accessible to potential readers. With the example above, a researcher may use keywords like "literature review," "climate change," and "coastal ecosystems" to attract the right audience.

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When writing your abstract, double-check it covers the critical points of your literature review. This includes the research topic, significance, objectives, data extraction methods, main findings, and implications for additional research. Avoiding ambiguity and complex terminology makes your abstract accessible to a wider audience, including those who may not be specialists in your field. Here are some important tips to keep in mind when writing abstracts:

Avoid using complex terminology or scientific jargon that might confuse readers. A good abstract should be accessible to a broad range of potential readers, including researchers and policymakers.

Avoid using quotations in your abstract; paraphrase the information to maintain clarity and conciseness. Write in the third person to ensure your abstract remains professional and focused.

Choose a descriptive title for your article mentioning key phrases from your literature review. Optimize the title for search engines to enhance its visibility and shareability. A well-crafted title can significantly impact the reach and impact of your research. Incorporating keywords into your title improves search engine optimization (SEO) and attracts readers' attention, making your work more discoverable.

Focus on the most important information, avoiding unnecessary details. Ensure a logical flow of ideas with clear and active language. Each sentence should contribute to explaining your literature review's key points. A well-structured abstract guides readers through your review logically, making it easier to follow and understand. It also leads readers through your review smoothly.

Make sure that your abstract accurately reflects the content of your literature review. Use relevant keywords and phrases to ensure your abstract remains focused and pertinent to your research. Accuracy is vital to maintain the interest of your readers and to guide those who read the full review to find the information they expect.

Proofread your abstract carefully to check for grammatical and typographical errors. Ensure that it is well-structured, polished, and error-free.

A well-written literature review abstract is vital for the effective dissemination of your research. It serves as the first impression of your work which engages readers and provides a succinct overview of your study's significance and findings. You will create an abstract that attracts readers and reaches a broader audience by introducing your topic, stating your objectives, summarizing key findings, and using clear language. Writing clear abstracts enhances the visibility, accessibility, and impact of your literature reviews.

Develop powerful literature reviews with ATLAS.ti

Use our intuitive data analysis platform to make the most of your literature review.

How do I Write a Literature Review?: #5 Writing the Review

• Step #1: Choosing a Topic
• Step #2: Finding Information
• Step #3: Evaluating Content
• Step #4: Synthesizing Content
• #5 Writing the Review
• Citing Your Sources

WRITING THE REVIEW 

You've done the research and now you're ready to put your findings down on paper. When preparing to write your review, first consider how will you organize your review.

The actual review generally has 5 components:

Abstract  -  An abstract is a summary of your literature review. It is made up of the following parts:

• A contextual sentence about your motivation behind your research topic
• Your thesis statement
• A descriptive statement about the types of literature used in the review
• Summarize your findings
• Conclusion(s) based upon your findings

Introduction :   Like a typical research paper introduction, provide the reader with a quick idea of the topic of the literature review:

• Define or identify the general topic, issue, or area of concern. This provides the reader with context for reviewing the literature.
• Identify related trends in what has already been published about the topic; or conflicts in theory, methodology, evidence, and conclusions; or gaps in research and scholarship; or a single problem or new perspective of immediate interest.
• Establish your reason (point of view) for reviewing the literature; explain the criteria to be used in analyzing and comparing literature and the organization of the review (sequence); and, when necessary, state why certain literature is or is not included (scope)  - 

Body :  The body of a literature review contains your discussion of sources and can be organized in 3 ways-

• Chronological -  by publication or by trend
• Thematic -  organized around a topic or issue, rather than the progression of time
• Methodical -  the focusing factor usually does not have to do with the content of the material. Instead, it focuses on the "methods" of the literature's researcher or writer that you are reviewing

You may also want to include a section on "questions for further research" and discuss what questions the review has sparked about the topic/field or offer suggestions for future studies/examinations that build on your current findings.

Conclusion :  In the conclusion, you should:

Conclude your paper by providing your reader with some perspective on the relationship between your literature review's specific topic and how it's related to it's parent discipline, scientific endeavor, or profession.

Bibliography :   Since a literature review is composed of pieces of research, it is very important that your correctly cite the literature you are reviewing, both in the reviews body as well as in a bibliography/works cited. To learn more about different citation styles, visit the " Citing Your Sources " tab.

• Writing a Literature Review: Wesleyan University
• Literature Review: Edith Cowan University
• << Previous: Step #4: Synthesizing Content
• Next: Citing Your Sources >>
• Last Updated: Aug 22, 2023 1:35 PM
• URL: https://libguides.eastern.edu/literature_reviews

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Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Writing a Literature Review

Welcome to the Purdue OWL

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

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• Knowledge Base

Methodology

• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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See an example

Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue

Google Scholar

• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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How to Write a Literature Review

• Critical analysis
• Sample Literature Reviews
• Scaffold examples for organising Literature Reviews
• Writing an Abstract
• Creating Appendices
• APA Reference Guide
• Library Resources
• Guide References

What is an abstract?

What is an Abstract?

An abstract is a short summary of an article, essay or research findings. A well-written abstract will provide the reader with a brief overview of the entire article, including the article's purpose, methodology and conclusion. An abstract should give the reader enough detail to determine if the information in the article meets their research needs...and it should make them want to read more!

While an abstract is usually anywhere between 150 - 300 words, it is important to always establish with your teacher the desired length of the abstract you are submitting.

This excellent guide from the University of Melbourne is a great snapshot of how to write an abstract.

Here are a few links to some useful abstract examples:

University of New South Wales

University of Wollongong

Michigan State University

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• Last Updated: Apr 8, 2024 9:14 AM
• URL: https://saintpatricks-nsw.libguides.com/lit_review

Academic Writing

• Strategies for Writing
• Punctuation
• Plagiarism & Self-Plagiarism

How to Build a Literature Review

• PRISMA - Systematic reviews & meta-analyses
• Other Resources
• Using Zotero for Bibliographies
• Abstract Writing Tips
• Writing Assistance
• Locating a Journal
• Assessing Potential Journals
• Finding a Publisher
• Types of Peer Review
• Author Rights & Responsibilities
• Copyright Considerations
• What is a Lit Review?
• Why Write a Lit Review?

Structure of a Literature Review

Preliminary steps for literature review.

• Basic Example
• More Examples

A literature review is a comprehensive summary and analysis of previously published research on a particular topic. Literature reviews should give the reader an overview of the important theories and themes that have previously been discussed on the topic, as well as any important researchers who have contributed to the discourse. This review should connect the established conclusions to the hypothesis being presented in the rest of the paper.

What a Literature Review Is Not:

• Annotated Bibliography: An annotated bibliography summarizes and assesses each resource individually and separately. A literature review explores the connections between different articles to illustrate important themes/theories/research trends within a larger research area. 
• Timeline: While a literature review can be organized chronologically, they are not simple timelines of previous events. They should not be a list of any kind. Individual examples or events should be combined to illustrate larger ideas or concepts.
• Argumentative Paper: Literature reviews are not meant to be making an argument. They are explorations of a concept to give the audience an understanding of what has already been written and researched about an idea. As many perspectives as possible should be included in a literature review in order to give the reader as comprehensive understanding of a topic as possible.

Why Write a Literature Review?

After reading the literature review, the reader should have a basic understanding of the topic. A reader should be able to come into your paper without really knowing anything about an idea, and after reading the literature, feel more confident about the important points.

A literature review should also help the reader understand the focus the rest of the paper will take within the larger topic. If the reader knows what has already been studied, they will be better prepared for the novel argument that is about to be made.

A literature review should help the reader understand the important history, themes, events, and ideas about a particular topic. Connections between ideas/themes should also explored. Part of the importance of a literature review is to prove to experts who do read your paper that you are knowledgeable enough to contribute to the academic discussion. You have to have done your homework.

A literature review should also identify the gaps in research to show the reader what hasn't yet been explored. Your thesis should ideally address one of the gaps identified in the research. Scholarly articles are meant to push academic conversations forward with new ideas and arguments. Before knowing where the gaps are in a topic, you need to have read what others have written.

As mentioned in other tabs, literature reviews should discuss the big ideas that make up a topic. Each literature review should be broken up into different subtopics. Each subtopic should use groups of articles as evidence to support the ideas. There are several different ways of organizing a literature review. It will depend on the patterns one sees in the groups of articles as to which strategy should be used. Here are a few examples of how to organize your review:

If there are clear trends that change over time, a chronological approach could be used to organize a literature review. For example, one might argue that in the 1970s, the predominant theories and themes argued something. However, in the 1980s, the theories evolved to something else. Then, in the 1990s, theories evolved further. Each decade is a subtopic, and articles should be used as examples. 

Themes/Theories

There may also be clear distinctions between schools of thought within a topic, a theoretical breakdown may be most appropriate. Each theory could be a subtopic, and articles supporting the theme should be included as evidence for each one. 

If researchers mainly differ in the way they went about conducting research, literature reviews can be organized by methodology. Each type of method could be a subtopic,  and articles using the method should be included as evidence for each one.

• Define your research question
• Compile a list of initial keywords to use for searching based on question
• Search for literature that discusses the topics surrounding your research question
• Assess and organize your literature into logical groups
• Identify gaps in research and conduct secondary searches (if necessary)
• Reassess and reorganize literature again (if necessary)
• Write review

Here is an example of a literature review, taken from the beginning of a research article. You can find other examples within most scholarly research articles. The majority of published scholarship includes a literature review section, and you can use those to become more familiar with these reviews.

Source:  Perceptions of the Police by LGBT Communities

There are many books and internet resources about literature reviews though most are long on how to search and gather the literature. How to literally organize the information is another matter.

Some pro tips:

• Be thoughtful in naming the folders, sub-folders, and sub, sub-folders.  Doing so really helps your thinking and concepts within your research topic.
• Be disciplined to add keywords under the tabs as this will help you search for ALL the items on your concepts/topics.
• Use the notes tab to add reminders, write bibliography/annotated bibliography
• Your literature review easily flows from your statement of purpose (SoP).  Therefore, does your SoP say clearly and exactly the intent of your research?  Your research assumption and argument is obvious?
• Begin with a topic outline that traces your argument. pg99: "First establish the line of argumentation you will follow (the thesis), whether it is an assertion, a contention, or a proposition.
• This means that you should have formed judgments about the topic based on the analysis and synthesis of the literature you are reviewing."
• Keep filling it in; flushing it out more deeply with your references

Other Resources/Examples

• ISU Writing Assistance The Julia N. Visor Academic Center provides one-on-one writing assistance for any course or need. By focusing on the writing process instead of merely on grammar and editing, we are committed to making you a better writer.
• University of Toronto: The Literature Review Written by Dena Taylor, Health Sciences Writing Centre
• Purdue OWL - Writing a Lit Review Goes over the basic steps
• UW Madison Writing Center - Review of Literature A description of what each piece of a literature review should entail.
• USC Libraries - Literature Reviews Offers detailed guidance on how to develop, organize, and write a college-level research paper in the social and behavioral sciences.
• Creating the literature review: integrating research questions and arguments Blog post with very helpful overview for how to organize and build/integrate arguments in a literature review
• Understanding, Selecting, and Integrating a Theoretical Framework in Dissertation Research: Creating the Blueprint for Your “House” Article focusing on constructing a literature review for a dissertation. Still very relevant for literature reviews in other types of content.

A note that many of these examples will be far longer and in-depth than what's required for your assignment. However, they will give you an idea of the general structure and components of a literature review. Additionally, most scholarly articles will include a literature review section. Looking over the articles you have been assigned in classes will also help you.

• Understanding, Selecting, and Integrating a Theoretical Framework in Dissertation Research: Creating the Blueprint for Your “House” Excellent article detailing how to construct your literature review.
• Sample Literature Review (Univ. of Florida) This guide will provide research and writing tips to help students complete a literature review assignment.
• Sociology Literature Review (Univ. of Hawaii) Written in ASA citation style - don't follow this format.
• Sample Lit Review - Univ. of Vermont Includes an example with tips in the footnotes.

Attribution

Content on this page was provided by Grace Allbaugh

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• Last Updated: Aug 6, 2024 1:41 PM
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What this handout is about

This handout provides definitions and examples of the two main types of abstracts: descriptive and informative. It also provides guidelines for constructing an abstract and general tips for you to keep in mind when drafting. Finally, it includes a few examples of abstracts broken down into their component parts.

An abstract is a self-contained, short, and powerful statement that describes a larger work. Components vary according to discipline. An abstract of a social science or scientific work may contain the scope, purpose, results, and contents of the work. An abstract of a humanities work may contain the thesis, background, and conclusion of the larger work. An abstract is not a review, nor does it evaluate the work being abstracted. While it contains key words found in the larger work, the abstract is an original document rather than an excerpted passage.

Why write an abstract?

You may write an abstract for various reasons. The two most important are selection and indexing. Abstracts allow readers who may be interested in a longer work to quickly decide whether it is worth their time to read it. Also, many online databases use abstracts to index larger works. Therefore, abstracts should contain keywords and phrases that allow for easy searching.

Say you are beginning a research project on how Brazilian newspapers helped Brazil’s ultra-liberal president Luiz Ignácio da Silva wrest power from the traditional, conservative power base. A good first place to start your research is to search Dissertation Abstracts International for all dissertations that deal with the interaction between newspapers and politics. “Newspapers and politics” returned 569 hits. A more selective search of “newspapers and Brazil” returned 22 hits. That is still a fair number of dissertations. Titles can sometimes help winnow the field, but many titles are not very descriptive. For example, one dissertation is titled “Rhetoric and Riot in Rio de Janeiro.” It is unclear from the title what this dissertation has to do with newspapers in Brazil. One option would be to download or order the entire dissertation on the chance that it might speak specifically to the topic. A better option is to read the abstract. In this case, the abstract reveals the main focus of the dissertation:

This dissertation examines the role of newspaper editors in the political turmoil and strife that characterized late First Empire Rio de Janeiro (1827-1831). Newspaper editors and their journals helped change the political culture of late First Empire Rio de Janeiro by involving the people in the discussion of state. This change in political culture is apparent in Emperor Pedro I’s gradual loss of control over the mechanisms of power. As the newspapers became more numerous and powerful, the Emperor lost his legitimacy in the eyes of the people. To explore the role of the newspapers in the political events of the late First Empire, this dissertation analyzes all available newspapers published in Rio de Janeiro from 1827 to 1831. Newspapers and their editors were leading forces in the effort to remove power from the hands of the ruling elite and place it under the control of the people. In the process, newspapers helped change how politics operated in the constitutional monarchy of Brazil.

From this abstract you now know that although the dissertation has nothing to do with modern Brazilian politics, it does cover the role of newspapers in changing traditional mechanisms of power. After reading the abstract, you can make an informed judgment about whether the dissertation would be worthwhile to read.

Besides selection, the other main purpose of the abstract is for indexing. Most article databases in the online catalog of the library enable you to search abstracts. This allows for quick retrieval by users and limits the extraneous items recalled by a “full-text” search. However, for an abstract to be useful in an online retrieval system, it must incorporate the key terms that a potential researcher would use to search. For example, if you search Dissertation Abstracts International using the keywords “France” “revolution” and “politics,” the search engine would search through all the abstracts in the database that included those three words. Without an abstract, the search engine would be forced to search titles, which, as we have seen, may not be fruitful, or else search the full text. It’s likely that a lot more than 60 dissertations have been written with those three words somewhere in the body of the entire work. By incorporating keywords into the abstract, the author emphasizes the central topics of the work and gives prospective readers enough information to make an informed judgment about the applicability of the work.

When do people write abstracts?

• when submitting articles to journals, especially online journals
• when applying for research grants
• when writing a book proposal
• when completing the Ph.D. dissertation or M.A. thesis
• when writing a proposal for a conference paper
• when writing a proposal for a book chapter

Most often, the author of the entire work (or prospective work) writes the abstract. However, there are professional abstracting services that hire writers to draft abstracts of other people’s work. In a work with multiple authors, the first author usually writes the abstract. Undergraduates are sometimes asked to draft abstracts of books/articles for classmates who have not read the larger work.

Types of abstracts

There are two types of abstracts: descriptive and informative. They have different aims, so as a consequence they have different components and styles. There is also a third type called critical, but it is rarely used. If you want to find out more about writing a critique or a review of a work, see the UNC Writing Center handout on writing a literature review . If you are unsure which type of abstract you should write, ask your instructor (if the abstract is for a class) or read other abstracts in your field or in the journal where you are submitting your article.

Descriptive abstracts

A descriptive abstract indicates the type of information found in the work. It makes no judgments about the work, nor does it provide results or conclusions of the research. It does incorporate key words found in the text and may include the purpose, methods, and scope of the research. Essentially, the descriptive abstract describes the work being abstracted. Some people consider it an outline of the work, rather than a summary. Descriptive abstracts are usually very short—100 words or less.

Informative abstracts

The majority of abstracts are informative. While they still do not critique or evaluate a work, they do more than describe it. A good informative abstract acts as a surrogate for the work itself. That is, the writer presents and explains all the main arguments and the important results and evidence in the complete article/paper/book. An informative abstract includes the information that can be found in a descriptive abstract (purpose, methods, scope) but also includes the results and conclusions of the research and the recommendations of the author. The length varies according to discipline, but an informative abstract is rarely more than 10% of the length of the entire work. In the case of a longer work, it may be much less.

Here are examples of a descriptive and an informative abstract of this handout on abstracts . Descriptive abstract:

The two most common abstract types—descriptive and informative—are described and examples of each are provided.

Informative abstract:

Abstracts present the essential elements of a longer work in a short and powerful statement. The purpose of an abstract is to provide prospective readers the opportunity to judge the relevance of the longer work to their projects. Abstracts also include the key terms found in the longer work and the purpose and methods of the research. Authors abstract various longer works, including book proposals, dissertations, and online journal articles. There are two main types of abstracts: descriptive and informative. A descriptive abstract briefly describes the longer work, while an informative abstract presents all the main arguments and important results. This handout provides examples of various types of abstracts and instructions on how to construct one.

Which type should I use?

Your best bet in this case is to ask your instructor or refer to the instructions provided by the publisher. You can also make a guess based on the length allowed; i.e., 100-120 words = descriptive; 250+ words = informative.

How do I write an abstract?

The format of your abstract will depend on the work being abstracted. An abstract of a scientific research paper will contain elements not found in an abstract of a literature article, and vice versa. However, all abstracts share several mandatory components, and there are also some optional parts that you can decide to include or not. When preparing to draft your abstract, keep the following key process elements in mind:

• Reason for writing: What is the importance of the research? Why would a reader be interested in the larger work?
• Problem: What problem does this work attempt to solve? What is the scope of the project? What is the main argument/thesis/claim?
• Methodology: An abstract of a scientific work may include specific models or approaches used in the larger study. Other abstracts may describe the types of evidence used in the research.
• Results: Again, an abstract of a scientific work may include specific data that indicates the results of the project. Other abstracts may discuss the findings in a more general way.
• Implications: What changes should be implemented as a result of the findings of the work? How does this work add to the body of knowledge on the topic?

(This list of elements is adapted with permission from Philip Koopman, “How to Write an Abstract.” )

All abstracts include:

• A full citation of the source, preceding the abstract.
• The most important information first.
• The same type and style of language found in the original, including technical language.
• Key words and phrases that quickly identify the content and focus of the work.
• Clear, concise, and powerful language.

Abstracts may include:

• The thesis of the work, usually in the first sentence.
• Background information that places the work in the larger body of literature.
• The same chronological structure as the original work.

How not to write an abstract:

• Do not refer extensively to other works.
• Do not add information not contained in the original work.
• Do not define terms.

If you are abstracting your own writing

When abstracting your own work, it may be difficult to condense a piece of writing that you have agonized over for weeks (or months, or even years) into a 250-word statement. There are some tricks that you could use to make it easier, however.

Reverse outlining:

This technique is commonly used when you are having trouble organizing your own writing. The process involves writing down the main idea of each paragraph on a separate piece of paper– see our short video . For the purposes of writing an abstract, try grouping the main ideas of each section of the paper into a single sentence. Practice grouping ideas using webbing or color coding .

For a scientific paper, you may have sections titled Purpose, Methods, Results, and Discussion. Each one of these sections will be longer than one paragraph, but each is grouped around a central idea. Use reverse outlining to discover the central idea in each section and then distill these ideas into one statement.

Cut and paste:

To create a first draft of an abstract of your own work, you can read through the entire paper and cut and paste sentences that capture key passages. This technique is useful for social science research with findings that cannot be encapsulated by neat numbers or concrete results. A well-written humanities draft will have a clear and direct thesis statement and informative topic sentences for paragraphs or sections. Isolate these sentences in a separate document and work on revising them into a unified paragraph.

If you are abstracting someone else’s writing

When abstracting something you have not written, you cannot summarize key ideas just by cutting and pasting. Instead, you must determine what a prospective reader would want to know about the work. There are a few techniques that will help you in this process:

Identify key terms:

Search through the entire document for key terms that identify the purpose, scope, and methods of the work. Pay close attention to the Introduction (or Purpose) and the Conclusion (or Discussion). These sections should contain all the main ideas and key terms in the paper. When writing the abstract, be sure to incorporate the key terms.

Highlight key phrases and sentences:

Instead of cutting and pasting the actual words, try highlighting sentences or phrases that appear to be central to the work. Then, in a separate document, rewrite the sentences and phrases in your own words.

Don’t look back:

After reading the entire work, put it aside and write a paragraph about the work without referring to it. In the first draft, you may not remember all the key terms or the results, but you will remember what the main point of the work was. Remember not to include any information you did not get from the work being abstracted.

Revise, revise, revise

No matter what type of abstract you are writing, or whether you are abstracting your own work or someone else’s, the most important step in writing an abstract is to revise early and often. When revising, delete all extraneous words and incorporate meaningful and powerful words. The idea is to be as clear and complete as possible in the shortest possible amount of space. The Word Count feature of Microsoft Word can help you keep track of how long your abstract is and help you hit your target length.

Example 1: Humanities abstract

Kenneth Tait Andrews, “‘Freedom is a constant struggle’: The dynamics and consequences of the Mississippi Civil Rights Movement, 1960-1984” Ph.D. State University of New York at Stony Brook, 1997 DAI-A 59/02, p. 620, Aug 1998

This dissertation examines the impacts of social movements through a multi-layered study of the Mississippi Civil Rights Movement from its peak in the early 1960s through the early 1980s. By examining this historically important case, I clarify the process by which movements transform social structures and the constraints movements face when they try to do so. The time period studied includes the expansion of voting rights and gains in black political power, the desegregation of public schools and the emergence of white-flight academies, and the rise and fall of federal anti-poverty programs. I use two major research strategies: (1) a quantitative analysis of county-level data and (2) three case studies. Data have been collected from archives, interviews, newspapers, and published reports. This dissertation challenges the argument that movements are inconsequential. Some view federal agencies, courts, political parties, or economic elites as the agents driving institutional change, but typically these groups acted in response to the leverage brought to bear by the civil rights movement. The Mississippi movement attempted to forge independent structures for sustaining challenges to local inequities and injustices. By propelling change in an array of local institutions, movement infrastructures had an enduring legacy in Mississippi.

Now let’s break down this abstract into its component parts to see how the author has distilled his entire dissertation into a ~200 word abstract.

What the dissertation does This dissertation examines the impacts of social movements through a multi-layered study of the Mississippi Civil Rights Movement from its peak in the early 1960s through the early 1980s. By examining this historically important case, I clarify the process by which movements transform social structures and the constraints movements face when they try to do so.

How the dissertation does it The time period studied in this dissertation includes the expansion of voting rights and gains in black political power, the desegregation of public schools and the emergence of white-flight academies, and the rise and fall of federal anti-poverty programs. I use two major research strategies: (1) a quantitative analysis of county-level data and (2) three case studies.

What materials are used Data have been collected from archives, interviews, newspapers, and published reports.

Conclusion This dissertation challenges the argument that movements are inconsequential. Some view federal agencies, courts, political parties, or economic elites as the agents driving institutional change, but typically these groups acted in response to movement demands and the leverage brought to bear by the civil rights movement. The Mississippi movement attempted to forge independent structures for sustaining challenges to local inequities and injustices. By propelling change in an array of local institutions, movement infrastructures had an enduring legacy in Mississippi.

Keywords social movements Civil Rights Movement Mississippi voting rights desegregation

Example 2: Science Abstract

Luis Lehner, “Gravitational radiation from black hole spacetimes” Ph.D. University of Pittsburgh, 1998 DAI-B 59/06, p. 2797, Dec 1998

The problem of detecting gravitational radiation is receiving considerable attention with the construction of new detectors in the United States, Europe, and Japan. The theoretical modeling of the wave forms that would be produced in particular systems will expedite the search for and analysis of detected signals. The characteristic formulation of GR is implemented to obtain an algorithm capable of evolving black holes in 3D asymptotically flat spacetimes. Using compactification techniques, future null infinity is included in the evolved region, which enables the unambiguous calculation of the radiation produced by some compact source. A module to calculate the waveforms is constructed and included in the evolution algorithm. This code is shown to be second-order convergent and to handle highly non-linear spacetimes. In particular, we have shown that the code can handle spacetimes whose radiation is equivalent to a galaxy converting its whole mass into gravitational radiation in one second. We further use the characteristic formulation to treat the region close to the singularity in black hole spacetimes. The code carefully excises a region surrounding the singularity and accurately evolves generic black hole spacetimes with apparently unlimited stability.

This science abstract covers much of the same ground as the humanities one, but it asks slightly different questions.

Why do this study The problem of detecting gravitational radiation is receiving considerable attention with the construction of new detectors in the United States, Europe, and Japan. The theoretical modeling of the wave forms that would be produced in particular systems will expedite the search and analysis of the detected signals.

What the study does The characteristic formulation of GR is implemented to obtain an algorithm capable of evolving black holes in 3D asymptotically flat spacetimes. Using compactification techniques, future null infinity is included in the evolved region, which enables the unambiguous calculation of the radiation produced by some compact source. A module to calculate the waveforms is constructed and included in the evolution algorithm.

Results This code is shown to be second-order convergent and to handle highly non-linear spacetimes. In particular, we have shown that the code can handle spacetimes whose radiation is equivalent to a galaxy converting its whole mass into gravitational radiation in one second. We further use the characteristic formulation to treat the region close to the singularity in black hole spacetimes. The code carefully excises a region surrounding the singularity and accurately evolves generic black hole spacetimes with apparently unlimited stability.

Keywords gravitational radiation (GR) spacetimes black holes

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Belcher, Wendy Laura. 2009. Writing Your Journal Article in Twelve Weeks: A Guide to Academic Publishing Success. Thousand Oaks, CA: Sage Press.

Koopman, Philip. 1997. “How to Write an Abstract.” Carnegie Mellon University. October 1997. http://users.ece.cmu.edu/~koopman/essays/abstract.html .

Lancaster, F.W. 2003. Indexing And Abstracting in Theory and Practice , 3rd ed. London: Facet Publishing.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Ten Simple Rules for Writing a Literature Review

Marco pautasso.

1 Centre for Functional and Evolutionary Ecology (CEFE), CNRS, Montpellier, France

2 Centre for Biodiversity Synthesis and Analysis (CESAB), FRB, Aix-en-Provence, France

Literature reviews are in great demand in most scientific fields. Their need stems from the ever-increasing output of scientific publications [1] . For example, compared to 1991, in 2008 three, eight, and forty times more papers were indexed in Web of Science on malaria, obesity, and biodiversity, respectively [2] . Given such mountains of papers, scientists cannot be expected to examine in detail every single new paper relevant to their interests [3] . Thus, it is both advantageous and necessary to rely on regular summaries of the recent literature. Although recognition for scientists mainly comes from primary research, timely literature reviews can lead to new synthetic insights and are often widely read [4] . For such summaries to be useful, however, they need to be compiled in a professional way [5] .

When starting from scratch, reviewing the literature can require a titanic amount of work. That is why researchers who have spent their career working on a certain research issue are in a perfect position to review that literature. Some graduate schools are now offering courses in reviewing the literature, given that most research students start their project by producing an overview of what has already been done on their research issue [6] . However, it is likely that most scientists have not thought in detail about how to approach and carry out a literature review.

Reviewing the literature requires the ability to juggle multiple tasks, from finding and evaluating relevant material to synthesising information from various sources, from critical thinking to paraphrasing, evaluating, and citation skills [7] . In this contribution, I share ten simple rules I learned working on about 25 literature reviews as a PhD and postdoctoral student. Ideas and insights also come from discussions with coauthors and colleagues, as well as feedback from reviewers and editors.

Rule 1: Define a Topic and Audience

How to choose which topic to review? There are so many issues in contemporary science that you could spend a lifetime of attending conferences and reading the literature just pondering what to review. On the one hand, if you take several years to choose, several other people may have had the same idea in the meantime. On the other hand, only a well-considered topic is likely to lead to a brilliant literature review [8] . The topic must at least be:

• interesting to you (ideally, you should have come across a series of recent papers related to your line of work that call for a critical summary),
• an important aspect of the field (so that many readers will be interested in the review and there will be enough material to write it), and
• a well-defined issue (otherwise you could potentially include thousands of publications, which would make the review unhelpful).

Ideas for potential reviews may come from papers providing lists of key research questions to be answered [9] , but also from serendipitous moments during desultory reading and discussions. In addition to choosing your topic, you should also select a target audience. In many cases, the topic (e.g., web services in computational biology) will automatically define an audience (e.g., computational biologists), but that same topic may also be of interest to neighbouring fields (e.g., computer science, biology, etc.).

Rule 2: Search and Re-search the Literature

After having chosen your topic and audience, start by checking the literature and downloading relevant papers. Five pieces of advice here:

• keep track of the search items you use (so that your search can be replicated [10] ),
• keep a list of papers whose pdfs you cannot access immediately (so as to retrieve them later with alternative strategies),
• use a paper management system (e.g., Mendeley, Papers, Qiqqa, Sente),
• define early in the process some criteria for exclusion of irrelevant papers (these criteria can then be described in the review to help define its scope), and
• do not just look for research papers in the area you wish to review, but also seek previous reviews.

The chances are high that someone will already have published a literature review ( Figure 1 ), if not exactly on the issue you are planning to tackle, at least on a related topic. If there are already a few or several reviews of the literature on your issue, my advice is not to give up, but to carry on with your own literature review,

The bottom-right situation (many literature reviews but few research papers) is not just a theoretical situation; it applies, for example, to the study of the impacts of climate change on plant diseases, where there appear to be more literature reviews than research studies [33] .

• discussing in your review the approaches, limitations, and conclusions of past reviews,
• trying to find a new angle that has not been covered adequately in the previous reviews, and
• incorporating new material that has inevitably accumulated since their appearance.

When searching the literature for pertinent papers and reviews, the usual rules apply:

• be thorough,
• use different keywords and database sources (e.g., DBLP, Google Scholar, ISI Proceedings, JSTOR Search, Medline, Scopus, Web of Science), and
• look at who has cited past relevant papers and book chapters.

Rule 3: Take Notes While Reading

If you read the papers first, and only afterwards start writing the review, you will need a very good memory to remember who wrote what, and what your impressions and associations were while reading each single paper. My advice is, while reading, to start writing down interesting pieces of information, insights about how to organize the review, and thoughts on what to write. This way, by the time you have read the literature you selected, you will already have a rough draft of the review.

Of course, this draft will still need much rewriting, restructuring, and rethinking to obtain a text with a coherent argument [11] , but you will have avoided the danger posed by staring at a blank document. Be careful when taking notes to use quotation marks if you are provisionally copying verbatim from the literature. It is advisable then to reformulate such quotes with your own words in the final draft. It is important to be careful in noting the references already at this stage, so as to avoid misattributions. Using referencing software from the very beginning of your endeavour will save you time.

Rule 4: Choose the Type of Review You Wish to Write

After having taken notes while reading the literature, you will have a rough idea of the amount of material available for the review. This is probably a good time to decide whether to go for a mini- or a full review. Some journals are now favouring the publication of rather short reviews focusing on the last few years, with a limit on the number of words and citations. A mini-review is not necessarily a minor review: it may well attract more attention from busy readers, although it will inevitably simplify some issues and leave out some relevant material due to space limitations. A full review will have the advantage of more freedom to cover in detail the complexities of a particular scientific development, but may then be left in the pile of the very important papers “to be read” by readers with little time to spare for major monographs.

There is probably a continuum between mini- and full reviews. The same point applies to the dichotomy of descriptive vs. integrative reviews. While descriptive reviews focus on the methodology, findings, and interpretation of each reviewed study, integrative reviews attempt to find common ideas and concepts from the reviewed material [12] . A similar distinction exists between narrative and systematic reviews: while narrative reviews are qualitative, systematic reviews attempt to test a hypothesis based on the published evidence, which is gathered using a predefined protocol to reduce bias [13] , [14] . When systematic reviews analyse quantitative results in a quantitative way, they become meta-analyses. The choice between different review types will have to be made on a case-by-case basis, depending not just on the nature of the material found and the preferences of the target journal(s), but also on the time available to write the review and the number of coauthors [15] .

Rule 5: Keep the Review Focused, but Make It of Broad Interest

Whether your plan is to write a mini- or a full review, it is good advice to keep it focused 16 , 17 . Including material just for the sake of it can easily lead to reviews that are trying to do too many things at once. The need to keep a review focused can be problematic for interdisciplinary reviews, where the aim is to bridge the gap between fields [18] . If you are writing a review on, for example, how epidemiological approaches are used in modelling the spread of ideas, you may be inclined to include material from both parent fields, epidemiology and the study of cultural diffusion. This may be necessary to some extent, but in this case a focused review would only deal in detail with those studies at the interface between epidemiology and the spread of ideas.

While focus is an important feature of a successful review, this requirement has to be balanced with the need to make the review relevant to a broad audience. This square may be circled by discussing the wider implications of the reviewed topic for other disciplines.

Rule 6: Be Critical and Consistent

Reviewing the literature is not stamp collecting. A good review does not just summarize the literature, but discusses it critically, identifies methodological problems, and points out research gaps [19] . After having read a review of the literature, a reader should have a rough idea of:

• the major achievements in the reviewed field,
• the main areas of debate, and
• the outstanding research questions.

It is challenging to achieve a successful review on all these fronts. A solution can be to involve a set of complementary coauthors: some people are excellent at mapping what has been achieved, some others are very good at identifying dark clouds on the horizon, and some have instead a knack at predicting where solutions are going to come from. If your journal club has exactly this sort of team, then you should definitely write a review of the literature! In addition to critical thinking, a literature review needs consistency, for example in the choice of passive vs. active voice and present vs. past tense.

Rule 7: Find a Logical Structure

Like a well-baked cake, a good review has a number of telling features: it is worth the reader's time, timely, systematic, well written, focused, and critical. It also needs a good structure. With reviews, the usual subdivision of research papers into introduction, methods, results, and discussion does not work or is rarely used. However, a general introduction of the context and, toward the end, a recapitulation of the main points covered and take-home messages make sense also in the case of reviews. For systematic reviews, there is a trend towards including information about how the literature was searched (database, keywords, time limits) [20] .

How can you organize the flow of the main body of the review so that the reader will be drawn into and guided through it? It is generally helpful to draw a conceptual scheme of the review, e.g., with mind-mapping techniques. Such diagrams can help recognize a logical way to order and link the various sections of a review [21] . This is the case not just at the writing stage, but also for readers if the diagram is included in the review as a figure. A careful selection of diagrams and figures relevant to the reviewed topic can be very helpful to structure the text too [22] .

Rule 8: Make Use of Feedback

Reviews of the literature are normally peer-reviewed in the same way as research papers, and rightly so [23] . As a rule, incorporating feedback from reviewers greatly helps improve a review draft. Having read the review with a fresh mind, reviewers may spot inaccuracies, inconsistencies, and ambiguities that had not been noticed by the writers due to rereading the typescript too many times. It is however advisable to reread the draft one more time before submission, as a last-minute correction of typos, leaps, and muddled sentences may enable the reviewers to focus on providing advice on the content rather than the form.

Feedback is vital to writing a good review, and should be sought from a variety of colleagues, so as to obtain a diversity of views on the draft. This may lead in some cases to conflicting views on the merits of the paper, and on how to improve it, but such a situation is better than the absence of feedback. A diversity of feedback perspectives on a literature review can help identify where the consensus view stands in the landscape of the current scientific understanding of an issue [24] .

Rule 9: Include Your Own Relevant Research, but Be Objective

In many cases, reviewers of the literature will have published studies relevant to the review they are writing. This could create a conflict of interest: how can reviewers report objectively on their own work [25] ? Some scientists may be overly enthusiastic about what they have published, and thus risk giving too much importance to their own findings in the review. However, bias could also occur in the other direction: some scientists may be unduly dismissive of their own achievements, so that they will tend to downplay their contribution (if any) to a field when reviewing it.

In general, a review of the literature should neither be a public relations brochure nor an exercise in competitive self-denial. If a reviewer is up to the job of producing a well-organized and methodical review, which flows well and provides a service to the readership, then it should be possible to be objective in reviewing one's own relevant findings. In reviews written by multiple authors, this may be achieved by assigning the review of the results of a coauthor to different coauthors.

Rule 10: Be Up-to-Date, but Do Not Forget Older Studies

Given the progressive acceleration in the publication of scientific papers, today's reviews of the literature need awareness not just of the overall direction and achievements of a field of inquiry, but also of the latest studies, so as not to become out-of-date before they have been published. Ideally, a literature review should not identify as a major research gap an issue that has just been addressed in a series of papers in press (the same applies, of course, to older, overlooked studies (“sleeping beauties” [26] )). This implies that literature reviewers would do well to keep an eye on electronic lists of papers in press, given that it can take months before these appear in scientific databases. Some reviews declare that they have scanned the literature up to a certain point in time, but given that peer review can be a rather lengthy process, a full search for newly appeared literature at the revision stage may be worthwhile. Assessing the contribution of papers that have just appeared is particularly challenging, because there is little perspective with which to gauge their significance and impact on further research and society.

Inevitably, new papers on the reviewed topic (including independently written literature reviews) will appear from all quarters after the review has been published, so that there may soon be the need for an updated review. But this is the nature of science [27] – [32] . I wish everybody good luck with writing a review of the literature.

Acknowledgments

Many thanks to M. Barbosa, K. Dehnen-Schmutz, T. Döring, D. Fontaneto, M. Garbelotto, O. Holdenrieder, M. Jeger, D. Lonsdale, A. MacLeod, P. Mills, M. Moslonka-Lefebvre, G. Stancanelli, P. Weisberg, and X. Xu for insights and discussions, and to P. Bourne, T. Matoni, and D. Smith for helpful comments on a previous draft.

Funding Statement

This work was funded by the French Foundation for Research on Biodiversity (FRB) through its Centre for Synthesis and Analysis of Biodiversity data (CESAB), as part of the NETSEED research project. The funders had no role in the preparation of the manuscript.

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Literature Review: Conducting & Writing

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Have an exemplary literature review.

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Have you written a stellar literature review you care to share for teaching purposes?

Are you an instructor who has received an exemplary literature review and have permission from the student to post?

Please contact Britt McGowan at [email protected] for inclusion in this guide. All disciplines welcome and encouraged.

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11.8  Writing an abstract

All full reviews must include an abstract of not more than 400 words. The abstract should be kept as brief as possible without sacrificing important content. Abstracts to Cochrane reviews are published in MEDLINE and the Science Citation Index, and are made freely available on the internet. It is therefore important that they can be read as stand-alone documents.

The abstract should summarize the key methods, results and conclusions of the review and should not contain any information that is not in the review. Links to other parts of the review (such as references, studies, tables and figures) may not be included in the abstract. A hypothetical example of an abstract is included in Box 11.8.a .

Abstracts should be targeted primarily at healthcare decision makers (clinicians, informed consumers and policy makers) rather than just to researchers. Terminology should be reasonably comprehensible to a general rather than a specialist healthcare audience. Abbreviations should be avoided, except where they are widely understood (for example, HIV). Where essential, other abbreviations should be spelt out (with the abbreviations in brackets) on first use. Names of drugs and interventions that can be understood internationally should be used wherever possible. Trade names should not be used.

The content under each heading in the abstract should be as follows:

Background: This should be one or two sentences to explain the context or elaborate on the purpose and rationale of the review. If this version of the review is an update of an earlier one, it is helpful to include a sentence such as “This is an update of a Cochrane review first published in YEAR, and previously updated in YEAR”.

Objectives:  This should be a precise statement of the primary objective of the review, ideally in a single sentence, matching the Objectives in the main text of the review. Where possible the style should be of the form “To assess the effects of   [intervention or comparison] for [health problem] for/in [types of people, disease or problem and setting if specified]”.

Search methods: This should list the sources and the dates of the last search, for each source, using the active form ‘We searched….’ or, if there is only one author, the passive form can be used, for example, ‘Database X, Y, Z were searched’. Search terms should not be listed here. If the CRG’s Specialized Register was used, this should be listed first in the form ‘Cochrane X Group Specialized Register’. The order for listing other databases should be the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, other databases. The date range of the search for each database should be given. For the Cochrane Central Register of Controlled Trials this should be in the form ‘Cochrane Central Register of Controlled Trials ( The Cochrane Library 2007, Issue 1)’. For most other databases, such as MEDLINE, it should be in the form ‘MEDLINE (January 1966 to December 2006)’. Searching of bibliographies for relevant citations can be covered in a generic phrase ‘reference lists of articles’. If there were any constraints based on language or publication status, these should be listed. If individuals or organizations were contacted to locate studies this should be noted and it is preferable to use ‘We contacted pharmaceutical companies’ rather than a listing of all the pharmaceutical companies contacted. If journals were specifically handsearched for the review, this should be noted but handsearching to help build the Specialized Register of the CRG should not be listed.

Selection criteria: These should be given as ‘ [type of study] of [type of intervention or comparison] in [disease, problem or type of people]‘ . Outcomes should only be listed here if the review was restricted to specific outcomes.

Data collection and analysis: This should be restricted to how data were extracted and assessed, and not include details of what data were extracted. This section should cover whether data extraction and assessments of risk of bias were done by more than one person. If the authors contacted investigators to obtain missing information, this should be noted here. What steps, if any, were taken to identify adverse effects should be noted.

Main results: This section should begin with the total number of studies and participants included in the review, and brief details pertinent to the interpretation of the results (for example, the risk of bias in the studies overall or a comment on the comparability of the studies, if appropriate). It should address the primary objective and be restricted to the main qualitative and quantitative results (generally including not more than six key results). The outcomes included should be selected on the basis of which are most likely to help someone making a decision about whether or not to use a particular intervention. Adverse effects should be included if these are covered in the review. If necessary, the number of studies and participants contributing to the separate outcomes should be noted, along with concerns over quality of evidence specific to these outcomes. The results should be expressed narratively as well as quantitatively if the numerical results are not clear or intuitive (such as those from a standardized mean differences analysis). The summary statistics in the abstract should be the same as those selected as the defaults for the review, and should be presented in a standard way, such as ‘odds ratio 2.31 (95% confidence interval 1.13 to 3.45)’. Ideally, risks of events (percentage) or averages (for continuous data) should be reported for both comparison groups. If overall results are not calculated in the review, a qualitative assessment or a description of the range and pattern of the results can be given. However, ‘vote counts’ in which the numbers of ‘positive’ and ‘negative’ studies are reported should be avoided.

Authors’ conclusions: The primary purpose of the review should be to present information, rather than to offer advice or recommendations. The Authors’ conclusions should be succinct and drawn directly from the findings of the review so that they directly and obviously reflect the main results. Assumptions should generally not be made about practice circumstances, values, preferences, tradeoffs; and the giving of advice or recommendations should generally be avoided. Any important limitations of data and analyses should be noted. Important conclusions about the implications for research should be included if these are not obvious.

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How to Write an Abstract for Literature Review?

• How to Write an Abstract…

Table of Contents

Writing an Abstract for Literature Review

Before a researcher or an academic writer starts to become familiar with how to write an abstract for literature review , one should first be familiar with what exactly qualifies as a Literature Review .

While writing a research paper or dissertation , the literature review is the portion where you brief the guidance counselor – also referred to as a Project Coordinator – about the precise problem you are looking to study and explain in the research paper.

Not only does this enable the guidance counselor to determine that the pupil is on the right track, but also helps the writer lay down a robust foundation to support his or her claim with the help of cited references .

Learn how to write an abstract?

Basic Tips and Guidelines

It would be more helpful to explain this with a real example. A student is looking to study the notion that “Small & Medium Enterprises can benefit by switching over to Cloud Computing”. This is the claim and the study path to be explored. In the Literature Review, the writer can build his case by, first, writing on the history of Cloud Computing; how it started, where it comes from, pioneers, how it evolved etc.

Consequently, the writer will also define & explain Cloud Computing; its various service models, deployment models, components, real life applications of Cloud Computing, the advantages & disadvantages etc.

Now that you know what the Literature Review comprises, let’s come back to how to write an abstract for literature review . The flow is the same as your research paper; initiate with the introduction and talk about the problem or situation being studied, follow it with a description of the research methods brought in to implementation during the data collection & analysis phases , the results derived from the data analysis and, finally, the conclusion reached at the end.

Sample of an Abstract for a Literature Review

Here is a sample of how to write an abstract for literature review in light of the previously mentioned scenario:

Cloud Computing is a technology that brings many advantages with it for businesses that adopt it. In times of this recession when companies are resorting to either shutting down or come up with ways to reduce their operating expenditures, Cloud Computing offers Small & Medium Enterprises numerous benefits and a lifeline to stay in business. To validate this proposition, 10 SMEs that switched over to a Cloud Computing IT infrastructure in the last 12 months or less were chosen from various industries. The firms’ executives and decision makers were interviewed in detail about their IT operations before and after the implementation of Cloud Computing. The findings attained from the respondents clearly indicated a sharp reduction in both operating & capital expenses. This was evident by the lessening in the physical space required for the hardware, diminution of the IT staff headcount to monitor the systems, annulment of expenses incurred on software licensing and also for data recovery & systems security. The study clearly indicates that Cloud Computing is of immense importance to SMEs that wish to reduce their running costs yet continue expanding their operations.

Author:  Ozzy Mirza

For the first 2 decades of life, Ozzy lived a nomadic life; growing up in different countries, interacting with various cultures, gaining exposure to numerous lifestyles. His inscriptions reflect the blend of it all; versatility & candidness meet paper & pen.

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How To Write an Abstract (With Examples)

• Smodin Editorial Team
• Updated: August 13, 2024
• Step-by-Step Instructions for Writing

The abstract is the shop front of your thesis. It’s essentially a summary of your paper outlining what you have discovered during your research.

In academia, an abstract serves several purposes:

• Offers a summary of your findings
• Other researchers use it to determine whether your work is relevant to their own research
• Helps your peers understand what you have discovered if they don’t have time to read the entire paper
• Provides an easy way to index and categorize papers for academic journals

So a good abstract has several benefits for readers and reviewers. But, beyond that, you need to know how to write a good abstract if you want to get a high grade.

In our article, we give you some of the best tips and tricks on how to write an abstract that is concise and informative.

Step 1 – Understand the Purpose of an Abstract

Before you learn how to write an abstract, you need to know what one is and what purpose it serves. A good abstract should answer these questions:

• What is the study about?
• Why did you do this study or project?
• What did you do and how?
• What were your findings?
• What do your findings mean?

Think of an abstract like a movie trailer. It gives the reader a glimpse–a teaser–of what’s to come. It helps them decide if your paper is something they’re interested in.

Usually, an abstract is 100-250 words, so you only have a small window to rope your audience in.

There are four types of abstracts. You might use a different one depending on the nature of your research paper . The different kinds of abstracts include:

• Informative abstract: Details the background information, key points, research methods, and significant findings. There may also be further reading recommendations so that the reader can understand the main elements of the paper better.
• Descriptive abstract: Provides an overview of the content, including major points and research methods. However, descriptive abstracts don’t provide significant findings or conclusions. So, they’re less helpful for determining the relevance of the work.
• Critical abstract: Evaluates or provides analysis regarding the paper’s findings, with an overview of the paper. These abstracts are longer, sometimes up to 500 words in length. They may also refer to outside information.
• Highlight abstract: Grabs the reader’s attention to hook them in. Academic writing doesn’t usually include this type of abstract, since it doesn’t really give an overview of the text.

Typically, you’ll only see the first two in academia, but a descriptive abstract is still rarer than an informative one. An informative abstract includes everything you need to know about a research paper. So, it’s the preferred method for most students.

Step 2 – Key Elements of an Abstract

Every good abstract page has certain elements, including the background, methodology, results, and conclusion. It may also include keywords listed at the end of the abstract, helping to categorize and index the paper.

Here’s everything you need to include in your abstract.

Background and Objective

The first part of the abstract should cover the background information for your central idea. Whether you’re studying social sciences or writing a scientific paper, this section is absolutely crucial. It’s the opening line that sets the tone for your entire dissertation.

You can usually do this in around three sentences. Here is what each one should include:

• Sentence 1: Introduce the topic and define the key concepts in your study.
• Sentence 2: Define the gap in the literature, describing the main existing theories and identifying their limitations.
• Sentence 3: Explain how your research will fill this gap in the knowledge and what it adds to your field.

You can also state your research question at this point. Of course, you’ll need to do a literature review to write this effectively. So, check out other abstracts and ensure you use a good sentence structure .

Example: “Climate change poses significant challenges for worldwide agricultural productivity. Despite the numerous studies that exist on its impact on crop yields, there is a lack of comprehensive analysis. Other articles do not study how these impacts vary across different climactic regions. This study aims to fill this gap by examining the regional differences in climate change effects on wheat production.”

Next, you can outline the specific details of your project, summarizing the methodology you intend to use. At this point, you can also outline the data, theories, and case studies that you used during your research.

Generally, this can be just a single sentence highlighting your methodology. However, it can vary greatly depending on your field. For example, in scientific writing, you might need to describe the materials you’re using in the study. Meanwhile, for social sciences, it’s likely to be more theory-based.

Example: “I conducted a meta-analysis of existing studies on wheat production under varying climatic conditions. I collected data from peer-reviewed journals published between 2000 and 2023. I used statistical methods to assess the impact of temperature and precipitation changes on wheat yield.”

The next part of your abstract should state your main point. Remember, the abstract is just a brief summary, so you don’t need to go into detail. Instead, summarize all the main arguments that your paper makes and state their contribution to the field.

Even if you feel like your main findings are significant, don’t go into too much detail yet! That comes later, in the paper itself.

Example: “The results indicated a significant negative correlation between increased temperatures and wheat yields in arid and semi-arid regions. The average yield reduction was 15%. Conversely, in temperate regions, moderate temperature increases were associated with a slight yield increase of 5%. Precipitation changes had less consistent effects across different regions.”

The final part of your abstract should provide a strong conclusion. Here, you can discuss the implications of your main findings. Often, you can also incorporate key words found within the abstract and write these in a list at the end. This makes your paper easier to index.

Example: “These findings suggest that climate change adaptation strategies for wheat production must be region-specific. In arid regions, efforts must focus on heat-resistant crop varieties and improving irrigation. Meanwhile, temperate regions may benefit from optimizing planting dates and crop management.

Keywords: Climate change, wheat production, regional analysis, agricultural adaptation, crop yield.”

Step 3 – Writing the Abstract

Now that you understand what an abstract is, you can master the art of writing one. Here are Smodin’s top tips when writing an abstract.

Write a Draft

Start by writing a draft, and don’t put too much emphasis on it being perfect. Make sure your draft includes all the key elements (background, methods, results, conclusions).

Ensure that your draft provides a clear and concise summary of your research, outlining your major findings.

Revise for Clarity and Conciseness

Once you have a draft, you can start to edit and improve it. At this point, you can start to pay more attention to the word count. It’s time to cut out the unnecessary parts and improve clarity.

You should focus on making your abstract as succinct as possible while retaining the essential information. Remember, the abstract is just one paragraph, so you might need to be quite harsh in cutting bits out.

Check for Accuracy and Consistency

Finally, check for accuracy. You’ll need to ensure that the abstract accurately reflects the main ideas in the paper. Don’t mention anything you haven’t talked about in the paper!

You should also check that all the terminology and data are correct. Getting this wrong isn’t just unprofessional, but it could lose you marks!

Step 4 – Formatting the Abstract

Depending on where you’re submitting your paper, there may be a publication manual. This is certainly the case if you’re submitting a journal article. However, your college or university might also have guidelines that they use to standardize abstracts.

It’s important to follow the format that the journal or institution provides. This includes sticking to the word count (decrease or i ncrease the number of words if necessary) but also following the specific format. For example, many journals in the social sciences, natural sciences, and engineering sciences use the IMRaD structure:

Introduction

Tips for Writing a Compelling Abstract

Want to know how to write an amazing abstract? Not just a good one, but one that’s going to get you the best grade? Here are five tips that will guarantee success.

• Be concise: It’s crucial to be brief. Potential readers don’t want to know all the details just yet. Remember, it’s only a paragraph long! Make sure you use clear and straightforward language throughout.
• Highlight key points: Your abstract should describe the main findings of your abstract, including a range of key phrases. Emphasize these aspects, and ensure that readers understand the significance of the study.
• Avoid jargon: The abstract should be accessible to a broad audience. So, minimize the use of technical terms and acronyms.
• Focus on the reader: It’s important to focus on things that the reader needs to know. The abstract should help them understand the research that comes later. Try to spark their interest without providing too much information.

Use Smodin To Write Effective Abstracts

Abstracts are important, so getting them right is a concern for many students. After all, they’re a crucial component that summarizes your research and hooks the reader. In some cases, an abstract is essential for winning you research grants.

Fortunately, you can make writing an abstract easier by using Smodin. Smodin’s AI writer can assist in crafting well-structured, comprehensive abstracts. Here are some of its key capabilities:

• Advanced language processing
• Customizable input parameters, to make the abstract your own
• Comprehensive coverage of key elements
• Keyword generation

Beyond its amazing generative capabilities, Smodin can improve efficiency and save you time! Whether you want it to generate the full text or just the abstract, Smodin helps you on your academic journey. And because it’s trained on academic data, it’s much better than similar generative AI models.

Smodin’s AI Writer offers a powerful solution for researchers looking to create effective abstracts. It can significantly enhance the quality and efficiency of your academic writing. So what are you waiting for? Try Smodin’s AI writer today!

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Automated data analysis of unstructured grey literature in health research: A mapping review

Affiliations.

• 1 National Institute for Health and Care Research Innovation Observatory, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK.
• 2 Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
• PMID: 38115736
• DOI: 10.1002/jrsm.1692

The amount of grey literature and 'softer' intelligence from social media or websites is vast. Given the long lead-times of producing high-quality peer-reviewed health information, this is causing a demand for new ways to provide prompt input for secondary research. To our knowledge, this is the first review of automated data extraction methods or tools for health-related grey literature and soft data, with a focus on (semi)automating horizon scans, health technology assessments (HTA), evidence maps, or other literature reviews. We searched six databases to cover both health- and computer-science literature. After deduplication, 10% of the search results were screened by two reviewers, the remainder was single-screened up to an estimated 95% sensitivity; screening was stopped early after screening an additional 1000 results with no new includes. All full texts were retrieved, screened, and extracted by a single reviewer and 10% were checked in duplicate. We included 84 papers covering automation for health-related social media, internet fora, news, patents, government agencies and charities, or trial registers. From each paper, we extracted data about important functionalities for users of the tool or method; information about the level of support and reliability; and about practical challenges and research gaps. Poor availability of code, data, and usable tools leads to low transparency regarding performance and duplication of work. Financial implications, scalability, integration into downstream workflows, and meaningful evaluations should be carefully planned before starting to develop a tool, given the vast amounts of data and opportunities those tools offer to expedite research.

Keywords: artificial intelligence; automation; grey literature; literature review; natural language processing.

© 2023 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

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• Published: 10 August 2024

Mapping biomimicry research to sustainable development goals

• Raghu Raman 1 ,
• Aswathy Sreenivasan 2 ,
• M. Suresh 2 &
• Prema Nedungadi 3  

Scientific Reports volume  14 , Article number:  18613 ( 2024 ) Cite this article

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This study systematically evaluates biomimicry research within the context of sustainable development goals (SDGs) to discern the interdisciplinary interplay between biomimicry and SDGs. The alignment of biomimicry with key SDGs showcases its interdisciplinary nature and potential to offer solutions across the health, sustainability, and energy sectors. This study identified two primary thematic clusters. The first thematic cluster focused on health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's role in healthcare innovations, sustainable collaboration, and land management. This cluster demonstrates the potential of biomimicry to contribute to medical technologies, emphasizing the need for cross-sectoral partnerships and ecosystem preservation. The second thematic cluster revolves around clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), showcasing nature-inspired solutions for sustainable development challenges, including energy generation and water purification. The prominence of SDG 7 within this cluster indicates that biomimicry significantly contributes to sustainable energy practices. The analysis of thematic clusters further revealed the broad applicability of biomimicry and its role in enhancing sustainable energy access and promoting ecosystem conservation. Emerging research topics, such as metaheuristics, nanogenerators, exosomes, and bioprinting, indicate a dynamic field poised for significant advancements. By mapping the connections between biomimicry and SDGs, this study provides a comprehensive overview of the field's trajectory, emphasizing its importance in advancing global sustainability efforts.

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Introduction.

Biomimicry, which combines 'bio' (life) and 'mimicry' (imitation), uses nature's patterns to solve human problems, aligning with the SDGs by fostering innovations 1 . This discipline studies natural processes to inspire sustainable designs and promote responsible consumption and production 2 . Biomimicry emphasizes sustainability, ideation, and education in reconnecting with nature to achieve the SDGs 3 . Collaboration among designers, technologists, and business experts is vital for translating natural mechanisms into commercial solutions 4 . Biomimetics, which aims for radical innovations by replicating living systems, strives for breakthroughs in economic growth 5 . By promoting systemic change through the emulation of nature's regenerative processes, biomimicry's alignment with the SDGs could enhance sustainability efforts. Merging biomimicry insights with SDGs could exceed sustainability benchmarks.

Integrating biomimicry with sustainable development goals (SDGs) is crucial for addressing global challenges. The SDGs offer a blueprint for global well-being and environmental stewardship by 2030 6 . They aim to protect the environment and foster social and economic development. Biomimicry provides innovative approaches to these objectives, drawing from natural strategies. While SDGs offer clear targets, biomimicry complements these by providing a unique lens for solutions 7 . The investigation of biomimicry in conjunction with the SDGs is based on the understanding that the development of biologically inspired materials, structures, and systems offers a novel and sustainable solution to design problems, particularly in the built environment 8 . By mimicking nature's answers to complicated challenges, biomimicry produces creative, clever, long-lasting, and environmentally responsible ideas.

The SDGs outline a comprehensive sustainability agenda targeting social equity, environmental conservation, and poverty alleviation 9 . The use of biomimicry in research can lead to the development of solutions that mimic natural efficiency 10 , revolutionizing industries with resource-efficient technologies and enhancing sustainability. This synergy could lead to environmentally friendly products, improved energy solutions, and effective waste management systems. Integrating biomimicry into industry and education promotes environmental stewardship and ecological appreciation 11 . Marrying biomimicry research with SDGs has accelerated progress toward sustainable development.

Biomimicry can provide insightful and useful solutions consistent with sustainability ideals by imitating the adaptability and efficiency observed in biological systems 12 . The built environment's use of biomimicry has a greater sustainable impact when circular design features are included 13 . Reusing materials, cutting waste, and designing systems that work with natural cycles are all stressed in a circular design. Combining biomimicry and circular design promotes social inclusion, environmental resilience, resourcefulness, and compassionate governance, all of which lead to peaceful coexistence with the environment. This all-encompassing strategy demonstrates a dedication to tackling the larger social and environmental concerns that the SDGs represent and design challenges 14 . Complementing these studies, Wamane 7 examined the intersection of biomimicry, the environmental, social, and governance (ESG) framework, and circular economy principles, advocating for an economic paradigm shift toward sustainability.

A key aspect of realizing the impact of biomimicry on SDGs is the successful translation and commercialization of biomimicry discoveries. This involves overcoming barriers such as skill gaps, the engineering mindset, commercial acumen, and funding. Insights from the "The State of Nature-Inspired-Innovation in the UK" report provide a comprehensive analysis of these challenges and potential strategies to address them, underscoring the importance of integrating commercial perspectives into biomimicry research.

This research employs bibliometric techniques to assess the integration and coherence within circular economy policy-making, emphasizing the potential for a synergistic relationship between environmental stewardship, economic growth, and social equity to foster a sustainable future.

In addressing the notable gap in comprehensive research concerning the contribution of biomimicry solutions to specific SDGs, this study offers significant insights into the interdisciplinary applications of biomimicry and its potential to advance global sustainability efforts. Our investigation aims to bridge this research gap through a systematic analysis, resulting in the formulation of the following research questions:

RQ1: How does an interdisciplinary analysis of biomimicry research align with and contribute to advancing specific SDGs?

RQ2: What emerging topics within biomimicry research are gaining prominence, and how do they relate to the SDGs?

RQ3 : What are the barriers to the translation and commercialization of biomimicry innovations, and how can these barriers be overcome to enhance their impact on SDGs?

RQ4: Based on the identified gaps in research and the potential for interdisciplinary collaboration, what innovative areas within biomimicry can be further explored to address underrepresented SDGs?

The remainder of this paper is arranged as follows. Section " Literature review " focuses on the literature background of biomimicry, followed by methods (section " Methods ") and results and discussion, including emerging research topics (section " Results and discussion "). Section " Conclusion " concludes with recommendations and limitations.

Literature review

The potential of biomimicry solutions for sustainability has long been recognized, yet there is a notable lack of comprehensive studies that explore how biomimicry can address specific sustainable development goals (SDGs) (Table 1 ). This research aims to fill this gap by investigating relevant themes and building upon the literature in this field.

Biomimicry, with its roots tracing back to approximately 500 BC, began with Greek philosophers who developed classical concepts of beauty and drew inspiration from natural organisms for balanced design 15 . This foundational idea of looking to nature for design principles continued through history, as exemplified by Leonardo Da Vinci's creation of a flying machine inspired by birds in 1482. This early instance of biomimicry influenced subsequent advancements, including the Wright brothers' development of the airplane in 1948 12 , 15 . The term "bionics," coined in 1958 to describe "the science of natural systems or their analogs," evolved into "biomimicry" by 1982. Janine Benyus's 1997 book, “Biomimicry: Innovation Inspired by Nature,” and the founding of the Biomimicry Institute (Biomimicry 16 ) were pivotal, positioning nature as a guide and model for sustainable design. Benyus’s work underscores the potential of biomimicry in tackling contemporary environmental challenges such as climate change and ecosystem degradation 12 , 17 .

In recent years, the call for more targeted research in biomimicry has grown, particularly in terms of architecture and energy use. Meena et al. 18 and Varshabi et al. 19 highlighted the need for biomimicry to address energy efficiency in building design, stressing the potential of nature-inspired solutions to reduce energy consumption and enhance sustainability. This perspective aligns with that of Perricone et al. 20 , who explored the differences between artificial and natural systems, noting that biomimetic designs, which mimic the principles of organism construction, can significantly improve resource utilization and ecosystem restoration. Aggarwal and Verma 21 contributed to this discourse by mapping the evolution and applications of biomimicry through scientometric analysis, revealing the growing significance of nature-inspired optimization methodologies, especially in clustering techniques. Their work suggested that these methodologies not only provide innovative solutions but also reflect a deeper integration of biomimetic principles in technological advancements. Building on this, Pinzón and Austin 22 emphasized the infancy of biomimicry in the context of renewable energy, advocating for more research to explore how nature can inspire new energy solutions. Their work connects with that of Carniel et al. 23 , who introduced a natural language processing (NLP) technique to identify research themes in biomimicry across disciplines, facilitating a holistic understanding of current trends and future directions.

To further illustrate the practical applications of biomimicry, Nasser et al. 24 presented the Harmony Search Algorithm (HSA), a nature-inspired optimization technique. Their bibliometric analysis demonstrated the algorithm's effectiveness in reducing energy and resource consumption, highlighting the practical benefits of biomimicry in technological innovation. Rusu et al. 25 expanded on these themes by documenting significant advancements in soft robotics, showing how biomimicry influences design principles and applications in this rapidly evolving field. Their findings underscore the diverse applications of biomimetic principles, from robotics to building design. Shashwat et al. 26 emphasized the role of bioinspired solutions in enhancing energy efficiency within the built environment, promoting the use of high solar reflectance surfaces that mimic natural materials. This perspective is in line with that of Pires et al. 27 , who evaluated the application of biomimicry in dental restorative materials and identified a need for more clinical studies to realize the full potential of biomimetic innovations in healthcare. Liu et al. 28 explored the application of nature-inspired design principles in software-defined networks, demonstrating how biomimetic algorithms can optimize resource and energy utilization in complex systems. This study builds on the broader narrative of biomimicry's potential to transform various sectors by offering efficient, sustainable solutions. Finally, Hinkelman et al. 29 synthesized these insights by discussing the transdisciplinary applications of ecosystem biomimicry, which supports sustainable development goals by integrating biomimetic principles across engineering and environmental disciplines. This comprehensive approach underscores the transformative potential of biomimicry, suggesting that continued interdisciplinary research and innovation are crucial for addressing global sustainability challenges effectively.

PRISMA framework

This study utilizes the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to structure its analysis, following the established five-step protocol: formulating research questions, defining a search strategy, executing a literature search, screening identified literature, and analyzing the findings (Page et al., 2021). The application of the PRISMA guidelines across various research domains, including the SDGs, is well documented 30 .

To ensure a comprehensive search, we searched the Scopus database, a widely utilized resource for bibliometric studies 31 (Donthu et al. 82 ), which led to the discovery of 46,141 publications from 2013 to 2023. This period marked significant research activity following the introduction of the SDGs at the Rio + 20 summit in 2012. Publications were identified using the following terms in the title and abstract: “ (biomimic* OR biomimetic* OR bioinspired OR bioinsp* OR bionic* OR nature-inspired OR "biologically inspired" OR bioinspiration OR biomimesis OR biognosis).”

During the screening phase, publications lacking complete author details were reviewed, narrowing the field to 46,083 publications for further analysis. The eligibility phase utilized proprietary algorithms to map publications to the 17 SDGs, informed by initiatives such as the University of Auckland (Auckland’s SDG mapping 32 ) and Elsevier's SDG Mapping Initiatives (Elsevier's SDG Mapping 33 ). The selection of the Elsevier SDG Mapping Initiative for this study was based on its seamless integration with Scopus, facilitating the use of predefined search queries for each SDG and employing a machine learning model that has been refined through expert review. This approach has been utilized in various studies to analyze research trends within emerging fields. For example, the exploration of green hydrogen was detailed by Raman et al. 34 , while investigations into Fake News and the Dark Web were conducted by Raman et al. 35 , 36 , 37 and Rama et al. 38 , respectively. These examples demonstrate the efficacy of SDG mapping in elucidating how research outputs align with and contribute to sustainable development goals in these emerging domains. This phase identified 13,287 publications as mapped to SDGs. In the inclusion phase, stringent criteria further filtered the publications to English-language journals and review articles, culminating in 13,271 publications deemed suitable for in-depth analysis. This process ensures a comprehensive and high-quality dataset for the study, reflecting the robust and systematic approach afforded by the PRISMA framework in evaluating literature relevant to SDGs.

Our keyword search strategy, while comprehensive, may capture papers that do not genuinely contribute to the field. To mitigate this, we employed manual verification. After the automated search, the authors conducted a manual review of a subset of the final set of identified papers to assess their relevance and authenticity in the context of biomimicry. The subset was based on 20 highly cited papers from each year. We believe that papers that are frequently cited within the community are more likely to be accurately classified. The authors mainly reviewed the introduction, methodology, and results sections to confirm the relevance and authenticity of the papers. However, we acknowledge that these steps may not fully eliminate the inclusion of irrelevant papers, which could skew the results of our meta-analysis.

SDG framework

The examination of sustainable development goals (SDGs) reveals their interconnected nature, where the achievement of one goal often supports progress in others. Studies by Le Blanc (2015) and Allison et al. (2016) have mapped out the complex web of relationships among the SDGs, identifying both strong and subtle linkages across different objectives. To visualize these connections, we employed a cocitation mapping approach using VOSviewer 39 , which allows us to depict the semantic relationships between SDGs through their cocitation rates in scholarly works. This approach generates a visual map where each SDG is represented as a node, with the node size reflecting the goal's research prominence and the thickness of the lines between nodes indicating the frequency of cocitations among the goals. This visual representation reveals the SDGs as an intricate but unified framework, emphasizing the collaborative nature of global sustainability initiatives.

Topic prominence percentile

The Scopus prominence percentile is a crucial metric indicating the visibility and impact of emerging research topics within the scientific community. High-ranking topics in this percentile are rapidly gaining attention, highlighting emerging trends and areas poised for significant advancements. This tool enables researchers and policymakers to identify and focus on innovative topics, ensuring that their efforts align with the forefront of scientific development 35 , 36 , 37 . Topics above the 99.9th percentile were used in this study.

Results and discussion

Rq1: sdg framework and interdisciplinary research (rq4).

This study evaluates biomimicry research through the framework of SDGs. A cocitation SDG map shows two clusters and provides insights into the interplay between biomimicry themes and SDGs, highlighting the cross-disciplinary nature of this research (Fig.  1 ). The blue box hidden behind the “3 – Good Health and Well-being” and “7 – Affordable and Clean Energy” is “11 – Sustainable cities and Communities”. The blue box hidden behind “15 – Life on Land” is “16 – Peace, Justice and Strong institutions”.

Interdisciplinary SDG network of biomimicry research.

Cluster 1 (Red): Biomimetic innovations for health, partnership, and life on land

This cluster comprises a diverse array of research articles that explore the application of biomimicry across various SDGs 3 (health), 17 (partnership), and 15 (land). The papers in this cluster delve into innovative biomimetic ideas, each contributing uniquely to the intersection of sustainable development and biological inspiration. SDG 3, emphasizing good health and well-being for all, is significantly represented, indicating a global effort to leverage biomimicry for advancements in healthcare, such as new medication delivery systems and medical technologies. Similarly, the frequent citations of SDG 17 underscore the vital role of partnerships in achieving sustainable growth, especially where bioinspired solutions require interdisciplinary collaboration to address complex challenges. Finally, the prominence of 15 SDG citations reflects a commitment to preserving terrestrial ecosystems, where biomimicry is increasingly applied in land management, demonstrating nature's adaptability and resilience as a model for sustainable practices. Table 2 lists the top 5 relevant papers from Cluster 1, further illustrating the multifaceted application of biomimicry in addressing these SDGs.

A unique binary variant of the gray wolf optimization (GWO) technique, designed especially for feature selection in classification tasks, was presented by Emary et al. 40 . GWO is a method inspired by the social hierarchy and hunting behavior of gray wolves to find the best solutions to complex problems. This bioinspired optimization technique was used to optimize SDG15, which also highlights its ecological benefits. The results of the study highlight the effectiveness of binary gray wolf optimization in identifying the feature space for ideal pairings and promoting environmental sustainability and biodiversity. Lin et al. 41 focused on SDG 3 by examining catalytically active nanomaterials as potential candidates for artificial enzymes. While acknowledging the limits of naturally occurring enzymes, this study explores how nanobiotechnology can address problems in the food, pharmaceutical, and agrochemical sectors.

The investigation of enzymatic nanomaterials aligns with health-related objectives, highlighting the potential for major improvements in human health. Parodi et al. 42 used biomimetic leukocyte membranes to functionalize synthetic nanoparticles, extending biomimicry into the biomedical domain. To meet SDG 3, this research presents "leukolike vectors," which are nanoporous silicon particles that can communicate with cells, evade the immune system, and deliver specific payloads. In line with the SDGs about health, this study emphasizes the possible uses of biomimetic structures in cancer detection and treatments. A novel strategy for biological photothermal nanodot-based anticancer therapy utilizing peptide‒porphyrin conjugate self-assembly was presented by Zou et al. 43 . For therapeutic reasons, efficient light-to-heat conversion can be achieved by imitating the structure of biological structures. By providing a unique biomimetic approach to cancer treatment and demonstrating the potential of self-assembling biomaterials in biomedical applications, this research advances SDG 3. Finally, Wang et al. 44 presented Monarch butterfly optimization (MBO), which is a bioinspired algorithm that mimics the migration patterns of monarch butterflies to solve optimization problems effectively. This method presents a novel approach to optimization, mimicking the migration of monarch butterflies, aligning with SDG 9. Comparative analyses highlight MBO's exceptional performance and demonstrate its capacity to address intricate issues about business and innovation, supporting objectives for long-term collaboration and sector expansion.

The publications in Cluster 1 show a wide range of biomimetic developments, from ecological optimization to new optimization techniques and biomedical applications. These varied contributions highlight how biomimicry can advance sustainable development in health, symbiosis, and terrestrial life.

Cluster 2 (green): Nature-inspired solutions for clean water, energy, and infrastructure

Cluster 2, which focuses on the innovative application of biomimicry in sustainable development, represents a range of research that aligns with SDGs 6 (sanitation), 7 (energy), 9 (infrastructure), and 14 (water). This cluster is characterized by studies that draw inspiration from natural processes and structures to offer creative solutions to sustainability-related challenges. The papers in this cluster, detailed in Table 3 , demonstrate how biomimicry can address key global concerns in a varied and compelling manner.

Within this cluster, the high citation counts for SDG 7 underscore the significance of accessible clean energy, a domain where biomimicry contributes innovative energy generation and storage solutions inspired by natural processes. This aligns with the growing emphasis on sustainable energy practices. The prominence of SDG 9 citations further highlights the global focus on innovation and sustainable industry, where biomimicry's role in developing nature-inspired designs is crucial for building robust systems and resilient infrastructure. Furthermore, the substantial citations for SDG 6 reflect a dedicated effort toward ensuring access to clean water and sanitation for all. In this regard, biomimicry principles are being applied in water purification technologies, illustrating how sustainable solutions modeled after natural processes can effectively meet clean water objectives.

The study by Sydney Gladman et al. (2016), which presented the idea of shape-morphing systems inspired by nastic plant motions, is one notable addition to this cluster. This discovery creates new opportunities for tissue engineering, autonomous robotics, and smart textile applications by encoding composite hydrogel designs that exhibit anisotropic swelling behavior. The emphasis of SDG 9 on promoting industry, innovation, and infrastructure aligns with this biomimetic strategy. SDGs 7 and 13 are addressed in the study of Li et al. 45 , which is about engineering heterogeneous semiconductors for solar water splitting. This work contributes to the goals of inexpensive, clean energy and climate action by investigating methods such as band structure engineering and bionic engineering to increase the efficiency of solar water splitting. Li et al. 46 conducted a thorough study highlighting the importance of catalysts for the selective photoreduction of CO2 into solar fuels. This review offers valuable insights into the use of semiconductor catalysts for selective photocatalytic CO2 reduction. Our work advances sustainable energy solutions by investigating biomimetic, metal-based, and metal-free cocatalysts and contributes to SDGs 7 and 13. Wang et al. 47 address the critical problem of water pollution. Creating materials with superlyophilic and superlyophobic qualities offers a creative method for effectively separating water and oil. This contributes to the goals of clean water, industry, innovation, and life below the water. It also correlates with SDGs 6, 9, and 14. Singh et al. 48 also explored the 'green' synthesis of metals and their oxide nanoparticles for environmental remediation, which furthers SDG 9. This review demonstrates the environmentally benign and sustainable features of green synthesis and its potential to lessen the environmental impact of conventional synthesis methods.

Cluster 2 provides nature-inspired solutions for clean water, renewable energy, and sustainable infrastructure, demonstrating the scope and importance of biomimicry. The varied applications discussed in these papers help overcome difficult problems and advance sustainable development in line with several SDGs.

RQ2: Emerging research topics

Temporal evolution of emerging topics.

Figure  2 displays the publication counts for various emerging topics from 2013 to 2022, indicating growth trends over the years. For 'Metaheuristics', there is a notable increase in publications peaking in approximately 2020, suggesting a surge in interest. 'Strain sensor' research steadily increased, reaching its highest publication frequency toward the end of the period, which is indicative of growing relevance in the field. 'Bioprinting' sharply increased over the next decade, subsequently maintaining high interest, which highlights its sustained innovation. In contrast, 'Actuators' showed fluctuating publication counts, with a recent upward trend. 'Cancer' research, while historically a major topic, displayed a spike in publications in approximately 2018, possibly reflecting a breakthrough or increased research funding. 'Myeloperoxidase' has a smaller presence in the literature, with a modest peak in 2019. The number of 'Water '-related publications remains relatively low but shows a slight increase, suggesting a gradual but increasing recognition of its importance. Research on exosomes has significantly advanced, particularly since 2018, signifying a greater area of focus. 'Mechanical' topic publications have moderate fluctuations without a clear trend, indicating steady research interest. 'Micromotors' experienced an initial publication surge, followed by a decline and then a recent resurgence, possibly due to new technological applications. 'Nanogenerators' have shown a dramatic increase in interest, particularly in recent years, while 'Hydrogel' publications have varied, with a recent decline, which may point toward a shift in research focus or maturity of the topic.

Evolution of emerging topics according to publications (y-axis denotes the number of publications; x-axis denotes the year of publication).

Figure  3 presents the distribution of various research topics based on their prominence percentile and total number of publications. Topics above the 99.9th percentile and to the right of the vertical threshold line represent the most emergent and prolific topics of study. Next, we examine the topics within each of the four quadrants, focusing on how each topic has developed over the years in relation to SDGs and the key phrases associated with each topic.

Distribution of research topics based on prominence percentile and total number of publications.

Next, we examine each research topic in four quadrants, assessing their evolution concerning SDGs. We also analyze the keyphrase cloud to identify which keyphrases are most relevant (indicated by their font size) and whether they are growing or not. In the key phrase cloud, green indicates an increasing relevance of the key phrase, grey signifies that its relevance remains constant, and blue represents a declining relevance of the key phrase.

Niche biomimetic applications

These are topics with a lower number of publications and prominence percentiles, indicating specialized or emerging areas of research that are not yet widely recognized or pursued (Quadrant 1—bottom left).

Myeloperoxidase; colorimetric; chromogenic compounds

The inclusion of myeloperoxidase indicates that inflammation and the immune system are the main research topics. The focus on chromogenic and colorimetric molecules suggests a relationship to analytical techniques for identifying biological materials. The evolution of the research is depicted in Fig.  4 a shows an evolving emphasis on various sustainable development goals (SDGs) over time. The research trajectory, initially rooted in SDG 3 (Good Health and Well-being), has progressively branched out to encompass SDG 7 (Affordable and Clean Energy) and SDG 6 (Clean Water and Sanitation), reflecting an expanding scope of inquiry within the forestry sciences. More recently, the focus has transitioned toward SDG 15 (Life on Land), indicating an increased recognition of the interconnectedness between forest ecosystems and broader environmental and sustainability goals. This trend underscores the growing complexity and multidisciplinary nature of forestry research, highlighting the need to address comprehensive ecological concerns along with human well-being and sustainable development.

Evolution of research ( a ) and key phrases ( b ).

The word cloud in Fig.  4 b highlights key phrases such as 'Biocompatible', 'Actuator', and 'Self-healing Hydrogel', reflecting a focus on advanced materials, while terms such as 'Elastic Modulus' and 'Polymeric Networks' suggest an emphasis on the structural properties essential for creating innovative diagnostic and environmental sensing tools. Such developments are pertinent to health monitoring and water purification, resonating with SDG 3 (Good Health and Well-being) and SDG 6 (Clean Water and Sanitation). The prominence of 'Self-healing' and 'Bioinspired' indicates a shift toward materials that emulate natural processes for durability and longevity, supporting sustainable industry practices aligned with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), contributing to the overarching aim of sustainable development.

Next, we analyzed the top 3 cited publications. Catalytically active nanomaterials, or nanozymes, are exciting candidates for artificial enzymes, according to Lin et al. 41 . The authors explore the structural features and biomimetics applications of these enzymes, classifying them as metal-, carbon-, and metal oxide-based nanomaterials. This study emphasizes the benefits of enzymes over natural enzymes, including their high stability, variable catalytic activity, and controlled production. Wang et al. 49 developed biomimetic nanoflowers made from nanozymes to cause intracellular oxidative damage in hypoxic malignancies. Under both normoxic and hypoxic conditions, the nanoflowers demonstrated catalytic efficiency. By overcoming the constraints of existing systems that depend on oxygen availability or external stimuli, this novel technique represents a viable treatment option for malignant neoplasms. Gao et al. 50 investigated the use of a dual inorganic nanozyme-catalyzed cascade reaction as a biomimetic approach for nanocatalytic tumor therapy. This approach produces a high level of therapeutic efficacy by cascading catalytic events inside the tumor microenvironment. This study highlights the potential of inorganic nanozymes for achieving high therapeutic efficacy and outstanding biosafety, which adds to the growing interest in nanocatalytic tumor therapy.

Water; hydrophobicity; aerogels

With an emphasis on hydrophobicity, aerogel use, and water-related features, this topic relates to materials science and indicates interest in cutting-edge materials with unique qualities. From Fig.  5 a, we can see that, initially, the focus was directed toward SDG 6 (Clean Water and Sanitation), which is intrinsically related to the research theme, as biomimetic approaches are leveraged to develop innovative water purification and management solutions. As the research progressed, the scope expanded to intersect with SDG 14 (Life Below Water) and SDG 7 (Affordable and Clean Energy), signifying a broadened impact of biomimetic innovations in marine ecosystem conservation and energy-efficient materials. The gradual involvement with SDG 9 (industry, innovation, and infrastructure) and SDG 13 (climate action) indicates the interdisciplinary reach of this research, which aims to influence industrial practices and climate change mitigation strategies.

The word cloud in Fig.  5 b reinforces this narrative by showcasing key phrases such as 'Hydrophobic', 'Bioinspired', 'Emulsion', and 'Oil Pollution', which reflect the emphasis on developing materials and technologies that mimic natural water repellency and separation processes. 'Aerogel' and 'polydopamine', along with 'Underwater' and 'Biomimetic Cleaning', suggest a strong focus on creating lightweight, efficient materials capable of self-cleaning and oil spill remediation. These keywords encapsulate the essence of the research theme, demonstrating a clear alignment with the targeted SDGs and the overall aim of sustainable development through biomimicry.

Three highly referenced works that have made substantial contributions to the field of biomimetic materials for oil/water separation are included in the table. The development of superlyophilic and superlyophobic materials for effective oil/water separation was examined by Wang et al. 47 . This review highlights the applications of these materials in separating different oil-and-water combinations by classifying them according to their surface wettability qualities. The excellent efficiency, selectivity, and recyclability of the materials—which present a viable treatment option for industrial oily wastewater and oil spills—are highlighted in the paper. Su et al. 51 explored the evolution of super wettability systems. The studies included superhydrophobicity, superoleophobicity, and undersea counterparts, among other extreme wettabilities. The kinetics, material structures, and wetting conditions related to obtaining superwettability are covered in the article. This demonstrates the wide range of uses for these materials in chemistry and materials science, including self-cleaning fabrics and systems for separating oil and water. Zhang et al. 52 presented a bioinspired multifunctional foam with self-cleaning and oil/water separation capabilities. To construct a polyurethane foam with superhydrophobicity and superoleophobicity, this study used porous biomaterials and superhydrophobic self-cleaning lotus leaves. Foam works well for separating oil from water because of its slight weight and ability to float on water. It also shows exceptional resistance to corrosive liquids. According to the article, multifunctional foams for large-scale oil spill cleaning might be designed using a low-cost fabrication technology that could be widely adopted.

Growing interest in bioinspired healthcare

These topics have a higher prominence percentile but a lower number of publications, suggesting growing interest and importance in the field despite a smaller body of research (Quadrant 2—top left).

Exosomes; extracellular vesicles; MicroRNAs

Exosomes and extracellular vesicles are essential for intercellular communication, and reference to microRNAs implies a focus on genetic regulation. The evolution of this topic reflects an increasing alignment with specific sustainable development goals (SDGs) over the years. The initial research focused on SDG 3 (good health and well-being) has expanded to encompass SDG 9 (industry, innovation, and infrastructure) and SDG 6 (clean water and sanitation), showcasing the multifaceted impact of biomimetic research in healthcare (Fig.  6 a). The research trajectory into SDG 9 and SDG 6 suggests broader application of bioinspired technologies beyond healthcare, potentially influencing sustainable industrial processes and water treatment technologies, respectively.

The word cloud (Fig.  6 b) underscores the central role of 'Extracellular Vesicles' and 'Exosomes' as platforms for 'Targeted Drug Delivery' and 'Nanocarrier' systems, which are key innovations in medical biotechnology. The prominence of terms such as 'Bioinspired', 'Biomimetic', 'Liposome', and 'Gold Nanoparticle' illustrates the inspiration drawn from biological systems for developing advanced materials and delivery mechanisms. These key phrases indicate significant advancements in 'Controlled Drug Delivery Systems', 'Cancer Chemotherapy', and 'Molecular Imaging', which have contributed to improved diagnostics and treatment options, consistent with the objectives of SDG 3.

The work by Jang et al. 53 , which introduced bioinspired exosome-mimetic nanovesicles for improved drug delivery to tumor tissues, is one of the most cited articles. These nanovesicles, which resemble exosomes but have higher creation yields, target cells and slow the growth of tumors in a promising way. Yong et al.'s 54 work presented an effective drug carrier for targeted cancer chemotherapy, focusing on biocompatible tumor cell-exocytosed exosome-biomimetic porous silicon nanoparticles. A paper by Cheng et al. 55 discussed the difficulties in delivering proteins intracellularly. This study suggested a biomimetic nanoparticle platform that uses extracellular vesicle membranes and metal–organic frameworks. These highly cited studies highlight the importance of biomimetic techniques in improving drug delivery systems for improved therapeutic interventions.

Nanogenerators; piezoelectric; energy harvesting

This topic advises concentrating on technology for energy harvesting, especially for those that use piezoelectric materials and nanogenerators. We see a rising focus on medical applications of biomimetics, from diagnostics to energy harvesting mimicking biological systems.

The evolution of this research topic reflects a broader contribution to the SDGs by not only addressing healthcare needs but also by promoting sustainable energy practices and supporting resilient infrastructure through biomimetic innovation (Fig.  7 a). Initially, the emphasis on SDG 3 (Good Health and Well-being) suggested the early application of biomimetic principles in healthcare, particularly in medical devices and diagnostics leveraging piezoelectric effects. Over time, the transition toward SDG 7 (Affordable and Clean Energy) and SDG 9 (Industry, Innovation, and Infrastructure) indicates an expansion of bioinspired technologies into sustainable energy solutions and industrial applications. Nanogenerators and energy harvesting techniques draw inspiration from biological processes and structures, aiming to optimize energy efficiency and contribute to clean energy initiatives.

The word cloud in Fig.  7 b emphasizes key phrases such as 'Piezoelectric', 'Energy Harvesting', 'Tactile Sensor', 'Triboelectricity', and 'Nanogenerators', highlighting the core technologies that are being developed. These terms, along with 'Bioinspired', 'Wearable Electronic Devices', and 'Energy Conversion Efficiency', illustrate the convergence of natural principles with advanced material science to create innovative solutions for energy generation and sensor technology.

Yang et al.'s 56 study in Advanced Materials presented the first triboelectrification-based bionic membrane sensor. Wearable medical monitoring and biometric authentication systems will find new uses for this sensor since it allows self-powered physiological and behavioral measurements, such as noninvasive human health evaluation, anti-interference throat voice recording, and multimodal biometric authentication. A thorough analysis of the state-of-the-art in piezoelectric energy harvesting was presented by Sezer and Koç 57 . This article addresses the fundamentals, components, and uses of piezoelectric generators, highlighting their development, drawbacks, and prospects. It also predicts a time when piezoelectric technology will power many electronics. The 2021 paper by Zhao et al. 58 examines the use of cellulose-based materials in flexible electronics. This section describes the benefits of these materials and the latest developments in intelligent electronic device creation, including biomimetic electronic skins, optoelectronics, sensors, and optoelectronic devices. This review sheds light on the possible drawbacks and opportunities for wearable technology and bioelectronic systems based on cellulose.

Leading edge of biomimetic sensing and electronics

This quadrant represents topics with both a high number of publications and a prominence percentile, indicating well-established and influential research areas (Quadrant 3—top right).

Strain sensor; flexible electronics; sensor

Figure  8 a highlights the progress of research on bioinspired innovations, particularly in the development of strain sensors and flexible electronics for adaptive sensing technologies. Initially, concentrated on health applications aligned with SDG 3 (Good Health and Well-being), the focus has expanded. The integration of SDG 9 (Industry, Innovation, and Infrastructure) indicates a shift toward industrial applications, while the incorporation of SDG 7 (Affordable and Clean Energy) suggests a commitment to energy-efficient solutions. Additionally, the mention of SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Consumption and Production) reflects the broadening scope to include urban sustainability and eco-friendly manufacturing practices.

Figure  8 b provides insight into the key phrases associated with this research topic, highlighting terms such as 'Bioinspired', 'Self-healing', 'Wearable Electronic Devices', 'Flexible Electronics', and 'Pressure Sensor'. These key phrases speak to the innovative approaches for creating sensors and electronics that are not only inspired by biological systems but also capable of seamlessly integrating human activity and environmental needs. The mention of 'Wearable Sensors' and 'Tactile Sensor' indicates a focus on user interaction and sensitivity, which is crucial for medical applications and smart infrastructure.

The top three articles with the most citations represent the cutting edge of this topic’s study. Chortos et al. 59 investigated how skin characteristics can be replicated for medicinal and prosthetic uses. Kim et al. 60 focused on creating ultrathin silicon nanoribbon sensors for smart prosthetic skin, opening up new possibilities for bionic systems with many sensors. A bioinspired microhairy sensor for ultraconformability on nonflat surfaces was introduced in Pang et al.'s 61 article, which significantly improved signal-to-noise ratios for accurate physiological measurements.

Cancer; photoacoustics; theranostic nanomedicine

Modern technologies such as photoacoustics, theranostic nanomedicine, and cancer research suggest that novel cancer diagnosis and therapy methods are highly needed. Figure  9 a traces the research focus that has evolved across various SDGs over time, commencing with SDG 3 (Good Health and Well-being), which is indicative of the central role of health in biomimetic research. It then extends into SDG 9 (Industry, Innovation, and Infrastructure) and SDG 7 (Affordable and Clean Energy), illustrating the cross-disciplinary applications of biomimetic technologies from healthcare to the energy and industrial sectors.

Figure  9 b provides a snapshot of the prominent keywords within this research theme, featuring terms such as “photodynamic therapy”, “photothermal chemotherapy”, “nanocarrier”, and “controlled drug delivery”. These terms underscore the innovative therapeutic strategies that mimic biological mechanisms for targeted cancer treatment. 'Bioinspired' and 'Biomimetic Synthesis' reflect the approach of deriving design principles from natural systems for the development of advanced materials and medical devices. 'Theranostic nanomedicine' integrates diagnosis and therapy, demonstrating a trend toward personalized and precision medicine.

A study conducted by Yu et al. 62 presented a novel approach for synergistic chemiexcited photodynamic-starvation therapy against metastatic tumors: a biomimetic nanoreactor, or bio-NR. Bio-NRs use hollow mesoporous silica nanoparticles to catalyze the conversion of glucose to hydrogen peroxide for starvation therapy while also producing singlet oxygen for photodynamic therapy. Bio-NR is promising for treating cancer metastasis because its coating on cancer cells improves its biological qualities. Yang et al.'s 63 study focused on a biocompatible Gd-integrated CuS nanotheranostic agent created via a biomimetic approach. This drug has low systemic side effects and good photothermal conversion efficiency, making it suitable for skin cancer therapy. It also performs well in imaging. The ultrasmall copper sulfide nanoparticles generated within ferritin nanocages are described in Wang et al.’s 64 publication. This work highlights the possibility of photoacoustic imaging-guided photothermal therapy with improved therapeutic efficiency and biocompatibility. These highly referenced articles highlight the significance of biomimetic techniques in furthering nanotheranostics and cancer therapy.

Established biomimetic foundations

Here, there are topics with a greater number of publications but a lower prominence percentile, which may imply areas where there has been significant research but that may be waning in influence or undergoing a shift in focus (Quadrant 4—bottom right).

Metaheuristics; Fireflies; Chiroptera

This topic is a fascinating mix of subjects. Using Firefly and Chiroptera in metaheuristic optimization algorithms provides a bioinspired method for resolving challenging issues. The thematic progression of research papers suggests the maturation of biomimetic disciplines that resonate with several SDGs (Fig.  10 a). The shift from initially aligning with SDG 3 (Good Health and Well-being) extends to intersecting with goals such as SDG 9 (Industry, Innovation, and Infrastructure), SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land). This diversification reflects the expansive utility of biomimetic approaches, from health applications to broader environmental and societal challenges.

The top keyphrases, such as 'Swarm Intelligence', 'Global Optimization', 'Cuckoo Search Algorithm', and 'Particle Swarm Optimization', are shown in Fig.  10 b highlights the utilization of nature-inspired algorithms for solving complex optimization problems. These terms, along with the 'Firefly Algorithm' and 'Bat Algorithm', underscore the transition of natural phenomena into computational algorithms that mimic the behavioral patterns of biological organisms, offering robust solutions in various fields, including resource management, logistics, and engineering design.

The three highly referenced metaheuristic publications centered around the “Moth Flame Optimization (MFO),” Salp Swarm Algorithm (SSA),” and Whale Optimization Algorithm (WOA).” The WOA, authored by Mirjalili and Lewis 65 , is a competitive solution for mathematical optimization and structural design issues because it emulates the social behavior of humpback whales. Inspired by the swarming behavior of salps, Mirjalili et al. 66 introduced the SSA and multiobjective SSA. This shows how well they function in optimizing a variety of engineering design difficulties. Finally, Mirjalili 67 suggested the MFO algorithm, which is modeled after the navigational strategy of moths and exhibits competitive performance in resolving benchmark and real-world engineering issues.

Bioprinting; three-dimensional printing; tissue engineering

The emphasis on sophisticated manufacturing methods for biological applications in this field suggests a keen interest in the nexus of biology and technology, especially in tissue engineering. As shown in Fig.  11 a, the topic's evolution encompasses Sustainable Development Goals (SDGs) that have transitioned over the years, including SDG 3 (Good Health and Well-being), which is inherently connected to the advancement of medical technologies and tissue engineering for health applications. This research also touches upon SDG 6 (Clean Water and Sanitation) and SDG 7 (Affordable and Clean Energy), suggesting applications of bioprinting technologies in the environmental sustainability and energy sectors. The progression toward SDG 9 (Industry, Innovation, and Infrastructure) and SDG 15 (Life on Land) reflects a broader impact, where biomimetic principles are applied to foster innovation in industrial processes and contribute to the preservation of terrestrial ecosystems.

Key phrases emerging from the word cloud in Fig.  11 b, such as “Hydrogel”, “Biofabrication”, “Tissue Scaffold”, and “Regenerative Medicine”, highlight the specialized methodologies and materials that are inspired by natural processes and structures. Terms such as 'Three-Dimensional Printing' and 'Bioprinting' underscore the technological advancements in creating complex biological structures, aiming to revolutionize the field of tissue engineering and regenerative medicine.

Three widely referenced papers about advances in 3D printing—particularly in bioprinting, soft matter, and the incorporation of biological tissue with functional electronics—are described next. Truby and Lewis’s 68 review of light- and ink-based 3D printing techniques is ground-breaking. This highlights the technology's capacity to create soft matter with tunable properties and its potential applications in robotics, shape-morphing systems, biologically inspired composites, and soft sensors. Ozbolat, and Hospodiuk 69 provide a thorough analysis of “extrusion-based bioprinting (EBB).” The adaptability of EBB in printing different biologics is discussed in the paper, with a focus on its uses in pharmaceutics, primary research, and clinical contexts. Future directions and challenges in EBB technology are also discussed. Using 3D printing, Mannoor et al. 70 presented a novel method for fusing organic tissue with functioning electronics. In the proof-of-concept, a hydrogel matrix seeded with cells and an interwoven conductive polymer containing silver nanoparticles are 3D printed to create a bionic ear. The improved auditory sensing capabilities of the printed ear show how this novel technology allows biological and nanoelectronic features to work together harmoniously.

RQ3: Translation and commercialization

Biomimicry offers promising solutions for sustainability in commercial industries with environmentally sustainable product innovation and energy savings with reduced resource commitment 71 . However, translating biomimicry innovations from research to commercialization presents challenges, including product validation, regulatory hurdles, and the need for strategic investment, innovative financial models, and interdisciplinary collaboration 71 , 72 , 73 , 74 . Ethical considerations highlight the need for universally applicable ethical guidelines regarding the moral debates surrounding biomimicry, such as motivations for pursuing such approaches and the valuation of nature 75 .

Addressing these barriers requires interdisciplinary collaboration, targeted education, and training programs. Strategic investment in biomimicry research and development is also crucial. Encouraging an engineering mindset that integrates biomimicry principles into conventional practices and developing commercial acumen among researchers is essential for navigating the market landscape 76 . Securing sufficient funding is essential for the development, testing, and scaling of these innovations 76 .

Successful case studies illustrate that the strategic integration of biomimicry enhances corporate sustainability and innovation (Larson & Meier 2017). In biomedical research, biomimetic approaches such as novel scaffolds and artificial skins have made significant strides (Zhang 2012). Architecture benefits through energy-efficient building facades modeled after natural cooling systems (Webb et al. 2017). The textile industry uses biomimicry to create sustainable, high-performance fabrics 77 .

RQ4: Interdisciplinary collaboration

Agricultural innovations (sdgs 1—no poverty and 2—zero hunger).

Environmental degradation, biodiversity loss, poverty, and hunger highlight the need for sustainable agricultural methods to mimic natural ecosystems. This includes computational models for ecological interactions, field experiments for biomimetic techniques, and novel materials inspired by natural soil processes. Research can develop solutions such as artificial photosynthesis for energy capture, polyculture systems mimicking ecosystem diversity, and bioinspired materials for soil regeneration and water retention 28 . These innovations can improve sustainability and energy efficiency in agriculture, addressing poverty and hunger through sustainable farming practices.

Educational models (SDG 4—Quality education)

Integrating sustainability principles and biomimicry into educational curricula at all levels presents opportunities for innovation. Collaborations between educators, environmental scientists, and designers can create immersive learning experiences that promote sustainability. This includes interdisciplinary curricula with biomimicry case studies, digital tools, and simulations for exploring biomimetic designs, and participatory learning approaches for engaging students with natural environments. Designing biomimicry-based educational tools and programs can help students engage in hands-on, project-based learning 10 , fostering a deeper understanding of sustainable living and problem-solving.

Gender-inclusive design (SDG 5—Gender inequality)

Gender biases in design and innovation call for research into biomimetic designs and technologies that facilitate gender equality. This includes participatory design processes involving women as cocreators, studying natural systems for inclusive strategies, and applying biomimetic principles to develop technologies supporting gender equality. Bioinspired technologies can address women's specific needs, enhancing access to education, healthcare, and economic opportunities. Interdisciplinary approaches involving gender studies, engineering, and environmental science can uncover new pathways for inclusive innovation.

Inclusive urban solutions (SDG 11—Sustainable cities and communities)

Rapid urbanization challenges such as housing shortages, environmental degradation, and unsustainable transportation systems require innovative solutions. Methodologies include systems thinking in urban planning, simulation tools for modeling biomimetic solutions, and pilot projects testing bioinspired urban innovations. Research on biomimetic architecture for affordable housing, green infrastructure for climate resilience, and bioinspired transportation systems can offer solutions. Collaborative efforts among architects, urban planners, ecologists, and sociologists are essential 78 .

Peace and justice (SDG 16—Peace, justice and institutions)

Social conflicts and weak institutions necessitate innovative approaches that integrate political science, sociology, and biology. Methods involve case studies, theoretical modeling, and participatory action research to develop strategies for peacebuilding and institutional development.

This research provides a comprehensive exploration of the multifaceted dimensions of biomimicry, SDG alignment, and interdisciplinary topics, demonstrating a clear trajectory of growth and relevance. Interdisciplinary collaboration has emerged as a pivotal strategy for unlocking the full potential of biomimicry in addressing underexplored SDGs.

While answering RQ1, the interdisciplinary analysis underscores the significant alignment of biomimicry research with several SDGs. This reflects the interdisciplinary nature of biomimicry and its ability to generate solutions for societal challenges. The analysis of two thematic clusters revealed the broad applicability of biomimicry across various sustainable development goals (SDGs). The first cluster includes health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's potential in medical technologies, sustainability collaborations, and land management. The second cluster encompasses clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), demonstrating innovative approaches to clean energy generation, sustainable infrastructure, and water purification.

In response to RQ2, this study highlights emerging topics within biomimicry research, such as metaheuristics and nanogenerators, which reflect a dynamic and evolving field that is swiftly gaining attention. These topics, alongside sensors, flexible electronics, and strain sensors, denote evolving research objectives and societal demands, pointing to new areas of study and innovation. This focus on interdisciplinary topics within biomimicry underscores the field’s adaptability and responsiveness to the shifting landscapes of technological and societal challenges.

In addressing RQ3, biomimicry holds potential for sustainable innovation but faces challenges in commercialization. Biomimicry inspires diverse technological and product innovations, driving sustainable advancements (Lurie-Luke 84 ). Overcoming these barriers through strategic investment, training, interdisciplinary collaboration, and ethical guidelines is essential for unlocking their full potential.

For RQ4 , the recommendations are formulated based on underexplored SDGs like 1, 4, 5, and 10 where biomimicry could play a pivotal role.

Future research could apply generative AI models to this dataset to validate the findings and explore additional insights. While our current study did not explore this topic, we see significant potential for this approach. Generative AI models can process extensive datasets and reveal patterns, potentially offering insights into biomimetic research correlations. The interpretation required for context-specific analysis remains challenging for generative AI 36 , 37

Our study provides valuable insights, but some limitations are worth considering. The chosen database might limit the comprehensiveness of the research captured, potentially excluding relevant work from other sources. Additionally, while the combination of cocitation mapping and BERTopic modeling provides a powerful analysis, both methods have inherent limitations. They may oversimplify the complexities of the field or introduce bias during theme interpretation, even with advanced techniques. Furthermore, our use of citations to thematically clustered publications as a proxy for impact inherits the limitations of citation analysis, such as biases toward established ideas and potential misinterpretations 79 , 80 . Another limitation of our study is the potential for missing accurate SDG mappings, as multiple SDG mapping initiatives are available, and our reliance on a single, Scopus-integrated method may not capture all relevant associations. Consequently, this could have resulted in the exclusion of papers that were appropriately aligned with certain SDGs but were not identified by our chosen mapping approach. Given these limitations, this study provides a valuable snapshot for understanding biomimicry research.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

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REVIEW article

Crafting personalized learning paths with ai for lifelong learning: a systematic literature review.

• 1 Business School, Tecnologico de Monterrey, Faculty of Informatics, Autonomous University of Querétaro, Monterrey, Mexico
• 2 EGADE Business School, Institute for the Future of Education, Tecnologico de Monterrey, Monterrey, Mexico
• 3 Faculty of Informatics, Autonomous University of Querétaro, Juriquilla, Mexico

The rapid evolution of knowledge requires constantly acquiring and updating skills, making lifelong learning crucial. Despite decades of artificial intelligence, recent advances promote new solutions to personalize learning in this context. The purpose of this article is to explore the current state of research on the development of artificial intelligence-mediated solutions for the design of personalized learning paths. To achieve this, a systematic literature review (SRL) of 78 articles published between 2019 and 2024 from the Scopus and Web or Science databases was conducted, answering seven questions grouped into three themes: characteristics of the published research, context of the research, and type of solution analyzed. This study identified that: (a) the greatest production of scientific research on the topic is developed in China, India and the United States, (b) the focus is mainly directed towards the educational context at the higher education level with areas of opportunity for application in the work context, and (c) the development of adaptive learning technologies predominates; however, there is a growing interest in the application of generative language models. This article contributes to the growing interest and literature related to personalized learning under artificial intelligence mediated solutions that will serve as a basis for academic institutions and organizations to design programs under this model.

Today, lifelong learning has become an imperative to thrive in an ever-changing and evolving world. The quest for knowledge is no longer limited to traditional classrooms; instead, it has transformed into a personalized and adaptive journey that spans a lifetime. The individual’s life cycle can no longer be divided into a period of preparation followed by a period of action, but rather learning extends throughout all stages of life ( UNESCO, 2022 ). Promoting lifelong learning means creating systems that realize the right to education for people of all ages and provide opportunities to unleash their potential. Within the framework of the Sustainable Development Goals (SDGs) as guiding axes of the 2030 Agenda of the United Nations Educational Scientific and Cultural Organization (UNESCO), SDG 4 promotes ensuring inclusive quality education and promoting lifelong learning opportunities for people ( UNESCO, 2017 ). The Organization for Economic Cooperation and Development (OECD) proposes four fundamental characteristics for lifelong learning: a systematic vision that includes both formal and informal educational contexts, the centrality of the learner by placing him/her as the focus of learning, the motivation to learn by developing the ability to “learn to learn” through self-regulated and self-directed learning, and the focus on a multi-objective education where learning priorities and goals can be transformed throughout the individual’s life ( OECD, 2009 ), in addition to the above, the recognition of the evolution of the concept of a single job for life makes it imperative for workers’ organizations to direct their efforts towards the development of new skills and lifelong learning ( Organización Internacional del Trabajo, 2020 ). With a view to increasing the life expectancy and quality of life of individuals, the study and development of lifelong learning options is becoming increasingly relevant.

Despite the growing recognition of the importance of lifelong learning, there is a significant gap in understanding how to effectively personalize learning experiences to meet the diverse and evolving needs of individuals throughout their lives. Traditional educational methods often fall short in providing the flexibility and adaptability required for lifelong learning. This gap necessitates the exploration of innovative solutions to enhance the personalization of learning experiences.

In this context, artificial intelligence (AI) emerges as a powerful and transformative ally, enabling the creation of personalized and effective learning experiences capable of adapting to the priorities and needs of the individual at a specific point in his or her life. The integration of AI-assisted learning solutions are key to the modernization of education as they have the ability to create motivating and quality learning environments ( Zhang et al., 2023 ). Artificial intelligence chatbots, for example, can provide individualized instruction and feedback based on the needs and progress of each learner, revolutionizing the concept of personalized learning ( Osamor et al., 2023 ). With the advent of generative language models, AI has reached new heights of capability and versatility, sparking unprecedented interest in its application for the design of learning trajectories ( Ifelebuegu, 2023 ). Because of its ability to transform education by offering motivating and personalized experiences that are tailored to individual needs, AI is positioned as an ally for lifelong learning.

The application of AI in educational contexts is not only based on the development of learning objects or tools for their creation but encompasses a wide range of applications. For the personalization of AI-mediated learning, researchers can opt for solutions such as mobile learning, educational games, collaborative learning in social networks, MOOCs or the application of augmented reality, among many others ( Hamal et al., 2022 ; Del Campo et al., 2023 ), without leaving aside the conversion towards an assessment of learning focused on complex thinking skills, avoiding the implicit risk of bad practices in the use of AI by students that constitute a threat to the legitimacy of online assessment and academic integrity ( Ifelebuegu, 2023 ). It is necessary, then, to consider that the use of IA in the educational context involves risks and limitations, among which are the problems of privacy, misinformation, plagiarism, biases and cultural differences and the lack of human connection, as well as other ethical implications, especially the gaps that may arise between students with access to these new technologies and those students who will be left behind due to the impossibility of access to these new educational models ( Wang et al., 2023 ; Bulathwela et al., 2024 ). Finally, it is important to note that the adoption of AI is not in itself the answer to meet the educational challenges in higher education and its use must be accompanied by a correct pedagogical design ( O’dea and O’Dea, 2023 ; Osamor et al., 2023 ). The adoption of AI in the educational context implies enormous advantages, however it is necessary to adopt a careful approach that allows minimizing its risks and maximizing its benefits in the development of solutions for the personalization of learning under a sound pedagogical design as an indispensable complement to this process. This research uses systematic literature review (SLR) to identify design strategies for artificial intelligence solutions in learning personalization. It aims to provide a broad overview of the current state of AI in learning personalization, highlight key areas of research, and advance the use of AI to enhance personalized learning in lifelong learning by proposing recommendations based on the findings to advance the integration of AI in personalized lifelong learning environments. The results contribute to the advancement of AI in learning personalization, key to educational innovation.

Lifelong learning.

The growing need for adults to acquire new skills and knowledge to advance their careers, address personal problems, or start and manage ventures has generated a growing interest in designing online education programs that are tailored to their specific needs and characteristics. In today’s evolving work environment, students entering the job market must demonstrate not only performance, but also collaboration, negotiation, planning, and organizational skills ( Partnership for 21st Century Learning, 2019 ). The labor market is experiencing a shift toward complex “hybrid” jobs with emerging roles. This transition reflects a movement from manufacturing to service-oriented industries, reducing the demand for mechanical-routine workers and emphasizing the need for autonomous, flexible, and creative individuals capable of problem solving ( Chiappe et al., 2020 ). The European Area of Lifelong Learning (2021) defines lifelong learning as any learning activity undertaken throughout life to improve knowledge, skills and competences with a personal, civic, social or occupational perspective. Adult education, especially in the context of lifelong learning, is a field that has become increasingly important in an ever-changing world. The idea that learning is a continuous process throughout life has become a fundamental principle.

Lifelong learning is crucial for the continued development and progress of individuals throughout their lives. Lifelong learning is important for several reasons. Firstly, it allows individuals to continuously acquire new knowledge and skills, enabling personal and professional growth throughout their lives ( Merriam et al., 2007 ). Secondly lifelong learning also promotes community well-being and contributes to social cohesion ( Merriam and Kee, 2014 ). Thirdly, it can enhance political stability and non-violence by fostering a culture of learning and knowledge acquisition ( Asongu and Nwachukwu, 2016 ). Fourthly lifelong learning is crucial for adapting to the changing demands of the labor market, as it helps individuals stay relevant and employable ( Schultheiss and Backes-Gellner, 2023 ), and lastly, it can also promote equality by providing opportunities for disadvantaged individuals to access education and improve their socio-economic status ( Hällsten, 2011 ). In summary, lifelong learning is crucial to adapt to the changing demands of the labor market, promote equality and improve individual and community well-being, a tool that can help enhance the acquisition of new skills and knowledge for adults in a flexible environment and that advances at great speed thanks to AI for its ability to generate flexible and adaptable environments for the learner.

Artificial intelligence

In the current era, characterized by rapid technological evolution and the growing need for continuous adaptation, artificial intelligence emerges as an invaluable resource that transforms and enriches the educational landscape, offering personalized and motivating solutions that enhance lifelong learning. AI plays a crucial role in adult and lifelong learning. Lifelong learning aims to emulate the capability of humans to continuously acquire knowledge and skills throughout their lives ( Chen and Liu, 2018 ). AI systems can support lifelong learning by providing personalized and adaptive learning experiences, allowing individuals to learn at their own pace and according to their specific needs ( Ally and Perris, 2022 ). AI can enhance learning efficiency and cognitive abilities, improving teaching and learning outcomes ( Huang et al., 2021 ). Additionally, AI can automate the construction of visual–linguistic knowledge, enabling continuous knowledge construction for lifelong learning ( Ha et al., 2015 ). The use of AI in education can transform learning into an ongoing, lifelong process ( Tang and Deng, 2022 ). AI supports ongoing initiatives to promote lifelong learning by providing tailored and adaptable experiences. Moreover, AI aids lifelong learning through automated assessment and progress tracking ( Sanabria-Z et al., 2023 ). Overall, AI has the potential to revolutionize adult and lifelong learning by providing personalized, adaptive, and continuous learning experiences.

Despite the growing importance of online adult education and the existence of effective design principles, relatively little attention has been paid to how to adapt these principles to adult learning, specifically those seeking to acquire new skills related to adapting to changing work environments. Massive open online courses (MOOCs) have triggered a sudden change in the educational scene. Its characteristics of being free, heterogeneous, multi-thematic, and fostering lifelong learning have completely changed the instructional design scene, allowing these innovations and new architectures of teaching and learning to be included ( Valenzuela et al., 2019 ). In this sense, Conget et al. (2021) point out that lifelong learning benefits both from feedback that elicits reflection on learning as well as the promotion of curiosity, motivation, perseverance and regulation of learning. Lifelong learning empowers individuals to have control over their own learning agenda and shape their own lives ( Eynon and Malmberg, 2021 ). As adult learners may differ significantly from younger learners, learning design based on andragogical principles and focused on the pragmatic and context-dependent needs of learners calls for consideration of incorporating frameworks on lifelong learning for learning design. Overall, lifelong learning is essential for personal development, societal progress, and economic prosperity.

Personalized learning

Personalized learning has become a key approach in contemporary education. In a world where universal approaches are no longer appropriate, personalized learning requires education to provide customized solutions to students according to their particular needs. This represents a significant shift from traditional teacher-centered models. However, the reality of education in schools, especially in developing countries, is far from being flexible, personalized, oriented to the development of soft skills, and based on the use of information and communication technologies ( Chiappe et al., 2020 ). The U.S. Office of Educational Technology defined personalized learning as “instruction tailored to the specific learning needs, preferences, and interests of diverse learners” ( Peters and Araya, 2011 ). In a personalized educational environment, learning objectives and content, as well as method and pace, may vary, so personalization encompasses differentiation and individualization. Personalization of learning can be based either on the cognitive characteristics or behavioral traits of learners but also on their learning style, level of knowledge or learning preferences ( Nguyen and Nguyen, 2023 ). Personalization of learning enables the improvement of both academic performance and the enhancement of student’s digital skills ( Yang and Wen, 2023 ). However, it is not without its challenges, mainly in terms of social skills development due to the lack of community learning environments, which can isolate students and prevent them from acquiring the skills needed in a work environment ( Pence, 2020 ). The personalization of learning represents an enormous advantage, not only in terms of improving the student’s academic performance and the development of digital skills, but also in terms of the needs of adult learning in work contexts with a focus on lifelong learning.

Notwithstanding the efforts made for the incorporation of personalization of learning in the educational system, it still presents challenges that need to be faced. It is necessary to expand the existing knowledge on the design of learning itineraries in terms of actors involved, personalization strategies, pattern language, structure and ways to evaluate the results of the implementation ( Buitrago et al., 2021 ). Personalized learning challenges include a lack of unified agreement on the components needed for a dynamic, personalized learning approach, which can provide unique and effective learning experiences. It should consider learner profiles, prior knowledge, adaptive learning paths, and flexible self-paced environments, with learning analytics generating dynamic environments ( Shemshack et al., 2021 ). Personalization is most successful when relevant learner characteristics are measured repeatedly during the learning process and used to adapt instruction in a systematic way ( Tetzlaff et al., 2021 ). A successful personalized learning system balances making the best recommendations based on current knowledge and exploring new learning trajectories that may pay off ( Tang et al., 2019 ). In summary, to delve into the design of learning pathways and overcome the challenges that the implementation of personalized learning represents, it is crucial to foster effective and adaptive educational experiences that cater to the diverse needs and preferences of learners.

In order to establish the basis for the exploration of artificial intelligence-mediated personalization of learning as a response to the growing need to establish a continuum of lifelong learning and professional development, a systematic literature review (SRL) was conducted. The SRL method allows identifying, analyzing and interpreting evidence related to the research objective in an unbiased and repeatable way ( García-Peñalvo, 2017 ) being a process that synthesizes research in a systematic, transparent and reproducible way in order to enrich knowledge and inform policy making and practice ( Tranfield et al., 2003 ). The process consisted of (1) the formulation of research questions, (2) the selection of databases and search terms or keywords for the preliminary mapping of articles published on the topic in question as part of the search process, (3) the selection of quality criteria for the inclusion and exclusion of articles to be reviewed, (4) the selection and extraction of data and, finally, (5) the synthesis of information that would allow answers to the research questions defined ( Kitchenham and Charters, 2007 ; Landa et al., 2011 ). The control of this process was carried out following the guidelines established by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement ( Page et al., 2021 ).

Research questions

The research questions were established in order to analyze published articles on artificial intelligence-mediated solutions for personalization of learning, published in the last five years. These seven research questions were designed to address three topics of interest:

1. Characteristics of the studies analyzed in the field of artificial intelligence and personalized learning.

2. Educational level and environment in which the research is carried out.

3. Solutions and technologies for AI-mediated personalization of learning.

The choice of research questions was based on the following criteria:

1. Relevance: the questions had to be relevant to the research topic, which is artificial intelligence applied to learning personalization.

2. Accuracy: The questions had to be precise and concise, to facilitate their understanding and response.

3. Feasibility: The questions had to be feasible to answer, taking into account the limitations of the research.

The research questions formulated are described in Table 1 .

Table 1 . Topics and research questions.

Search process

The search for articles was performed on February 26, 2024, in the Scopus and Web of Science (WoS) databases. The keywords chosen were: artificial intelligence and personalized learning, the search period: 2019 to 2024 and the document type: article, with the publication languages: English or Spanish, were the delimiters. The search strings are shown in Table 2 .

Table 2 . Search strings.

Inclusion and exclusion criteria

The Scopus and Web of Science (WoS) databases were used to search for articles. The search terms used were: Artificial intelligence, Personal learning, Personal training, and Learning path. For the elaboration of this review, the following categorization of criteria for the inclusion of information was carried out:

1. Thematic: Artificial intelligence and Personalized learning.

2. Spatial: It was decided not to establish a geographical restriction. Worldwide research is included only in English language.

3. Temporal: Papers published during the last five years are included, starting in 2019.

4. Type of document: Research articles.

5. As criteria for exclusion of information, it was established that documents lacking a theoretical or conceptual framework would be eliminated, as well as those that did not meet the previously established inclusion criteria.

Selection process and data extraction

The number of articles found in both databases (Scopus and WoS) was 139. Following quality criteria, four records corresponding to articles withdrawn from the publications were eliminated to proceed to a review of titles and abstracts in order to identify those articles that corresponded to the focus of interest of this publication in terms of type of document and relationship with the topic, leaving a total of 78 articles selected for the SRL, from which the following information was extracted: Title, Author, DOI, Abstract, Name of the publication, Number of citations and Country of the first author. This information was compiled in an Excel file available for consultation. Figure 1 shows the selection process of articles included in the SLR.

Figure 1 . PRISMA diagram.

Data extraction and synthesis

Before writing the narrative synthesis, the 78 selected publications were carefully read and summarized in the context of the research questions. Given the newness of the research in the field there was, to the authors’ knowledge, no definitive classification proposed for the type of artificial intelligence solutions used for learning personalization, so, to answer question RQ7 a classification of our own was created based on the classifications proposed by Hashim et al. (2022) and Bozkurt et al. (2021) which includes the categories: (1) Adaptive learning environments, (2) AI-aided LMS, (3) AI-Enabled Mobile Apps, (4) Content recommendation systems, (5) Generative language model, (6) Holistic integration, (7) Intelligent conversational agents and tutorials, (8) Learning analytics and personalized assessment, (9) Machine learning, (10) Smart classrooms/IoT, and (11) Virtual and augmented reality.

This section presents the results obtained from the meticulous and systematic analysis of the data collected. The articles under analysis are integrated in Supplementary Material , with an identification number, in order to identify them in some of the results.

RQ1. What is the geographical distribution of the authors of the articles analyzed?

In order to identify the regions of the world that are currently leading research on personalization of learning through artificial intelligence-assisted solutions, the geographical dispersion of the first authors of the articles reviewed was analyzed. Figure 2 shows that the highest concentration of authors is located in China outnumbering in a ratio of about 5:1 the next concentration located in the United States, followed by India and Germany. The areas with low scientific production on the subject are in Africa and Latin America.

Figure 2 . Geographical dispersion of authors.

The study of the geographic distribution of authors with interest in the subject allows us to identify the regions of the world where there is an area of opportunity for the development of research, especially if we consider that the personalization of learning requires adapting it to the characteristics of the student, which may be influenced by both culture and place of origin.

RQ2. In which journals have artificial intelligence and personalized learning items been published more, and what are the Q levels of the journals?

To understand which academic journals are leaders in the publication of articles related to artificial intelligence and personalized learning, we analyzed the total number of published articles as well as the year of publication and the quartile of classification of the journal. It was found that 37% of the published articles are grouped in 8 journals at the Q1 and Q2 levels: International Journal of Emerging Technologies in Learning (6), Applied Mathematics and Nonlinear Sciences (5), Sustainability (Switzerland)(4), IEEE Access (4). Education Sciences (4), Frontiers in Psychology (3), Frontiers in Education (3). The analysis by quality levels (Q levels) of the journals indicates that 73% of the articles reviewed were published in journals with Q1 and Q2 level ( Figure 3 ).

Figure 3 . Frequency of publication by Q level.

The identification of publications and their quality level allows authors to identify sources for the dissemination of their research results through clarity on the perceived quality of research on personalization of learning and artificial intelligence as well as informed decision making for the development of strategies to raise the overall standard of research on the topic.

RQ3. What keywords are most commonly used in the analyzed articles?

The identification and analysis of keyword co-occurrence in the 78 articles reviewed made it possible to detect and group the concepts that are related to the key terms of this research: personalized learning and artificial intelligence. Figure 4 allows identifying the relationship between the term “personalized learning” and the four groupings of words, indicated by color, among which can be grouped those referring to learning analytics as a way to evaluate learning effectiveness, deep learning algorithms, the different personalization solutions mediated by artificial intelligence among which “e-learning,” “machine learning” and “learning systems” stand out. It is worth noting the grouping corresponding to generative language models where ChatGPT occupies an important place despite the novelty of its appearance in practice.

Figure 4 . Keyword co-occurrence map.

The keyword co-occurrence analysis allows identifying predominant themes and areas of interest in the academic literature, as well as emerging trends and possible gaps in knowledge. The groupings in terms of artificial intelligence-mediated solutions for learning personalization reflect the main trends in educational practice and confirm the classification proposed for the development of this research.

RQ4. What are the trends in research methods observed in the articles?

The analysis of trends in research methods and design allows inferring the preferred methodological approaches for research on learning personalization and artificial intelligence. The classification of articles was done in terms of quantitative methods (experimental design, quasi-experimental, applied experimental), qualitative methods (case study, conceptual design, exploratory, descriptive, grounded theory, theoretical research) and mixed methods (bibliometric analysis, case study, experimental, and systematic literature review) ( Bauer, 2000 ; Valenzuela and Flores, 2013 ). The review of research methods and designs results in a concentration of more than 50% of the articles reviewed whose research was conducted under a quantitative research method in an experimental research design. It should be noted that among the articles with the highest number of citations are studies conducted under a qualitative approach: A-131 with 64 citations on business models for the application of learning analytics and artificial intelligence for the development of learning solutions ( Renz and Hilbig, 2020 ), A-138 with 47 citations that explores whether artificial intelligence-mediated solutions can be applied in an enterprise learning environment for talent development ( Maity, 2019 ) A-132 with a state-of-the-art review on personalization of learning and exposing gaps in creating and maintaining motivation for learning, a focus on diversity, and eliminating data-and algorithm-induced biases ( Maghsudi et al., 2021 ), and A-056 on the advantages of using ChatGPT in the educational context, with 29 citations each ( Sallam et al., 2023 ). The results of this review are detailed in Figure 5 .

Figure 5 . Research methods and design.

The study of research methods and designs applied to the topics of interest is useful to determine their state of maturity since a tendency towards experimental and exploratory approaches denotes novelty in the topic and the existence of important gaps and areas of opportunity and convergence for future research.

RQ5. At what educational levels is the personalization of learning mediated by artificial intelligence being developed?

RQ6. In what environments is the research and development of initiatives on personalization of learning mediated by artificial intelligence taking place?

RQ7. What kind of solutions or technologies are being prioritized in the development of AI-mediated personalization of learning?

In order to identify the educational contexts and the kind of solutions towards which the research on personalized learning and artificial intelligence is directed, the classification of articles was made under three headings: Educational (encompasses primary education, secondary education and higher education), Industry (refers to the application in the workplace and/or in organizations) and Informal Education (that available outside the scope of formal education), finding that more than 80% of the research is conducted in the educational context with a prevalence of 86% in higher education, while only 11.5% of the articles reviewed have a focus on learning within the work context and 6.5% in the context of informal education. Within this context, the study of artificial intelligence under a holistic approach stands out (44%) and only two of the articles reviewed, whose first authors are located on the Asian continent, focus on a specific solution. In A-050, the authors point out the imperative need to establish large-scale rapid retraining systems for the workforce, anticipating that smart and virtual workplaces will replace traditional offices, and thus an artificial intelligence-based framework for rapid retraining of job skills is presented ( Ashrafi et al., 2023 ). In A-113, the authors propose a Blended Learning model for the assignment of learning paths based on the evaluation of knowledge acquisition with a focus on higher education applied in work contexts for the development of lifelong learning ( Bekmanova et al., 2021 ). The results of this analysis are shown in Figure 6 .

Figure 6 . Trends and context of AI-measured solutions for learning personalization.

In the educational context, the study of solutions focused on Adaptive Learning (11) predominates, followed closely by Generative Language Models (9): A-002, A-005, A-010, A-015, A-023, A-045, A-056, A-057, A-093 and A-040.

The analysis of the educational levels in which the development of solutions for the personalization of learning is studied allows identifying areas of opportunity in the expansion towards contexts where the solutions for the personalization of learning are applicable in the format of continuing education or lifelong learning for the development of work competencies as well as the development of Adaptive Learning solutions taking into account the characteristics of the adult population as well as the use of Generative Language Models for the integration of training programs for adults.

After analyzing 78 articles published in the Scopus and Web of Science databases between 2019 and 2024, the main findings and recommendations for future research are presented.

The study of personalization of learning through mediated solutions is not yet widespread as research is concentrated in a small number of countries. Figure 2 shows the geographical concentration of authors on the topic finding that the largest production comes from China, followed by far by the United States and India. The above coincides with the findings of other research ( Nguyen and Nguyen, 2023 ) and allows highlighting the need not only for further research on the subject but also for its geographical dispersion, since the risks exposed by Bulathwela et al. (2024) and Wang et al. (2023) point out the lack of democratization in the personalization of learning due to the existence of gaps in access, which will disadvantage students in countries lagging behind in the application and implementation of these solutions. The dissemination of the relevance of the topic is important to motivate research throughout the world.

Regarding the relevance of research on the topic, it is clear that top-tier academic publications are aware of the importance of the application of AI in personalizing learning. Figure 3 allows us to observe a significant concentration of publications in Q1 and Q2level publications. The finding coincides with that reported by Del Campo et al. (2023) who report a remarkable increase in the scientific literature on the subject in the last decade, focusing on the use of disruptive technologies in education especially in high impact publications. It is expected that this importance will peer in the educational environment for a greater scientific production on the research topic.

Although the novelty regarding the incorporation of generative language models has put the focus on the advantages of their adaptation for the personalization of learning, their adoption is not the only way to achieve the acquisition of learning and the development of digital skills. Figure 4 , through the correlation of terms around personalized learning allows identifying the importance of the development of these in a learning platform environment. The result is consistent with that pointed out by Hamal et al. (2022) and Valenzuela et al. (2019) . The new technologies, in terms of personalization of learning mediated by AI through solutions such as mobile learning, educational games, collaborative learning in social networks, MOOCs or the application of augmented reality, as well as the evaluation and feedback on them ( Ifelebuegu, 2023 ). The variety of options in terms of learning personalization demands a holistic approach to evaluate the effectiveness of different solutions.

Much of the research around AI and its different applications is still novel. Figure 5 shows a significant concentration of research still in its experimental and theoretical design stage. In their research Chiappe et al. (2020) point out that, although these concepts are not new, personal learning paths, research-based teaching, open, flexible and digitally supported curricula and lifelong learning, awaken a renewed interest by educational researchers and new developments around this area of study. It is inferred that, as this line of research acquires greater maturity, there will be more research on the evaluation of the effectiveness of its applications.

Finally, the existence of a wide window of opportunity for the development of personalized learning applications in informal education environments and work contexts where the need for lifelong learning dynamics is imperative is highlighted. Figure 6 shows the development trends and context in which AI-mediated solutions for the personalization of learning are developed where an incipient development is observed in informal education and work contexts. The design of these solutions must obey a correct pedagogical design ( Pence, 2020 ) and be oriented to the needs of users at different educational levels as a means of preparation for accessing job opportunities ( Sanabria-Z et al., 2023 ). In a world of constant change and evolution, individuals require learning solutions tailored to their interests, goals and preferences that allow them to remain relevant in the workplace.

Research on personalization of learning and the use of AI in lifelong learning emerges as a vital field in the current era of constant change in response to the need to adapt by developing the practice of continuous and adaptive lifelong learning. In this sense, the integration of AI solutions in education offers transformative potential to create personalized and effective learning experiences that adapt to individual and contextual needs. From the application of AI chatbots to generative language models, AI offers a range of innovative tools that revolutionize the concept of personalized learning.

However, it is crucial to address the challenges and risks associated with the use of AI in education. The concentration of research development in a few countries can contribute to algorithmic bias and the digital divide, highlighting the need for a careful and ethical approach to the implementation of these technologies. Furthermore, it is critical to recognize that IA is not a one-size-fits-all solution to all educational challenges but must be complemented by sound pedagogical design and attention to the specific needs of learners in different educational contexts and levels.

This study highlights the importance of continuing to research and develop IL solutions for the personalization of learning, especially in areas such as informal education and the workplace. The identification of trends, areas of opportunity and ethical challenges provides a solid foundation for future research and educational practices. Ultimately, the goal is to promote equitable and democratized access to personalized learning opportunities, thus driving innovation and progress in education towards lifelong learning.

This study is not exhaustive as it only analyzed publications found in two databases, which have the widest coverage but are not the only ones where relevant research on the topic can be found. The research method used (SLR) and its findings provide a comprehensive overview of the existing literature and highlight key areas in the use of IL to enhance personalized learning in the context of lifelong learning. The results of this research contribute to the advancement of the use of IA to enhance personalization of learning as one of the pillars of lifelong learning for innovation in education. Future lines of research are proposed among which are the determination of the factors that influence the effectiveness of personalization of learning as well as the ethical implications of this development to ensure equity and non-discrimination in access to these solutions in order to promote the democratization of learning.

Author contributions

KB-C: Writing – original draft, Writing – review & editing. M-SR-M: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – review & editing. AM-A: Supervision, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The authors would like to thank the financial support from Tecnologico de Monterrey through the “Challenge-Based Research Funding Program 2022.” Project ID # I003 – IFE001 – C2-T3 – T. Also, academic support from Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, México.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2024.1424386/full#supplementary-material

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Keywords: personalized learning paths, lifelong learning, artificial intelligence, educational innovation, higher education

Citation: Bayly-Castaneda K, Ramirez-Montoya M-S and Morita-Alexander A (2024) Crafting personalized learning paths with AI for lifelong learning: a systematic literature review. Front. Educ . 9:1424386. doi: 10.3389/feduc.2024.1424386

Received: 28 April 2024; Accepted: 30 July 2024; Published: 08 August 2024.

Reviewed by:

Copyright © 2024 Bayly-Castaneda, Ramirez-Montoya and Morita-Alexander. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: K. Bayly-Castaneda, [email protected] ; M-S. Ramirez-Montoya, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Master the art of how to write an abstract for a literature review with this informative guide. Start creating standout abstracts today!

You probably already read lots of journal article abstracts while conducting your literature review —try using them as a framework for structure and style. You can also find lots of dissertation abstract examples in thesis and dissertation databases.

An APA abstract is a 150-250 word summary of your paper. Learn how to write and format it with an easy example! (APA 6th & 7th edition)

A literature review is a survey of scholarly knowledge on a topic. Our guide with examples, video, and templates can help you write yours.

A literature review abstract serves as a concise summary of the purpose or aim of your research. This abstract provides an overview of your research questions, problems, or hypotheses, research methods, study results, conclusions, recommendations, and implications. Literature review abstracts in APA style are common in scholarly journals ...

Abstract Content The abstract addresses the following (usually 1-2 sentences per topic): key aspects of the literature review problem under investigation or research question(s) clearly stated hypothesis or hypotheses methods used (including brief descriptions of the study design, sample, and sample size)

Writing a literature review requires a range of skills to gather, sort, evaluate and summarise peer-reviewed published data into a relevant and informative unbiased narrative. Digital access to research papers, academic texts, review articles, reference databases and public data sets are all sources of information that are available to enrich ...

An abstract is a short summary of an article, essay or research findings. A well-written abstract will provide the reader with a brief overview of the entire article, including the article's purpose, methodology and conclusion. An abstract should give the reader enough detail to determine if the information in the article meets their research needs...and it should make them want to read more!

This guide provides guidance, tips, and examples about different types of academic writing like literature reviews, annotated bibliographies, and abstract writing.

An abstract for a literature review or meta-analysis should describe: (1) the problem or relations under investigation (2) study eligibility criteria (3) types of participants (4) main results, including the most important effect sizes, and any important moderators of these effect sizes (5) conclusions, including limitations (6) implications ...

Authors abstract various longer works, including book proposals, dissertations, and online journal articles. There are two main types of abstracts: descriptive and informative. A descriptive abstract briefly describes the longer work, while an informative abstract presents all the main arguments and important results.

Reviewing the literature requires the ability to juggle multiple tasks, from finding and evaluating relevant material to synthesising information from various sources, from critical thinking to paraphrasing, evaluating, and citation skills [7]. In this contribution, I share ten simple rules I learned working on about 25 literature reviews as a PhD and postdoctoral student. Ideas and insights ...

Objectives This article provides practical guidance on developing a comprehensible abstract, including those required for funding applications, conferences, and publication. In addition, we discuss and demonstrate the practicalities of editing and revising an abstract for conference or peer review and identify emerging formats that may be more relevant to nurses and researchers.

This guide will provide research and writing tips to help students complete a literature review assignment.

Although a literature review may summarize research on a given topic, it generally synthesizes and summarizes a subject. The purpose of a literature review therefore is to present summaries and analysis of current research not contribute new ideas on the topic (making it different from a research paper).

A guide to writing abstracts, annotated bibliographies, and literature reviews

The abstract should summarize the key methods, results and conclusions of the review and should not contain any information that is not in the review. Links to other parts of the review (such as references, studies, tables and figures) may not be included in the abstract. A hypothetical example of an abstract is included in Box 11.8.a.

Need to know what an abstract is and how to write one? This comprehensive guide to abstracts gives fifteen examples and the rules to follow.

Now that you know what the Literature Review comprises, let's come back tohow to write an abstract for literature review. The flow is the same as your research paper; initiate with theintroductionand talk about the problem or situation being studied, follow it with a description of the research methodsbrought in to implementation during the ...

Informative abstract: Details the background information, key points, research methods, and significant findings. There may also be further reading recommendations so that the reader can understand the main elements of the paper better. Descriptive abstract: Provides an overview of the content, including major points and research methods.

Breast cancer is the most common malignant tumor in cisgender women and the second leading cause of cancer mortality. 6 However, breast cancer risk in specific subpopulations, such as transgender people, is not yet fully characterized. Some evidence suggests an increased breast cancer risk in transgender men compared to their cisgender counterpart, while having a lower risk than cisgender ...

To our knowledge, this is the first review of automated data extraction methods or tools for health-related grey literature and soft data, with a focus on (semi)automating horizon scans, health technology assessments (HTA), evidence maps, or other literature reviews. We searched six databases to cover both health- and computer-science literature.

Section "Literature review" focuses on the literature background of biomimicry, ... Publications were identified using the following terms in the title and abstract: ...

To achieve this, a systematic literature review (SRL) of 78 articles published between 2019 and 2024 from the Scopus and Web or Science databases was conducted, answering seven questions grouped into three themes: characteristics of the published research, context of the research, and type of solution analyzed. ... Title, Author, DOI, Abstract ...

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