trends in science education research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• CAREER FEATURE
• 08 April 2024

Ready or not, AI is coming to science education — and students have opinions

• Sarah Wells 0

Sarah Wells is an independent science journalist based in Washington DC.

You can also search for this author in PubMed   Google Scholar

You have full access to this article via your institution.

Leo Wu, an economics student at Minerva University in San Francisco, California, founded a group to discuss how AI tools can help in education. Credit: AI Consensus

The world had never heard of ChatGPT when Johnny Chang started his undergraduate programme in computer engineering at the University of Illinois Urbana–Champaign in 2018. All that the public knew then about assistive artificial intelligence (AI) was that the technology powered joke-telling smart speakers or the somewhat fitful smartphone assistants.

But, by his final year in 2023, Chang says, it became impossible to walk through campus without catching glimpses of generative AI chatbots lighting up classmates’ screens.

“I was studying for my classes and exams and as I was walking around the library, I noticed that a lot of students were using ChatGPT,” says Chang, who is now a master’s student at Stanford University in California. He studies computer science and AI, and is a student leader in the discussion of AI’s role in education. “They were using it everywhere.”

‘Without these tools, I’d be lost’: how generative AI aids in accessibility

ChatGPT is one example of the large language model (LLM) tools that have exploded in popularity over the past two years. These tools work by taking user inputs in the form of written prompts or questions and generating human-like responses using the Internet as their catalogue of knowledge. As such, generative AI produces new data based on the information it has already seen.

However, these newly generated data — from works of art to university papers — often lack accuracy and creative integrity, ringing alarm bells for educators. Across academia, universities have been quick to place bans on AI tools in classrooms to combat what some fear could be an onslaught of plagiarism and misinformation. But others caution against such knee-jerk reactions.

Victor Lee, who leads Stanford University’s Data Interactions & STEM Teaching and Learning Lab, says that data suggest that levels of cheating in secondary schools did not increase with the roll-out of ChatGPT and other AI tools. He says that part of the problem facing educators is the fast-paced changes brought on by AI. These changes might seem daunting, but they’re not without benefit.

Educators must rethink the model of written assignments “painstakingly produced” by students using “static information”, says Lee. “This means many of our practices in teaching will need to change — but there are so many developments that it is hard to keep track of the state of the art.”

Despite these challenges, Chang and other student leaders think that blanket AI bans are depriving students of a potentially revolutionary educational tool. “In talking to lecturers, I noticed that there’s a gap between what educators think students do with ChatGPT and what students actually do,” Chang says. For example, rather than asking AI to write their final papers, students might use AI tools to make flashcards based on a video lecture. “There were a lot of discussions happening [on campus], but always without the students.”

Computer-science master’s student Johnny Chang started a conference to bring educators and students together to discuss the responsible use of AI. Credit: Howie Liu

To help bridge this communications gap, Chang founded the AI x Education conference in 2023 to bring together secondary and university students and educators to have candid discussions about the future of AI in learning. The virtual conference included 60 speakers and more than 5,000 registrants. This is one of several efforts set up and led by students to ensure that they have a part in determining what responsible AI will look like at universities.

Over the past year, at events in the United States, India and Thailand, students have spoken up to share their perspectives on the future of AI tools in education. Although many students see benefits, they also worry about how AI could damage higher education.

Enhancing education

Leo Wu, an undergraduate student studying economics at Minerva University in San Francisco, California, co-founded a student group called AI Consensus . Wu and his colleagues brought together students and educators in Hyderabad, India, and in San Francisco for discussion groups and hackathons to collect real-world examples of how AI can assist learning.

From these discussions, students agreed that AI could be used to disrupt the existing learning model to make it more accessible for students with different learning styles or who face language barriers. For example, Wu says that students shared stories about using multiple AI tools to summarize a lecture or a research paper and then turn the content into a video or a collection of images. Others used AI to transform data points collected in a laboratory class into an intuitive visualization.

Three ways ChatGPT helps me in my academic writing

For people studying in a second language, Wu says that “the language barrier [can] prevent students from communicating ideas to the fullest”. Using AI to translate these students’ original ideas or rough drafts crafted in their first language into an essay in English could be one solution to this problem, he says. Wu acknowledges that this practice could easily become problematic if students relied on AI to generate ideas, and the AI returned inaccurate translations or wrote the paper altogether.

Jomchai Chongthanakorn and Warisa Kongsantinart, undergraduate students at Mahidol University in Salaya, Thailand, presented their perspectives at the UNESCO Round Table on Generative AI and Education in Asia–Pacific last November. They point out that AI can have a role as a custom tutor to provide instant feedback for students.

“Instant feedback promotes iterative learning by enabling students to recognize and promptly correct errors, improving their comprehension and performance,” wrote Chongthanakorn and Kongsantinart in an e-mail to Nature . “Furthermore, real-time AI algorithms monitor students’ progress, pinpointing areas for development and suggesting pertinent course materials in response.”

Although private tutors could provide the same learning support, some AI tools offer a free alternative, potentially levelling the playing field for students with low incomes.

Jomchai Chongthanakorn gave his thoughts on AI at a UNESCO round table in Bangkok. Credit: UNESCO/Jessy & Thanaporn

Despite the possible benefits, students also express wariness about how using AI could negatively affect their education and research. ChatGPT is notorious for ‘hallucinating’ — producing incorrect information but confidently asserting it as fact. At Carnegie Mellon University in Pittsburgh, Pennsylvania, physicist Rupert Croft led a workshop on responsible AI alongside physics graduate students Patrick Shaw and Yesukhei Jagvaral to discuss the role of AI in the natural sciences.

“In science, we try to come up with things that are testable — and to test things, you need to be able to reproduce them,” Croft says. But, he explains, it’s difficult to know whether things are reproducible with AI because the software operations are often a black box. “If you asked [ChatGPT] something three times, you will get three different answers because there’s an element of randomness.”

And because AI systems are prone to hallucinations and can give answers only on the basis of data they have already seen, truly new information, such as research that has not yet been published, is often beyond their grasp.

‘Obviously ChatGPT’ — how reviewers accused me of scientific fraud

Croft agrees that AI can assist researchers, for example, by helping astronomers to find planetary research targets in a vast array of data. But he stresses the need for critical thinking when using the tools. To use AI responsibly, Croft argued in the workshop, researchers must understand the reasoning that led to an AI’s conclusion. To take a tool’s answer simply on its word alone would be irresponsible.

“We’re already working at the edge of what we understand” in scientific enquiry, Shaw says. “Then you’re trying to learn something about this thing that we barely understand using a tool we barely understand.”

These lessons also apply to undergraduate science education, but Shaw says that he’s yet to see AI play a large part in the courses he teaches. At the end of the day, he says, AI tools such as ChatGPT “are language models — they’re really pretty terrible at quantitative reasoning”.

Shaw says it’s obvious when students have used an AI on their physics problems, because they are more likely to have either incorrect solutions or inconsistent logic throughout. But as AI tools improve, those tells could become harder to detect.

Chongthanakorn and Kongsantinart say that one of the biggest lessons they took away from the UNESCO round table was that AI is a “double-edged sword”. Although it might help with some aspects of learning, they say, students should be wary of over-reliance on the technology, which could reduce human interaction and opportunities for learning and growth.

“In our opinion, AI has a lot of potential to help students learn, and can improve the student learning curve,” Chongthanakorn and Kongsantinart wrote in their e-mail. But “this technology should be used only to assist instructors or as a secondary tool”, and not as the main method of teaching, they say.

Equal access

Tamara Paris is a master’s student at McGill University in Montreal, Canada, studying ethics in AI and robotics. She says that students should also carefully consider the privacy issues and inequities created by AI tools.

Some academics avoid using certain AI systems owing to privacy concerns about whether AI companies will misuse or sell user data, she says. Paris notes that widespread use of AI could create “unjust disparities” between students if knowledge or access to these tools isn’t equal.

Tamara Paris says not all students have equal access to AI tools. Credit: McCall Macbain Scholarship at McGill

“Some students are very aware that AIs exist, and others are not,” Paris says. “Some students can afford to pay for subscriptions to AIs, and others cannot.”

One way to address these concerns, says Chang, is to teach students and educators about the flaws of AI and its responsible use as early as possible. “Students are already accessing these tools through [integrated apps] like Snapchat” at school, Chang says.

In addition to learning about hallucinations and inaccuracies, students should also be taught how AI can perpetuate the biases already found in our society, such as discriminating against people from under-represented groups, Chang says. These issues are exacerbated by the black-box nature of AI — often, even the engineers who built these tools don’t know exactly how an AI makes its decisions.

Beyond AI literacy, Lee says that proactive, clear guidelines for AI use will be key. At some universities, academics are carving out these boundaries themselves, with some banning the use of AI tools for certain classes and others asking students to engage with AI for assignments. Scientific journals are also implementing guidelines for AI use when writing papers and peer reviews that range from outright bans to emphasizing transparent use .

Lee says that instructors should clearly communicate to students when AI can and cannot be used for assignments and, importantly, signal the reasons behind those decisions. “We also need students to uphold honesty and disclosure — for some assignments, I am completely fine with students using AI support, but I expect them to disclose it and be clear how it was used.”

For instance, Lee says he’s OK with students using AI in courses such as digital fabrication — AI-generated images are used for laser-cutting assignments — or in learning-theory courses that explore AI’s risks and benefits.

For now, the application of AI in education is a constantly moving target, and the best practices for its use will be as varied and nuanced as the subjects it is applied to. The inclusion of student voices will be crucial to help those in higher education work out where those boundaries should be and to ensure the equitable and beneficial use of AI tools. After all, they aren’t going away.

“It is impossible to completely ban the use of AIs in the academic environment,” Paris says. “Rather than prohibiting them, it is more important to rethink courses around AIs.”

Nature 628 , 459-461 (2024)

doi: https://doi.org/10.1038/d41586-024-01002-x

Related Articles

• Machine learning
• Scientific community

How I harnessed media engagement to supercharge my research career

Career Column 09 APR 24

How we landed job interviews for professorships straight out of our PhD programmes

Career Column 08 APR 24

After the genocide: what scientists are learning from Rwanda

News Feature 05 APR 24

How can we make PhD training fit for the modern world? Broaden its philosophical foundations

Correspondence 02 APR 24

The neuroscientist formerly known as Prince’s audio engineer

Career Feature 14 MAR 24

Is ChatGPT corrupting peer review? Telltale words hint at AI use

News 10 APR 24

How to break big tech’s stranglehold on AI in academia

Correspondence 09 APR 24

AI can help to tailor drugs for Africa — but Africans should lead the way

Comment 09 APR 24

Junior Group Leader Position at IMBA - Institute of Molecular Biotechnology

The Institute of Molecular Biotechnology (IMBA) is one of Europe’s leading institutes for basic research in the life sciences. IMBA is located on t...

Austria (AT)

IMBA - Institute of Molecular Biotechnology

Open Rank Faculty, Center for Public Health Genomics

Center for Public Health Genomics & UVA Comprehensive Cancer Center seek 2 tenure-track faculty members in Cancer Precision Medicine/Precision Health.

Charlottesville, Virginia

Center for Public Health Genomics at the University of Virginia

Husbandry Technician I

Memphis, Tennessee

St. Jude Children's Research Hospital (St. Jude)

Lead Researcher – Department of Bone Marrow Transplantation & Cellular Therapy

Researcher in the center for in vivo imaging and therapy.

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

UNDERSTANDING RESEARCH PARADIGMS: TRENDS IN SCIENCE EDUCATION RESEARCH

This essay offers several insights regarding the principles of qualitative and quantitative methods, defining how they shape the empirical process as well as knowledge acquisition in social science research. A comprehensive discussion includes comparing the assumptions and techniques of each paradigm, as well as a description of their respective strengths and weaknesses in research. These paradigms are examined in terms of past trends in science education research, indicating that over the last several decades a shift in approach from the quantitative to qualitative has occurred. The central thesis of the essay contends that methodological decisions should be based in pragmatism, rather than a pre-existent set of philosophies or beliefs irrespective of context. Implications for research are discussed in terms of the findings of several science education content analysis studies, conveying that research methods often coincide with the collective interest of the masses, policy, educational reform or program developments. Key words: paradigm decisions, qualitative research, quantitative research, science education, trends.

• Related Documents

Affective economy of national-populist images: Investigating national and transnational online networks through visual big data

In our article, we investigate the affective economy of national-populist image circulation on Facebook. This is highly relevant, since social media has been an essential area for the spread of national-populist ideology. In our research, we analyse image circulation as affective practice, combining qualitative and quantitative methods. We use computational data analysis methods to examine visual big data: image fingerprints and reverse image search engines to track down the routes of thousands of circulated images as well as make discourse-historical analysis on the images that have gained most attention among supporters. Our research demonstrates that these existing tools allow social science research to make theory-solid approaches to understand the role of image circulation in creating and sustaining national and transnational networks on social media, and show how national-populist thinking is spread through images that catalyse and mobilise affects – fear, anger and resentment – thus creating an effective affective economy.

Evolution of Statistical Software and Quantitative Methods

Statistical software is the enabling tool of quantitative research and the availability and use of the software can greatly shape which methods are used by researchers. Software that is more accessible is likely to have more users and the methods implemented within the software limits the methods accessible to researchers. Open source software, (e.g. R), has reduced these barriers by making cutting edge statistical methods available to researchers through add-on packages. This manuscript explores the evolution of statistical software within social science research using a research synthesis to establish the state of affairs. Software and statistical analysis keywords were searched in published manuscripts from high impact journals in five disciplines, Economics, Education, Political Science, Public Policy, and Sociology. Analysis was based on research synthesis methods. Implications for open science and reproducibility are discussed.

Students as Subjects and Scholars: Qualquant Tools in the Classroom

My experience attending two NSF Short Courses on Research Methods in Cultural Anthropology prompted me to use free list and pile sorting activities as teaching exercises with interesting and informative results that could be useful for others grappling with teaching research methods to undergraduates. My immediate goal in attending the course was inform my teaching of anthropological research methods. However, I also gained a new pedagogical tool that I have implemented in a wide range of classes to help students experience and understand the various qualitative and quantitative methods undertaken in social science research, while also redirecting their role as passive students to active scholars. The following paper outlines the implementation of this Museum Studies' free list and pile sorting exercises, considers the resultant data and impact on students in their own words, and provides some caveats for future implementation.

A Tale of Two Cultures

Some in the social sciences argue that the same logic applies to both qualitative and quantitative research methods. This book demonstrates that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. The book identifies and discusses major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, the book also seeks to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. The book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.

Contributions from Science Education Research

Review and use of learning theories within computer science education research, community design for connected communities of practice in computer science education research, comment: what constitutes evidence in science education research, (re)considering foucault for science education research: considerations of truth, power and governance, where is computer science education research happening, export citation format, share document.

• Open access
• Published: 16 April 2015

Research trends on argumentation in science education: a journal content analysis from 1998–2014

• Sibel Erduran 1 ,
• Yasemin Ozdem 2 &
• Jee-Young Park 3  

International Journal of STEM Education volume  2 , Article number:  5 ( 2015 ) Cite this article

17k Accesses

88 Citations

23 Altmetric

Metrics details

The primary objective of this paper is to provide a review of research on argumentation in science education based on publications from 1998 to 2014 in three science education journals. In recent years, the teaching and learning argumentation (i.e. the coordination of evidence and theory to support or refute an explanatory conclusion, model or prediction) has emerged as a significant educational goal. Argumentation is a critically important discourse process in science and it should be taught and learned in the science classroom as part of scientific inquiry and literacy. Argumentation stresses the evidence-based justification of knowledge claims, and it underpins reasoning across STEM domains. Our aim in this study was to investigate how argumentation has been positioned within the publications of three top academic journals: Science Education , International Journal of Science Education , and Journal of Research in Science Teaching . A methodology for content analysis of the journals is described using quantitative and qualitative techniques.

One of the contributions of our analysis is the illustration that researchers studying argumentation from a linguistic perspective have been emphasizing related concepts in different ways. While the emphasis has been on discourse and discussion across all journals, the related concepts of talk, conversation, dialogue and negotiation were observed to a lesser extent. Likewise, the fine-level analysis of the key epistemic concepts such as reasoning, evidence and inquiry indicates variation in coverage.

Conclusions

The findings can provide evidence-based indicators for where more emphasis needs to be placed in future research on argumentation, and in particular they can provide guidelines for journals in soliciting articles that target underemphasized aspects of argumentation in science education.

The primary objective of this paper is to provide a review of argumentation studies in science education in manuscripts published from 1998 to 2014 in key science education research journals. In recent years, the teaching and learning argumentation (i.e. the coordination of evidence and theory to support or refute an explanatory conclusion, model or prediction) has emerged as a significant educational goal. Argumentation is a critically important discourse process in science and it should be taught and learned in the science classroom as part of scientific inquiry and literacy (Erduran & Jimenez-Aleixandre 2012 ; Erduran & Jimenez-Aleixandre 2007 ; Jimenez-Aleixandre et al. 2000 ; Kelly & Takao 2002 ; Zohar & Nemet 2002 ). Argumentation stresses the evidence-based justification of knowledge claims, and it underpins reasoning across STEM domains. Our aim in this study was to investigate how argumentation has been positioned within the publications of top academic journals: Science Education (SE), International Journal of Science Education (IJSE) and Journal of Research in Science Teaching (JRST). Our selection of these journals is consistent with other recent studies that have concentrated on journal content analysis in science education (e.g. Chang et al. 2010 ; Lee et al. 2009 ).

Content analysis of academic journals is an important aspect of educational research (Bowen 1992 ; Chang et al. 2010 ; Henson 2001 ). There are high-impact journals such as the Review of Educational Research ranked first in the Thompson Reuters Citation Reports that are dedicated to the analysis of research literature. Content analysis of journals provides researchers with insight into recent and emerging trends of key themes in the literature (e.g. Chang et al. 2010 ; Lee et al. 2009 ; Lin et al. 2014 ). Another significant aspect of journal content analysis is that it can provide evidence-based indicators for where more emphasis needs to be placed in research in order to understand how to improve the educational sector (Foreman-Peck & Winch 2010 ). In short, content analysis of journals can be useful in conceptualizing recent trends (e.g. Lee et al. 2009 ), forging new levels of interpretation of the literature (e.g. Anderson et al. 2006 ) and providing synthesis of ideas (e.g. Slavin et al. 2009 ).

Our focus in this review was on argumentation in science education. Argumentation was identified as an area of research in science education that has gained significant attention in recent years (Lee et al. 2009 ). Attention given to argumentation is apparent in the recent review by Lin et al. ( 2014 ) showing that the top 10 highly cited papers in 1998–2002 included papers on argumentation. The review also illustrated that a handful of the top 10 highly cited papers in 2003–2007 were concerned with argumentation, including those with a focus on informal reasoning (Lin et al. 2014 ). It was also reported that argumentation is in the list of the top 10 highly cited papers in 2008–2012, along with inquiry and scientific modelling. These review data support the claim that the argumentation was a significant topic of investigation and has received enduring attention from science educators for over a decade (Lee et al. 2009 ; Lin et al. 2014 ). Despite the increasing interest in argumentation in science education research, the precise nature of the trends in its coverage has not been previously documented in detail. Therefore, this study aimed to contribute to the understanding of the trends in the research literature through a content analysis of some key journals in the field.

Lin et al. ( 2014 ) indicated that in the past 15 years, argumentation, including informal reasoning, has been studied mostly in the context of various socio-scientific issues, suggesting that these three research topics were widely considered to be closely interrelated by science educators. Similarly, within science education, the notions of ‘epistemic practices’, and ‘discourse’ have been intricately linked to argumentation studies (Erduran & Jimenez-Aleixandre 2007 ).

On the other hand, Buty and Plantin ( 2008 ) point out that the established community working on argumentation studies does not tend to take into account the contributions of science education. Evidence for this lack of attention can be found in reference books, in the scarce presence of science education-related papers in journals such as Argumentation . In this paper, therefore, we focus on the argumentation studies in top science education journals in order to contribute to the understanding of the development of argumentation theory in science education in relation to their foundational grounding particularly in relation to the epistemic and linguistic aspects.

Theoretical framework

Argumentation can be described as a kind of discourse through which knowledge claims are individually and collaboratively constructed and evaluated in the light of empirical or theoretical evidence (Erduran & Jimenez-Aleixandre 2007 ). As a relatively unfamiliar strategy, argumentation needs to be appropriated by children and explicitly taught through suitable instruction, task structuring and modelling (e.g. Mason 1996 ). The teaching and learning of argumentation are based on premises that are consistent with the wider literature in science education, namely in framing science learning in terms of the appropriation of community practices that provide the structure, motivation and modes of communication required to sustain scientific discourse (Kelly & Chen 1999 ; Lemke 1990 ). From this perspective, argumentation is a significant tool that is instrumental in the growth of scientific knowledge (Kitcher 1988 ) as well as a vital component of scientific discourse (Pera 1994 ). The implication is that argumentation plays a central role in the building of explanations, models and theories (Siegel 1989 ) as scientists use arguments to relate the evidence they select to the claims they reach through use of warrants and backings (Toulmin 1958 ).

International curriculum and policy documents have been advocating the incorporation of argumentation in science education. Within Europe, the distinctive feature of argumentation is that it is framed in the development of the scientific competence. Jiménez-Aleixandre and Federico-Agraso ( 2009 ) illustrate this point through a discussion of the European Union recommendation of eight key competences (European Union 2006 ). In other parts of the world, for instance in the USA, argumentation is framed in the context of scientific practices (Berland & Reiser 2009 ). The recent development of the Next Generation Science Education Standards following on from the National Research Council’s recommendations (National Research Council 2012 ) is testimony to the articulation of argumentation as a significant component of scientific practices.

There are at least three theoretical bodies of research framing argumentation studies: (a) developmental psychology, including the distributed cognition perspective; (b) language sciences, for instance the theory of communicative action; and (c) science studies, for instance, drawing on history, philosophy and sociology of science. As Erduran & Jimenez-Aleixandre ( 2007 ) argued, rather than being a one-way relationship, argumentation studies and science education have the potential to inform these perspectives, leading to fruitful interactions. Likewise, we contend that within science education, the study of how argumentation studies have been informed by foundational perspectives is important in setting the scene for potential reciprocal interdisciplinary investigations of argumentation (Erduran & Jimenez-Aleixandre 2007 ) with contributions of science education research to other fields. For example, (a) the discussions about to what extent argumentation research in science education contributes to cognitive and metacognitive processes would inform the situated cognition perspective (Brown & Campione 1990 ); (b) the development of communicative competences and particularly critical thinking by means of argumentative science education would add to the theory of communicative action; (Habermas 1981 ); and (c) understanding the development of reasoning through argumentation in science education could extend our knowledge about teaching and learning philosophy of science (Giere 1988 ) as well as developmental psychology (Kuhn & Crowell 2011 ).

In this paper, we focus on the coverage of the epistemic and linguistic aspects of argumentation. Apart from the theoretical rationale as illustrated, reason for this choice is that argumentation is closely interrelated with these dimensions in international curriculum and assessment documents. For example, The PISA framework (Organisation for Economic Cooperation and Development 2006 , p. 29) emphasizes three dimensions of the scientific competence characterized as the abilities to

Identify scientific issues and questions that could lend themselves to answers based on scientific evidence.

Explain or predict phenomena by applying appropriate knowledge of science.

Use scientific evidence to draw and communicate conclusions and to identify the assumptions, evidence and reasoning behind conclusions.

Among these aims, it is the third that can be identified as targeting the same practices as argumentation, namely the use of evidence to evaluate scientific claims, be it to draw conclusions from evidence or to identify the evidence behind conclusions. Though, certainly, the three dimensions are related.

In the USA, National Research Council ( 2012 ), p.49) outlines the key aspects of scientific practices as follows:

Asking questions (for science) and defining problems (for engineering)

Developing and using models

Planning and carrying out investigations

Analysing and interpreting data

Using mathematics and computational thinking

Constructing explanations (for science) and designing solutions (for engineering)

Engaging in argument from evidence

Obtaining, evaluating and communicating information.

Argumentation is explicitly stated in Practice 7 (‘Engaging in argument from evidence’), and it is also implicitly covered in Practices 4 (‘Analyzing and interpreting data’) and 8 (‘Obtaining, evaluating and communicating information’). The general aims that integrate features of argumentation are focused on empowering students to talk and to write science as well as on supporting their enculturation into science communities and their acquisition of epistemic criteria for knowledge evaluation. These perspectives address the epistemic and linguistic aspects of argumentation.

Epistemic practices are the cognitive and discursive activities that are targeted in science education to develop epistemic understanding (e.g. Duschl 2008 ; Duschl & Grandy 2008 ). These practices include the articulation and evaluation of knowledge, coordination of theory and evidence, making sense of patterns in data, and holding claims accountable to evidence and criteria all aspects of scientific argumentation. The argumentation studies addressing the understanding of scientific epistemology resulted in the observation that students have to be in instructional contexts where they make explicit epistemic decisions to understand scientific practices (Sandoval & Millwood 2005 ). Sandoval and Millwood argued that to make the epistemic decisions explicit, pedagogical strategies such as constructing and evaluating arguments are needed. Similarly, Erduran & Jimenez-Aleixandre ( 2007 ) claimed that argumentation, involving the justification of claims through evidence, may support the development of scientific epistemology and understanding of the practices of the scientific community. The role of language, particularly the relation between ways of thinking and talking, has been prevalent across many areas of science education (and not only in argumentation) due to prevalence of socio-cultural theories of learning through the popularization of Lev Vygotsky’s work (e.g. Lemke 1990 ; Mortimer & Scott 2003 ).

In summary, our aim in this study was to investigate to what extent the argumentation research in science education utilized epistemic and linguistic perspectives in contribution to the development of argumentation theory in science education with the potential to influence the achievement of related goals in educational outcomes.

The methodological process followed the steps of review methods, which were developed by the Evidence for Policy and Practice Information and Coordinating Centre for systematic reviews of educational research literature (Bennett et al. 2005 ). The review has three main phases as follows:

Selection of research papers related to argumentation for analysis : The criteria by which studies are to be included in, or excluded from, the review were determined. The studies which appear to meet these criteria were listed by means of electronic database searching, and then the abstracts of the studies were screened to see if they meet the inclusion criteria.

The study is based on the review of published articles in the journals SE, IJSE and JRST from 1998 to 2014. The rationale for the choice of these three journals is that they are the major journals that have high impact factors in science education research. Book reviews, replies, erratum and editorial materials were all excluded because we were interested in investigating original research contributions. The number of total articles was 3,076, of which approximately 5% were related to argumentation.

The research related to argumentation was sorted out through electronic database search, where the criterion was to include the keyword stem ‘argu-’ (to detect the words argue, arguing, argument, argumentation). A second-level screening of the abstracts resulted in the exclusion of some of the articles since the keyword ‘argue’ does not refer to the content of argumentation in science education but only is used as a verb in a generic sense, like ‘ as researcher , we argue that …’ Once this step eliminated irrelevant articles, it was sufficient for an article to include just one of the keywords to be included in the analysis. The resulting number of research articles is provided in Table  1 .

Identifying keywords and generating systematic categories : Each of the included studies was coded against a pre-agreed list of keywords related to epistemic and linguistic aspects of argumentation. The list was then used to generate a systematic map of the argumentation studies. The studies were grouped according to their emphasis on each of these aspects denoted by the keywords.

The researchers agreed on a list of keywords addressing epistemic, linguistic and wider epistemic aspects of argumentation. The keyword identification was based on the potential contributions from the introduction of argumentation in the science classrooms, drawn from diverse foundational disciplines such as philosophy, linguistics and communication (Erduran & Jimenez-Aleixandre 2007 ). For example, we identified the keywords ‘claim’, ‘evidence’, ‘justif-’ (to detect the words such as justification, justify, justifying) and ‘reason-’ (to detect the words such as reasoning, reason) in order to address argumentation-specific epistemic aspects. The linguistic aspects of argumentation were addressed by means of the keywords ‘talk’, ‘discuss’, ‘discourse’, ‘conversation’, ‘dialog-’ (to detect the words such as dialogue, dialogic, etc.) and ‘negotiat-’ (to detect the words such as negotiation, negotiate). These keywords were identified considering the relation of argumentation to the communicative competencies and socio-cultural perspectives. The keywords ‘inquiry’ and ‘expla-’ (to detect the words such as explain, explanation) address wider epistemic aspect of argumentation. We wanted to differentiate the argumentation-specific epistemic aspects such as ‘reason’ and ‘justification’ from broader epistemic aspects such as ‘explanations’ and ‘inquiry’ which can potentially be explored without a specific emphasis on argumentation. In the analyses of the data in this study, these two aspects (argumentation-specific epistemic and wider epistemic) were considered under the category of epistemic aspect of argumentation. Table  2 summarizes the keywords framing the categories.

An article may have had more than one occurrence of a keyword, but the category was coded just once to indicate that article includes that keyword. In other words, for the purposes of this analysis, we were not interested in the frequency but rather the occurrence of whichever aspect of argumentation. Moreover, the meaning of a keyword in a research article was taken into account since the keyword might not be used in relation to argumentation. For example, when inspecting the keyword ‘discuss’, if the researchers used it in a way to indicate their discussion related to the findings of the study such that ‘ The findings and further implications of the study were discussed ’ that article was not coded as having the keyword ‘discuss’. Instead, if the researchers used the keyword to indicate a communicative competency such as ‘ Students involved in small-group discussion ’, the article is considered to be one addressing a linguistic aspect of argumentation.

In-depth review and data extraction : The studies were listed and evaluated according to the categories described in 1 and 2 to identify the patterns such as the distribution of articles related to argumentation in all journals across time and across journal, and the distribution of articles based on epistemic and linguistic aspects.

Results and discussion

All of the published papers in SE, IJSE and JRST between the years 1998 and 2014 were analysed first for whether or not argumentation was covered and, second, for their emphasis on different aspects of argumentation. In total, among 3,076 articles during this period, approximately 5% of articles related to broad range of ‘argumentation’ research (Table  1 ). This ratio of articles related to argumentation within each journal is different for SE as the highest of all (5.7%) and quite similar for IJSE and JRST (4.8% and 4.7%, respectively).

Trends across years and across journals

In order to identify chronological trends in the argumentation literature across the timeframe covered, we looked for the number of argumentation articles published each year in each of the journals (see Figure  1 ). The number of argumentation-related articles each year increased gradually. For example, between the years 1998 and 2002, there were 19 articles published; between 2003 and 2007, there were 27 articles; between years 2008 and 2012, there were 69 articles; and the last 2 years, the total number of argumentation-related articles was 38. The trend is that the number of articles published in the last 7-year period (2008–2014), which was 107, is more than twice of the previous 7-year period (2001–2007), which was 36, and more than the total of the first 10-year period (1998–2007), which was 46. This trend indicates a steady increase in the amount of research reported on argumentation in the last 7 years.

Number of argumentation articles published in SE, JRST and IJSE from 1998 to 2014.

The investigation of the distribution of articles for each journal across time provided a chronological pattern regarding to what extent a specific journal followed a similar tendency towards argumentation as the general pattern. The results showed that all three journals published research articles related to argumentation in increasing numbers across the timeframe investigated. The only exception for this trend is that in JRST, there was a slight decrease between 2003 and 2007.

The highest frequency of publication of argumentation-related studies in a journal was seen between 2007 and 2014 for all three journals. In other words, IJSE published 78.4% of argumentation-related articles between these years, while JRST published 71.8% and SE published 72.5% in this period. However, in total, the highest frequency between 2007 and 2014 was in IJSE. That is, of the 115 argumentation-related articles in total in this period, 50.4% were published in IJSE, followed by 25.2% in SE and 24.4% in JRST.

Trends related to epistemic and linguistics aspects

Overall, there were 153 articles that used the term argumentation or argu- explicitly in the title or abstract. These articles were further examined against a pre-agreed list of keywords in terms of their emphasis on epistemic or linguistic aspects of argumentation. A high percentage of research articles (90.2%) in all three journals considered argumentation from epistemic and/or linguistic perspective (Table  3 ).

The research articles in each journal put more emphasis on the epistemic aspects as compared to the linguistic aspects. For example, in SE and JRST, while there were 31 articles addressing epistemic aspects of argumentation, there were 27 articles addressing linguistic aspects. The difference between two aspects in IJSE was more pronounced. That is, there were 54 articles addressing epistemic aspects and 45 articles addressing linguistic aspects.

The distribution of epistemic and linguistic aspects for time periods across journals gave a picture of how the trends within argumentation research have evolved (Figure  2 ). We selected the first time period to be 1998–2006 because this time period represents the release of argumentation studies in three journals until there is a sharp increase in the number of studies as indicated above. After the year 2007, the time periods were divided into 2-year intervals to observe the trends more closely across the journals in terms of their emphasis on epistemic and linguistic aspects. In line with the increase of interest in argumentation research in science education beginning in 2007, the number of articles addressing epistemic aspects and linguistic aspect showed increase, too. However, it makes sense to evaluate the trend by looking at the percentage of articles addressing each aspect for each time period within the total number of articles published in that time period.

Distribution of journal articles with epistemic and linguistic aspects across time intervals with detailed focus in timeframes 2007–2014.

The research on argumentation puts heavy emphasis either on epistemic and/or linguistic aspects of argumentation or both aspects at the same time. The other aspects of argumentation have been investigated in relatively low percentages in each time period (8% between 1998 and 2006, 10% between 2007–2008 and 2009–2010, 7%% between 2011 and 2012 and 13% between 2013 and 2014). The epistemic aspects of argumentation received much more attention by researchers through almost all time periods, with an exception of 2007–2008 timeframe. However, it is plausible that researchers tended to consider these two aspects to be highly interrelated. Indeed, considering the intertwined perspectives in argumentation research in science education, it makes sense that these two aspects were examined together in high percentages in each time period and retained their importance since 1998 at almost the same rate (55% between 1998 and 2006, 50% between 2007 and 2008, 57% between 2009 and 2010, 44% between 2011 and 2012 and 45% between 2013 and 2014).

When each journal was investigated separately, some fluctuations in the patterns were observed. For example, according to the graph demonstrating the articles addressing epistemic aspects for each journal (Figure  3 ), the frequency was lower in the last years compared to the early years of argumentation research in science education for IJSE (from 81.7% between 1998 and 2006 to 70% between 2013 and 2014) whereas in JRST and SE, there were fluctuations in the trends across the years eventually leading to more argumentation studies focusing on epistemic aspects in JRST (from 81.8% between 1998 and 2006 to 75% between 2009 and 2010 and to 90% between 2013 and 2014), but less attention to this aspect in SE (from 63.6% between 1998 and 2006 to 88.9% between 2009 and 2010 and to 75% between 2013 and 2014).

Distribution of articles with emphasis on epistemic aspects of argumentation in each journal.

The trend in research addressing linguistic aspects for each journal across time was similar (Figure  4 ). In particular, in two journals, SE and IJSE, the interest in linguistic aspects dropped, compared to the early years (from 81.8% between 1998 and 2006 to 50% between 2013 and 2014 for SE and from 68.8% between 1998 and 2006 to 50% between 2013 and 2014 for IJSE). However, in JRST, papers reported on the linguistic aspects in gradually increasing percentages (from 63.6% between 1998 and 2006 to 70% between 2013 and 2014).

Distribution of articles with emphasis on linguistic aspects of argumentation in each journal.

We should note that the research articles addressing the linguistic aspects along with the epistemic aspects or vice versa were also included in these analyses. Further analyses, in which the research articles in each journal were differentiated as those (a) articles addressing only epistemic aspects, (b) articles addressing only linguistics aspects, (c) articles addressing both aspects, and (d) articles addressing none of the two aspects, resulted in interesting findings (Figure  5 ).

Distribution of papers focusing on epistemic, linguistic, both or neither aspect of argumentation across journals.

The trend in SE and JRST looks similar in some ways; for example, at the beginning of the timeline, both journals published papers addressing either epistemic/linguistic aspect (27% only linguistic aspect in SE, 27% only epistemic aspect in JRST) or both of them together (55% in SE, 55% in JRST). On the contrary in IJSE, even in the early years of argumentation research, studies addressed diverse aspects of argumentation, including linguistic and epistemic aspects together in high percentages (56%). Such comprehensive studies emerged in JRST beginning in 2007. For SE, the situation was reversed such that in SE, beginning from 2007, there were more argumentation studies focusing on only epistemic aspects (23% between 2007 and 2010 and 31% between 2011 and 2014) along with those addressing both aspects (62% between 2007 and 2010 and 50% between 2011 and 2014). Interestingly, in those years, linguistic aspects hardly attracted interest in SE (8% between 2007 and 2010 and 6% between 2011 and 2014). The 2007–2014 period made more reference to diverse aspects of argumentation.

Epistemic aspects in detail

The epistemic aspects of argumentation were examined in two groups of keywords: argumentation-specific epistemic practices such as ‘claim’, ‘justify’, ‘evidence’ and general or wider epistemic practices such as ‘inquiry’ and ‘explanation’. The distribution of these keywords allowed for an analysis of trends across the journals (Figure  6 ). An article might have more than one keyword at the same time, and each keyword was considered separately. That is, for example, if an article had the keywords ‘inquiry’ and ‘claim’, this article was counted in both the list of articles having keyword ‘inquiry’ and in the list of articles having keyword ‘claim’.

Keyword analysis of trends for epistemic aspects across journals.

The analysis of the distribution of the keywords related to epistemic aspects of argumentation for each journal suggested the strongest connection between ‘reason/reasoning’ and ‘argumentation’. The keyword ‘reason’, which we examined as an argumentation-specific epistemic keyword, was connected with ‘argumentation’ by 33.3% of the articles. Specifically, the keyword was highly emphasized in IJSE (27%), JRST (46.2%) and SE (32.5%) in connection with argumentation. However, it is important to note that in SE, all other keywords referring to the epistemic aspects of argumentation were emphasized at about the same percentages (between 25.0% and 32.5%), with an exception of ‘justif-’ showing a slight variation (22.5%). The general epistemic keywords ‘inquiry’ and ‘expla-’ were related to argumentation as much as the argumentation-specific epistemic keyword ‘evidence’ (25.0%). Therefore, we cannot particularly infer whether argumentation-specific keywords or general epistemic keywords had received more attention as a research focus.

The top three epistemic keywords based on the previous analysis, ‘evidence’, ‘reason’, and ‘expla-’, were examined further for their distribution for each journal across years (Figure  7 ).

Top epistemic keywords across time.

Between 1998 and 2010, the keyword ‘reason’ was used in relation to argumentation in high percentages. Specifically, it was emphasized in 45.5% of the articles in this time period in JRST, which is the highest compared to the other keywords as well as 33.3% in IJSE and 37.5% in SE. The keyword ‘evidence’ was the most emphasized epistemic keyword in the following years in all journals (between 52.9% and 18.8%).

Linguistic aspects in detail

The keywords illustrating linguistic aspects of argumentation were examined to identify more specific trends (Figure  8 ). The distribution of the keywords illustrates which linguistic aspects were emphasized mostly across journals.

Keyword analysis of trends for linguistic aspects across journals.

In one sense, it seems as if the research made strong connections between ‘discuss’ and ‘argumentation’ (27.5%) as well as ‘discourse’ and ‘argumentation’ (28.1%). Specifically, in IJSE, ‘discuss’ was the leading linguistic keyword (32.4% of the argumentation articles in IJSE) and ‘discourse’ was emphasized more than any of the linguistic keywords in JRST and in SE (35.9% of the argumentation articles in JRST and 27.5% in SE). On the other hand, the nature of ‘conversation’ and ‘negotiation’ among the participants of argumentation did not receive so much attention (4.6% and 5.2%, respectively, for JRST and SE).

The top two linguistic keywords based on the previous analysis, ‘discuss’ and ‘discourse’, were examined further for their distribution for each journal across the years (Figure  9 ).

Top linguistic keywords across time.

The trend was interesting in that although the journals showed back and forth patterns in their emphasis on each of the two keywords across the years, the total trend indicated that while in the early years, articles were establishing connections between ‘discourse’ and ‘argumentation’ (21.6%), and recently, between 2011 and 2014, articles studied argumentation more in connection with ‘discuss’ (11.1%).

The paper contributes to science education literature by highlighting the key conceptualizations around argumentation, a significant theme of research in recent years. The conceptualization is based on the epistemic and linguistic aspects of argumentation. By reviewing and quantifying the trends in the uptake of argumentation and related concepts, we examined the various ways in which this area of research has been covered in the literature. Our discussion presents a nuanced approach for the finer details of how argumentation is covered across time as well as across some key journals. The study provides meta-analysis and synthesis of an important territory of research and holds the potential to contribute to the characterization of the accumulated knowledge.

One of the contributions of our analysis is the illustration that researchers studying argumentation from a linguistic perspective have been emphasizing related concepts in different ways. While the emphasis has been on ‘discourse’ and ‘discussion’ across all journals, the related concepts of ‘talk’, ‘conversation’, ‘dialogue’ and ‘negotiation’ were observed at a lesser extent. A comparison between the epistemic aspects and linguistic aspect displays that researchers emphasized the linguistic aspect of argumentation more than the epistemic aspects. This might be the result of researchers’ considering argumentation as a tool instrumental in the achievement of scientific inquiry (Erduran & Jimenez-Aleixandre 2007 ) as well as a vital component of scientific discourse (Pera 1994 ). These findings can provide evidence-based indicators for where more emphasis needs to be placed in both research, and in particular, they can provide guidelines for journal editors in soliciting articles that target underemphasized aspects of argumentation.

The trends as investigated in this study suggest that the number of argumentation-related studies is more in IJSE compared to SE and JRST mainly because the number of issues in IJSE is 18 per year, while it is 6 per year for SE and 10 per year for JRST. However, one critical breakpoint seems to be the year 2007 for argumentation research. The number of argumentation articles were especially few between years 2005 and 2007 (Figure  1 ), but there is a sharp increase after the year 2007. One major explanation for this increase might be the publishing of the preliminary articles that would have probably preceded and guided the oncoming articles both in terms of philosophy and methodology. For example, TAPping into argumentation: Developments in the application of Toulmin’s argument pattern for studying science discourse (Erduran et al. 2004 ) published in SE provided a method for analysing argumentation that was widely used by science education researchers afterwards. Patterns of informal reasoning in the context of socioscientific decision making (Sadler & Zeidler 2005 ) published in JRST contributed to a theoretical knowledge base for extending the school-based research to informal learning contexts.

Another potential reason in increasing attention at argumentation studies might be the release of important policy documents addressing argumentation in various national contexts at the beginning of 2000s leading to the necessity of research in the area. For example, in the UK, the importance of argument was set as an educational goal by means of the documents such as the Ideas and Evidence (DfES/QCA 2004 ) and How Science Works (Qualifications and Curriculum Authority 2007 ) components of the National Science Curriculum. In the new Spanish National Curriculum for secondary schooling, the relevance of the use of evidence and of argumentation is emphasized both in the general definition of basic competencies and in the description of goals in the science subjects (Ministerio de Educación y Ciencia, Spain MEC 2007 ). In Turkey, the national reform efforts have promoted informed citizenship where individuals make evidence-based judgements in their everyday lives including issues that relate to science (Milli Egitim Bakanligi, Turkey 2005 ). The examples can be extended, but the main idea is that in numerous science education policies across the world, the trends between the years 2005 and 2007 highlight the significance of argumentation with connection to scientific literacy or science-society-technology goals.

In future reporting of related work, we intend to discuss detailed qualitative characterizations of the language used around ‘argumentation’ illustrating the range of meanings researchers have attributed to ‘argumentation’. For example, while some researchers have focused on the use of Stephen Toulmin’s framework of argument (e.g. Erduran et al. 2004 ), others have begun to incorporate Douglas Walton’s scheme (e.g. Ozdem et al. 2013 ). However, even within the particular characterizations of argument from, say, a Toulmin perspective, there may be qualitative variations in the way that researchers have adapted his framework (e.g. Zohar & Nemet 2002 ; Jimenez-Aleixandre et al. 2000 ). As stated at the beginning of the paper, we are also mindful of reporting on the relation of SSI and argumentation, and the trends around how these bodies of work have interacted in recent years. Hence, a detailed articulation of such variations is likely to contribute to an assessment of where and how future studies on argumentation can place a concerted effort in maximizing understanding of argumentation’s utility for science teaching and learning.

Overall, the paper outlines a methodological approach on journal content analysis that is theoretically driven in terms of the epistemic and linguistic aspects of argumentation. The study provides evidence for how science educators worldwide have situated argumentation from different perspectives within the educative domain thereby generating pedagogical, curricular and instructional explanations on how argumentation in science education can be conceptualized. These results might be of use and interest to other researchers whose work does not necessarily concern argumentation but is underlined by epistemic and linguistic accounts of science teaching and learning as well as those researchers who might be interested in carrying out content analyses of journals on other topics.

Abbreviations

Science technology engineering mathematics

Socio-scientific issues

• Science education

International journal of science education

Journal of research in science teaching

Anderson, RD, Kahl, SR, Glass, GV, & Smith, ML. (2006). Science education: a meta-analysis of major questions. Journal of Research in Science Teaching, 20 (5), 379–385.

Article   Google Scholar  

Bennett, J, Lubben, F, Hogarth, S, & Campbell, B. (2005). A systematic review of the use of small-group discussions in science teaching with students aged 11–18, and their effects on students’ understanding in science or attitude to science. In Research Evidence in Education Library . London: EPPICentre, Social Science Research Unit, Institute of Education.

Google Scholar  

Berland, LK, & Reiser, B. (2009). Making sense of argumentation and explanation. Science Education, 93 (1), 26–55.

Bowen, CW. (1992). A survey of types of articles published in science education literature. Journal of Experimental Education, 60 (2), 13–140.

Brown, AL, & Campione, JC. (1990). Communities of learning and thinking, or a context by any other name. In D. Kuhn (Ed.) Developmental perspectives on teaching and learning thinking skills (special issue). Contribution to. Human Development, 21 , 108–126.

Buty, C, & Plantin, C. (2008). Introduction. L’argumentation à l’épreuve de l’enseignement des sciences et vice-versa [Introduction. Argumentation put to the test of science education and vice-versa]. In C Buty & C Plantin (Eds.), Argumenter en classe de sciences [Engaging in argumentation in science classrooms] (pp. 17–41). Lyon: Institut National de Recherche Pédagogique.

Chang, YH, Chang, CY, & Tseng, YH. (2010). Trends of science education research: an automatic content analysis. Journal of Science Education and Technology, 19 , 315–331.

Qualifications and Curriculum Authority (2007). How science works . Retrieved on March 26 from www.qca.org.uk .

DfES/QCA. (2004). Science: the National Curriculum for England and Wales . London: HMSO.

Duschl, RA. (2008). Quality argumentation and epistemic criteria. In S Erduran & MP Jiménez Aleixandre (Eds.), Argumentation in science education: perspectives from classroom-based research (pp. 159–175). Dordrecht: Springer.

Duschl, R, & Grandy, R (Eds.). (2008). Teaching scientific inquiry: recommendations for research and implementation . Rotterdam: Sense Publishers.

Erduran, S. & Jimenez-Aleixandre, MP. (2007). Research in argumentation in science education: perspectives from classroom-based research (p. 285). Dordrecht: Springer. ISBN: 978-1-4020-6669-6).

Erduran, S, & Jimenez-Aleixandre, JM. (2012). Research on argumentation in science education in Europe. In D Jorde & J Dillon (Eds.), Science education research and practice in Europe: retrospective and prospective (pp. 253–289). Rotterdam: Sense Publishers.

Chapter   Google Scholar  

Erduran, S, Simon, S, & Osborne, J. (2004). TAPping into argumentation: developments in the use of Toulmin’s argument pattern for studying science discourse. Science Education, 88 (6), 915–933.

European Union (2006). Recommendation of the European Parliament and of the Council of 18 December 2006 on key competences for lifelong learning . Official Journal of the European Union, 30–12–2006, L 394/10–L 394/18. ( http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:32006H0962 )

Foreman-Peck, L, & Winch, C. (2010). Using educational research to inform practice: a practical guide to practitioner research in universities and colleges . London: Routledge.

Giere, R. (1988). Explaining science. A cognitive approach . Chicago: The University of Chicago Press.

Book   Google Scholar  

Habermas, J. (1981). The theory of communicative action . Boston: Beacon Press.

Henson, KT. (2001). Writing for professional journals: paradoxes and promises. Phi Delta Kappan, 82 , 765–768.

Jiménez-Aleixandre, MP, & Federico-Agraso, M. (2009). Justification and persuasion about cloning: arguments in Hwang’s paper and journalistic reported versions. Research in Science Education, 39 (3), 331–347. doi:10.1007/s11165-008-9113-x.

Jimenez-Aleixandre, MP, Bugallo, A, & Duschl, RA. (2000). “Doing the lesson” or “doing science”; argument in high school genetics. Science Education, 84 (6), 757–792.

Kelly, GJ, & Chen, C. (1999). The sound of music: constructing science as sociocultural practices through oral and written discourse. Journal of Research in Science Teaching, 36 (8), 883–915.

Kelly, GJ, & Takao, A. (2002). Epistemic levels in argument: an analysis of university oceanography students’ use of evidence in writing. Science Education, 86 (3), 314–342.

Kitcher, P. (1988). The child as parent of the scientist. Mind and Language, 3 (3), 215–228.

Kuhn, D, & Crowell, A. (2011). Dialogic argumentation as a vehicle for developing young adolescents’ thinking. Psychological Science, 22 (4), 545–552. doi:10.1177/0956797611402512.

Lee, M-H, Wu, Y, Tien, T, & Chin-Chung, A. (2009). Research trends in science education from 2003 to 2007: a content analysis of publications in selected journals. International Journal of Science Education, 31 (15), 1999–2020.

Lemke, J. (1990). Talking science. Language, learning and values . Norwood, NJ: Ablex.

Lin, TC, Lin, TJ, & Tsai, CC. (2014). Research Trends in Science Education from 2008 to 2012: a systematic content analysis of publications in selected journals. International Journal of Science Education, 36 (8), 1346–1372.

Mason, L. (1996). An analysis of children’s construction of new knowledge through their use of reasoning and arguing in classroom discussions. International Journal of Qualitative Studies in Education, 9 (4), 411–433.

Milli Egitim Bakanligi, Turkey. (2005). Ilkögretim fen ve teknoloji dersi ögretim programi (6, 7 ve 8. siniflar) . Ankara, Turkey: Milli Egitim Bakanligi.

Ministerio de Educación y Ciencia, Spain (MEC). (2007). Real decreto 1631/2006 enseñanzas mínimas educación secundaria obligatoria. Boletín Oficial del Estado, 5 , 677–773.

Mortimer, EF, & Scott, PH. (2003). Meaning making in secondary science classrooms . Maidenhead: Open University Press.

National Research Council. (2012). A framework for K-12 science education . Washington, DC: National Academies Press.

Organisation for Economic Cooperation and Development. (2006). PISA 2006. Assessing scientific, reading and mathematical literacy: a framework for PISA 2006 . Paris: OECD.

Ozdem, Y, Cakiroglu, J, Ertepinar, H, & Erduran, S. (2013). The nature of pre-service science teachers’ argumentation in inquiry-oriented laboratory context. International Journal of Science Education, 35 (15), 2559–2586.

Pera, M. (1994). The discourses of science . Chicago: University of Chicago Press.

Sadler, TD, & Zeidler, DL. (2005). Patterns of informal reasoning in the context of socioscientific decision making. Journal of Research in Science Teaching, 42 (1), 112–138.

Sandoval, WA, & Millwood, KA. (2005). The quality of students’ use of evidence in written scientific explanations. Cognition and Instruction, 23 (1), 23–55.

Siegel, H. (1989). The rationality of science, critical thinking and science education. Synthese, 80 , 9–41.

Slavin, RE, Lake, C, Chambers, B, Heung, A, & Davis, S. (2009). Effective reading programs for the elementary grades: a best-evidence synthesis. Review of Educational Research, 79 (4), 1391–1466.

Toulmin, S. (1958). The uses of argument . Cambridge, England: Cambridge University Press.

Zohar, A, & Nemet, F. (2002). Fostering students’ knowledge and argumentation skills through dilemmas in human genetics. Journal of Research in Science Teaching, 39 (1), 35–62.

Download references

Author information

Authors and affiliations.

University of Limerick, Castletroy, Co., Limerick, Ireland

Sibel Erduran

Gaziosmanpasa University, Yeniyurt Mh, 60100, Tokat, Turkey

Yasemin Ozdem

Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, South Korea

Jee-Young Park

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Sibel Erduran .

Additional information

Competing interests.

The authors declare that they have no competing interests.

Authors’ contributions

SE has made substantial contributions to the conception and design, acquisition as well as analysis and interpretation of data; has been involved in drafting the manuscript or revising it critically for important intellectual content; has given final approval of the version to be published; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. YOY has made substantial contributions to the conception and design, acquisition as well as analysis and interpretation of data; has been involved in drafting the manuscript or revising it critically for important intellectual content; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. JYP has made substantial contributions to the acquisition as well as analysis and interpretation of data; has given final approval of the version to be published; and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final manuscript.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0 ), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Erduran, S., Ozdem, Y. & Park, JY. Research trends on argumentation in science education: a journal content analysis from 1998–2014. IJ STEM Ed 2 , 5 (2015). https://doi.org/10.1186/s40594-015-0020-1

Download citation

Received : 04 September 2014

Accepted : 25 February 2015

Published : 16 April 2015

DOI : https://doi.org/10.1186/s40594-015-0020-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Argumentation
• Journal content analysis
• Trends in research

Schools are using research to try to improve children’s learning – but it’s not working

Senior Research Fellow in the Centre for Teachers and Teaching Research, UCL

Disclosure statement

Sally Riordan is currently working on two projects that receive funding from the Education Endowment Foundation.

University College London provides funding as a founding partner of The Conversation UK.

View all partners

Evidence is obviously a good thing. We take it for granted that evidence from research can help solve the post-lockdown crises in education – from how to keep teachers in the profession to how to improve behaviour in schools, get children back into school and protect the mental health of a generation.

But my research and that of others shows that incorporating strategies that have evidence backing them into teaching doesn’t always yield the results we want.

The Department for Education encourages school leadership teams to cite evidence from research studies when deciding how to spend school funding. Teachers are more frequently required to conduct their own research as part of their professional training than they were a decade ago. Independent consultancies have sprung up to support schools to bring evidence-based methods into their teaching.

This push for evidence to back up teaching methods has become particularly strong in the past ten years. The movement has been driven by the Education Endowment Foundation (EEF), a charity set up in 2011 with funding from the Conservative-Liberal Democrat coalition government to provide schools with information about which teaching methods and other approaches to education actually work.

The EEF funds randomised controlled trials – large-scale studies in which students are randomly assigned to an educational initiative or not and then comparisons are then made to see which students perform better. For instance, several of these studies have been carried out in which some children received one-on-one reading sessions with a trained classroom assistant, and their reading progress was compared to children who had not. The cost of one of these trials was around £500,000 over the course of a year.

Trials such as this in education were lobbied for by Ben Goldacre , a doctor and data scientist who wrote a report in 2013 on behalf of the Department for Education. Goldacre suggested that education should follow the lead of medicine in the use of evidence.

Using evidence

In 2023, however, researchers at the University of Warwick pointed out something that should have been obvious for some time but has been very much overlooked – that following the evidence is not resulting in the progress we might expect.

Reading is the most heavily supported area of the EEF’s research, accounting for more than 40% of projects . Most schools have implemented reading programmes with significant amounts of evidence behind them. But, despite this, reading abilities have not changed much in the UK for decades.

This flatlining of test scores is a global phenomenon . If reading programmes worked as the evidence says they do, reading abilities should be better.

And the evidence is coming back with unexpected results. A series of randomised controlled trials, including one looking at how to improve literacy through evidence , have suggested that schools that use methods based on research are not performing better than schools that do not.

In fact, research by a team at Sheffield Hallam University have demonstrated that on average, these kinds of education initiatives have very little to no impact .

My work has shown that when the findings of different research studies are brought together and synthesised, teachers may end up implementing these findings in contradictory ways. Research messages are frequently too vague to be effective because the skills and expertise of teaching are difficult to transfer.

It is also becoming apparent that the gains in education are usually very small, perhaps because learning is the sum total of trillions of interactions. It is possible that the research trials we really need in education would be so vast that they are currently too impractical to do.

It seems that evidence is much harder to tame and to apply sensibly in education than elsewhere. In my view, it was inevitable and necessary that educators had to follow medicine in our search for answers. But we now need to think harder about the peculiarities of how evidence works in education.

Right now, we don’t have enough evidence to be confident that evidence should always be our first port of call.

• Young people
• Department for Education

Faculty of Law - Academic Appointment Opportunities

Operations Manager

Senior Education Technologist

Audience Development Coordinator (fixed-term maternity cover)

Lecturer (Hindi-Urdu)

SCIENCE & ENGINEERING INDICATORS

Higher education in science and engineering.

• Report PDF (1.9 MB)
• Report - All Formats .ZIP (9.2 MB)
• Supplemental Materials - All Formats .ZIP (6.4 MB)
• MORE DOWNLOADS OPTIONS
• Share on X/Twitter
• Share on Facebook
• Share on LinkedIn
• Send as Email

Technical Appendix

Methodology notes for international degree data.

International data for first degrees and doctoral degrees for the Higher Education in Science and Engineering report were retrieved from several sources. Data were sourced from the Organisation for Economic Co-operation and Development (OECD), Eurostat, and several national and regional statistical offices. These methodology notes provide details on the degree field classifications, degree-level definitions, and sources used for the international higher education data.

Degree Fields and Levels

Fields of degree used in the international section of this report are based on the most recent coding system of the International Standard Classification of Education (ISCED) , ISCED Fields of Education and Training 2013 (ISCED-F 2013), to facilitate international comparisons. Table SAHED-1 shows the crosswalk of science and engineering (S&E) degree fields used to map degree data from regional and national data sources to the fields used in this report. Comparing degree fields across higher education systems with different degree taxonomies may require classification decisions that unavoidably result in either overcounting or undercounting of degree fields of interest. For example, degrees in political science and sociology are reported under the law field by China, but data are not published for these fields individually. Political science and sociology are typically included within social and behavioral sciences, but this report does not classify degrees awarded in law within social and behavioral sciences for China because the law field also includes traditional legal disciplines.

Crosswalk of S&E fields for international higher education data, by selected region, country, or economy and field

NA = not available.

ISCED = International Standard Classification of Education; ISCED-F = ISCED Fields of Education and Training; IT = information technology; OECD = Organisation for Economic Co-operation and Development.

a China data include computer sciences under engineering.

Organisation for Economic Co-operation and Development (OECD), OECD.Stat; Eurostat, Education and training database; National Bureau of Statistics of China, China Statistical Yearbook (various years); People's Republic of China, Ministry of Education data (various years); Ministry of Education, Educational Statistics of the Republic of China (Taiwan) (various years); Government of India, Ministry of Human Resource Development, Department of Higher Education, All India Survey on Higher Education (various years).

Science and Engineering Indicators

Levels of degree for international degree data in this report are based on the ISCED 2011 system. Doctoral degrees correspond to ISCED 2011 level 8 (doctoral or equivalent). First degrees may correspond to ISCED 2011 level 6 (bachelor’s or equivalent) or include a combination of degrees at ISCED 2011 levels 6 and 7 (master’s or equivalent), depending on the data source. Some countries grant bachelor’s degrees and “long first degrees.” These degrees typically take at least 5 years to complete and involve training at a level comparable to a master’s degree in the United States. Similar to bachelor’s degree programs, long first degree programs only require completion of secondary education to enroll, and completion of a program provides the first opportunity to enter the labor market with an academic credential at the tertiary level (excluding shorter-duration, occupationally focused programs). OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions and Classifications . Paris, France: OECD Publishing. Available at https://doi.org/10.1787/9789264304444-en . Accessed 24 June 2021." data-bs-content="For a detailed discussion on classifying educational programs to ISCED levels, see OECD. 2018. OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions and Classifications . Paris, France: OECD Publishing. Available at https://doi.org/10.1787/9789264304444-en . Accessed 24 June 2021." data-endnote-uuid="aa273648-c897-44e4-ad97-8df6707e756d">​ For a detailed discussion on classifying educational programs to ISCED levels, see OECD. 2018. OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions and Classifications . Paris, France: OECD Publishing. Available at https://doi.org/10.1787/9789264304444-en . Accessed 24 June 2021. The United States does not report long first degrees. Combined bachelor’s and master’s programs in the United States may provide roughly similar educational training to long first degrees, but there are very few such programs, and institutions award both degrees to these joint program graduates.

Where data are available, national totals for first degrees presented in the International S&E Higher Education section of the report equal the sum of first degrees at the bachelor’s level and long first degrees. For countries such as the United States that do not report data specifically for first degrees, first degree totals are bachelor’s degrees.

Unless otherwise specified, international degree data in the report were retrieved from the OECD statistical database, OECD.Stat . The data reported by OECD come from an annual collection of education data conducted jointly by the United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics, OECD, and Eurostat (UOE data collection). OECD degree data for 2013 and later years use current ISCED codes (ISCED 2011 levels of education, and ISCED-F 2013 fields of education). OECD data for 2012 and earlier years have been partially updated to the current classifications, but much of the data in earlier years are still based on ISCED 1997 codes. The transition in the data reporting includes changes in the degree fields and levels. These changes may lead to limitations in year-to-year comparability for first degrees for some countries, but they do not appear to pose methodological concerns for constructing an uninterrupted time series for doctoral degrees.

The crosswalk of fields of degree between early (ISCED 1997) and later (ISCED-F 2013) years of OECD data is included in Table SAHED-1 . This mapping applied to first degrees and doctoral degrees.

Mapping of levels of degree required different approaches for first degrees and doctoral degrees. OECD doctoral degrees were specified as ISCED 1997 level 6 (advanced research programs) for 2012 and earlier and ISCED 2011 level 8 (doctoral or equivalent) for 2013 and subsequent years. Mapping first degrees was a more complex process. Under the ISCED 1997 classification system, short-cycle tertiary education (comparable with an associate’s degree), bachelor’s degrees, and master’s degrees are collectively categorized under level 5. To identify the ISCED 1997 level 5 degrees comparable with first degrees under the ISCED 2011 system, level 5 degrees were refined using two additional criteria:

• Program destination: A (theoretically based programs that give access to advanced research qualifications or professions with high-skill requirements); ​ In contrast, shorter-duration ISCED 1997 5B programs focus on acquiring occupation-specific skills and credentials and include the equivalent of associate’s degrees. and
• Program orientation: first degree or qualification orientation.

First degrees under the ISCED 2011 system were specified as the sum of first degrees at level 6 (bachelor’s or equivalent) and long first degrees at level 7 (master’s or equivalent). If data were unavailable for first degrees at level 6, the sum of all level 6 degrees and level 7 long first degrees was used.

OECD Data Quality Notes

This report uses OECD degree data as provided by the OECD.Stat database. The change to ISCED 2011 levels of degree may have led to irregular reporting of first degree data during the transition in 2013 and subsequent years. The conventions used in this report for presenting first degrees led to a significant drop in the number of first degrees reported by OECD for Russia, from 1,406,050 in 2012 (ISCED 1997 system) to 129,375 in 2013, the first year of ISCED 2011 reporting. Reporting of degrees has continued to change across levels and categories of education in subsequent years. Degrees by level and category for Russia are presented in Table SAHED-2 to illustrate the changes in reporting.

Example OECD first degree data reporting: Degrees awarded by Russia, by level and category of education: 2013–18

ISCED = International Standard Classification of Education; OECD = Organisation for Economic Co-operation and Development.

Organisation for Economic Co-operation and Development (OECD), OECD.Stat.

The Eurostat Data Explorer was used to retrieve degree data on European Union (EU) countries that are not OECD members and not included in the OECD statistical database. These countries include Bulgaria, Croatia, Cyprus, Malta, and Romania. In some instances, Eurostat was used to supplement missing data for countries with data otherwise sourced from OECD. This approach was taken because the Eurostat database consistently provided the same data for OECD countries with joint coverage across the data sources. The consistency between the databases is unsurprising given that both rely on the same joint UOE data collection.

The Eurostat database uses the same ISCED system for levels and fields of education as the current OECD database. However, Eurostat provides totals for entire ISCED levels only, without the ability to identify the subset of first degrees at a given level. Specifically, there is no method to include only long first degrees at ISCED level 7 (master’s degree or equivalent) without including all degrees at ISCED level 7. Therefore, totals for ISCED level 6 (bachelor’s degree or equivalent) were used for first degrees for the select non-OECD EU members listed previously.

Other Countries and Economies

Degree award data for China for 2000–15 come from the China Statistical Yearbook of the National Bureau of Statistics of China and remain unchanged from Indicators 20 20 . New years of data come from annual tables published by the Ministry of Education . Data for first degrees were retrieved from table “Number of Regular Students for Normal Courses in HEIs (Higher Education Institutions) by Discipline” and data for doctorates were retrieved from table “Number of Postgraduate Students by Academic Field (Total).”

Degree award data for India were retrieved from the India Department of Higher Education’s All India Survey on Higher Education . Data for India in this report will not match data reported in Indicators 2020 , which were retrieved from OECD when available. OECD has since ceased publication of higher education degree data for India; thus, a national-level data source was required.

Data for Japan for 2000–13 remain unchanged from previous editions of Indicators . These data were retrieved from the Ministry of Education, Culture, Sports, Science and Technology Survey of Education. Data for 2014 and later were sourced from OECD. The OECD database was not used for prior years because its coverage of higher education for Japan is limited for earlier years. The change in data source from 2013 to 2014 led to a significant drop in the number of degrees in the social and behavioral sciences—and, thus, in overall S&E degrees.

All years of data for Taiwan use the Ministry of Education Main Statistics, Summary of Tertiary Education Institutes file. Data for all years have been updated since Indicators 20 20 . Changes in Taiwan’s classification of degree fields from 2016 to 2017 have caused some changes in the distribution of degrees reported among S&E fields, most notably an increase in computer sciences and a shift of degrees from agricultural sciences to life sciences.

Related Content

Research in Science Education

Research in Science Education is an international journal publishing and promoting scholarly science education research of interest to a wide group of people. The journal examines early childhood, primary, secondary, tertiary, workplace, and informal learning as they relate to science education.

In publishing scholarly articles, RISE is looking for articulation of the principles and practices used by scholars to make valid claims about the world and their critique of such claims. Publishing such work is important as it makes these principles and practices known to the scholarly community so that they can be considered, debated, judged, and accepted, rejected or reframed. Importantly, these principles and practices must be constantly advancing in ways that allow our knowledge to advance within the field. In looking for works to publish, RISE will seek articles that advance our knowledge in science education research rather than reproducing what we already know.

Research can take many forms, quantitative, qualitative and mixed methods to name a few. RISE is interested in producing valid and trustworthy research that takes on a variety of forms and embraces new capabilities at hand, particularly around new technologies. Innovative practices and how these relate to science education will be at the forefront of our thinking in RISE.

Scholarly works of interest need to encompass the wide diversity of readership. RISE is the journal associated with the Australasian Science Education Research Association (ASERA), one of the oldest such association in the world. With ASERA’s history from a colonial western tradition, combined with its location within the highly productive and exciting Asian region, the membership of ASERA and the readership of RISE spans the globe and cultural perspectives. Hence, the scholarly works of interest published within RISE need to reflect this diversity. Additionally, they must also include a diversity of form. So, RISE will continue to review articles, editorials, book reviews, and other material deemed appropriate by the Editors.

This is a transformative journal , you may have access to funding.

• Wendy Nielsen,
• Kok-Sing Tang

Latest issue

Volume 54, Issue 2

Latest articles

Exploring features that play a role in adolescents’ science identity development.

• Ella Ofek-Geva
• David Fortus

A Structural Model of Future-Oriented Climate Change Optimism in Science Education: PISA Evidence from Countries with Top Environmental Protection Index

• Kason Ka Ching Cheung

Mediational Affordances at a Science Centre Gallery: An Exploratory and Small Study Using Eye Tracking and Interviews

• Tang Wee Teo
• Zee Heng Joshua Loh
• Eugene Wambeck

A Co-design Based Research Study: Developing Formative Assessment Practices with Preservice Science Teachers in a Chemistry Laboratory Setting

• Osman Nafiz Kaya

Seventh-Grade Students’ Relational Conceptual Change and Science Achievement: Photosynthesis and Cellular Respiration Duo

• Ifeyinwa Uke
• Jazlin Ebenezer

Journal updates

Meet the editors: wendy nielsen & kok-sing tang.

Topical Collections in RISE

Research in Science Education (RISE) is pleased to announce the introduction of topical collections to complement the ongoing publication of papers through regular and special issues. A topical collection curates papers on a given topic, theme or problem. The articles in a topical collection are published continuously over several issues, making them different from special issues that are time-bounded and assigned to one issue. Articles selected for a topical collection will appear in that collection. At the same time, they will still be published in a regular issue.

Topical collections represent a chance for editors to gather related papers on a topic of contemporary interest to the RISE readership and the wider science education research community. As such, we are interested to develop collections that both consolidate a series of thematically-related papers previously published in RISE and encourage future developments in the field. This approach allows us to connect the rich  historical conversation in RISE with contemporary issues that matter to the science education community.

With this objective, RISE has launched two inaugural topical collections on “Artificial Intelligence in Science Education” and “STEM and teaching engineering design”. Interested authors are encouraged to explore these collections and contribute new articles that build upon the ongoing work within the collection. To read more of these collections, please click here .

Authors wishing to submit their manuscripts to a topical collection can indicate their intention via the Editorial Manager submission system. All submissions to a topical collection will undergo the same peer review process and standards. The Editors-in-Chief have the final discretions to choose and include articles in any collection.

Furthermore, RISE welcomes proposals for new topical collections that meet the following criteria:

1.      Relevance to RISE: The topic should have a solid foundation within RISE, as evidenced by a substantial number of previously published articles in RISE. These articles will be curated to form the initial core of the collection.

2.      Timeliness: The topic should focus on current and urgent issues in science education, demonstrating a strong potential to draw future contributions to the collection

Researchers interested in editing a topical collection are encouraged to contact the Editors-in-Chief.

Call for Papers: Science Education: Fit for the Future

Guest Editors: 

Peta White and Russell Tytler

Please email abstracts to [email protected] before you submit the full manuscripts online .  To read more, please click here

Abstracts should be 300 – 400 words making clear the nature of the contribution to new knowledge

Call for Papers: Special Issue: Enterpreneurial STEM Education

Guest Editors

James P. Davis (Queensland University of Technology)

Lyn English (Queensland University of Technology)

Feng-Kuang Chiang (Shanghai Jiaotong University)

To read more, please click  here

Journal information

• Astrophysics Data System (ADS)
• Current Contents/Social & Behavioral Sciences
• Google Scholar
• Norwegian Register for Scientific Journals and Series
• OCLC WorldCat Discovery Service
• Social Science Citation Index
• TD Net Discovery Service
• UGC-CARE List (India)

Rights and permissions

Springer policies

© Springer Nature B.V.

• Find a journal
• Publish with us
• Track your research

Read our research on: Gun Policy | International Conflict | Election 2024

Regions & Countries

6. teachers’ views on the state of public k-12 education.

Overall, teachers have a negative view of the U.S. K-12 education system – both the path it’s been on in recent years and what its future might hold.

The vast majority of teachers (82%) say that the overall state of public K-12 education has gotten worse in the last five years. Only 5% say it’s gotten better, and 11% say it has gotten neither better nor worse.

Looking to the future, 53% of teachers expect the state of public K-12 education to be worse five years from now. One-in-five say it will get better, and 16% expect it to be neither better nor worse.

We asked teachers who say the state of public K-12 education is worse now than it was five years ago how much each of the following has contributed:

• The current political climate (60% of teachers say this is a major reason that the state of K-12 education has gotten worse)
• The lasting effects of the COVID-19 pandemic (57%)
• Changes in the availability of funding and resources (46%)

Elementary school teachers are especially likely to point to resource issues – 54% say changes in the availability of funding and resources is a major reason the K-12 education system is worse now. By comparison, 41% of middle school and 39% of high school teachers say the same.

Differences by party

Overall, teachers who are Democrats and Democratic-leaning independents are as likely as Republican and Republican-leaning teachers to say that the state of public K-12 education is worse than it was five years ago.

But Democratic teachers are more likely than Republican teachers to point to the current political climate (65% vs. 54%) and changes in the availability of funding and resources (50% vs. 40%) as major reasons.

Democratic and Republican teachers are equally likely to say that lasting effects of the pandemic are a major reason that the public K-12 education is worse than it was five years ago (57% each).

K-12 education and political parties

We asked teachers which political party they trust to do a better job on various aspects of public K-12 education.

Across each of the issues we asked about, roughly a third or more of teachers say they don’t trust either party to do a better job. In particular, a sizable share (42%) trust neither party when it comes to shaping the school curriculum.

On balance, more teachers say they trust the Democratic Party to do a better job handling the things we asked about than say they trust the Republican Party.

About a third of teachers say they trust the Democratic Party to do a better job in ensuring adequate funding for schools, adequate pay and benefits for teachers, and equal access to high quality K-12 education for students. Only about one-in-ten teachers say they trust the Republican Party to do a better job in these areas.

A quarter of teachers say they trust the Democratic Party to do a better job in shaping the school curriculum and making schools safer; 11% and 16% of teachers, respectively, say they trust the Republican Party in these areas.

Across all the items we asked about, shares ranging from 15% to 17% say they are not sure which party they trust more, and shares ranging from 4% to 7% say they trust both parties equally.

A majority of public K-12 teachers (58%) identify with or lean toward the Democratic Party. About a third (35%) identify with or lean toward the GOP.

For each aspect of the education system we asked about, both Democratic and Republican teachers are more likely to say they trust their own party to do a better job than to say they trust the other party.

However, across most of these areas, Republican teachers are more likely to say they trust neither party than to say they trust their own party.

For example, about four-in-ten Republican teachers say they trust neither party when it comes to ensuring adequate funding for schools and equal access to high quality K-12 education for students. Only about a quarter of Republican teachers say they trust their own party on these issues.

The noteworthy exception is making schools safer, where similar shares of Republican teachers trust their own party (41%) and neither party (35%) to do a better job.

Social Trends Monthly Newsletter

Sign up to to receive a monthly digest of the Center's latest research on the attitudes and behaviors of Americans in key realms of daily life

Report Materials

Table of contents, ‘back to school’ means anytime from late july to after labor day, depending on where in the u.s. you live, among many u.s. children, reading for fun has become less common, federal data shows, most european students learn english in school, for u.s. teens today, summer means more schooling and less leisure time than in the past, about one-in-six u.s. teachers work second jobs – and not just in the summer, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

Apr 11, 2024

The Power of Citizen Science

• Community Outreach
• Marine Life
• Oceanography
• Polar Science

New research by Scripps Institution of Oceanography at UC San Diego and Reef Environmental Education Foundation ( REEF ) has found that citizen science initiatives could be one of the keys to unlocking crucial insights into ecological trends.

Citizen science projects facilitate collaboration between scientific researchers and the general public with the goal of collecting data more efficiently and furthering research in ways not possible without the help of the public.

In a recent  study led by Scripps Oceanography marine biologist  Brice Semmens and REEF research scientist Dan Greenberg, their team evaluated the effectiveness of citizen science data compared to structured survey data in monitoring population trends of coral reef fishes in Key Largo, Fla. over the span of 25 years. Their findings were published in the journal  Conservation Letters .

The team analyzed citizen science scuba diver observations made through the  REEF Volunteer Fish Survey Project and a federally-funded fish population survey led by NOAA to determine the level of correlation between the two methods. 

The REEF Volunteer Fish Survey Project, ongoing since 1993, allows volunteer scuba divers and snorkelers to collect and report information on marine fish populations, as well as selected invertebrate and algae species in marine waters world-wide. The data collected are housed in a  publicly-accessible database on REEF’s website and allow scientists and resource managers to better understand and protect ocean ecosystems. 

The study authors said the state of biodiversity worldwide has long been shrouded in mystery, primarily due to the lack of comprehensive, long-term population monitoring data. Their study presents compelling evidence that citizen science programs have the potential to address the global data crisis surrounding biodiversity monitoring.

"The large majority of species, such as groupers and snappers, were highly similar between population time series," said Semmens. "Our findings clearly indicate that citizen scientists can indeed serve as effective sentinels of ecological change."

The study also revealed variations in survey similarity across different taxonomic and trait-based groups, highlighting the need for careful consideration of methodological nuances. Despite these variances, the overall implication remains clear that citizen science has the potential to substantially augment traditional monitoring efforts, particularly for data-limited marine species, including groupers and snappers. 

"This research underscores the invaluable contributions that citizen scientists can make to our understanding of biodiversity," said Christy Pattengill-Semmens, a study co-author and co-director of REEF. "By engaging thousands of scuba divers in marine life observing and reporting, we have harnessed a vast network of observers to track ecological changes and inform marine conservation." 

The power of citizen science was highlighted in  another recent study, led by researchers at Stanford University and Scripps Oceanography. The team uncovered a genetic link between fluorescence and color in sea anemones, thanks in part to observations collected through the community platform  iNaturalist . This online social network empowers citizen scientists to document biodiversity information to help one another learn more about nature. The research team used iNaturalist to find specific locations of the sometimes rare neon-green sea anemones along the Pacific coast of North America. 

“Thanks to the dedication and efforts of citizen scientists, we can gain deeper insights into the population distributions of sea anemones, the gene pool of these organisms, and much more,” said Scripps marine biologist and senior author of the study Dimitri Deheyn. “Every observation, no matter how seemingly small or insignificant, plays a crucial role in expanding our knowledge and appreciation of the natural world.”

In honor of Citizen Science Month, observed throughout April, Scripps recognizes the different ways individuals can contribute to the collective effort to advance scientific research, discoveries and local actions. Below, learn more about other research projects at Scripps Oceanography that encourage citizen science participation. 

CoastSnap is a global project that helps monitor changing coastlines. No matter where you are located in the world, if you have a smartphone and an interest in the coast, you are welcome to participate in this research. CoastSnap originally started in Australia in 2017, and there are now several regional projects in the United States, including San Diego. The Scripps  Coastal Processes Group at the Center for Coastal Studies and then-Scripps Oceanography project scientist Julia Fielder, now a research scientist at the University of Hawaii Sea Level Center, helped launch the CoastSnap project in San Diego. 

Using a technique known as photogrammetry, CoastSnap gathers data by making it easy for anyone with a smartphone to capture and submit photos of different beach locations over time. These submitted photos are valuable coastal data that is helping researchers better understand how the coast is changing due to storms, sea level rise, human activities, and other factors. 

All CoastSnap station locations include a stainless steel phone cradle that overlooks a certain beach location. The general public is invited to use their phone to take a photo and share it to a centralized database via the free CoastSnap app or social media using a QR code and hashtag unique to each station. The technology behind CoastSnap can then create time-lapse videos that capture shoreline position and beach width as it evolves through time. There are currently five CoastSnap stations in San Diego, including one on the Scripps Institution of Oceanography campus on the corner of the observation deck, directly south of Scripps Pier. 

Tourists visiting the polar regions in Antarctica have the opportunity to contribute to research through the  FjordPhyto program, a NASA-funded citizen science project that was co-created by Scripps PhD candidate  Allison Cusick and biological oceanographer  Maria Vernet . FjordPhyto brings together scientists, tour operators, polar guides, and travelers to Antarctica to gather data on the community of phytoplankton species living within the fjords of Antarctica. 

The Antarctic Peninsula is one of the fastest warming regions in the world. As a result, melting glaciers bring an influx of freshwater and nutrients into the fjords potentially altering phytoplankton life in the ocean. 

Phytoplankton are microscopic, drifting plants that make up the base of the Antarctic food chain. They draw carbon dioxide out of the atmosphere and contribute to over half of Earth’s oxygen. 

Travelers on board the tour vessels help researchers understand more about what fuels the polar ecosystem by using tools, such as nets and a CTD (a device that measures conductivity, temperature, and depth) to collect seawater measurements and samples from glacier fjords. Back on board the vessels, volunteers are able to discover the invisible forest that is phytoplankton underneath a microscope. At the end of the season, these collected samples taken by citizen scientists make their way back to the  Vernet Lab at Scripps Oceanography to be analyzed by researchers.

SeadragonSearch

SeadragonSearch is a community-driven research initiative that increases understanding of wild seadragon populations. Greg Rouse is a marine biologist at Scripps Oceanography and one of the leaders of the  SeadragonSearch Project who helps gather data collected from the community to plan for the conservation of seadragons. There are currently only three known species of seadragons, so they remain relatively mysterious to scientists. Seadragons live in shallow algal habitats and are particularly vulnerable to climate change. 

This project uses artificial intelligence tools to identify individual seadragons from photos taken by community members and uploaded to the SeadragonSearch website. The resulting data about their lifespans and other traits will inform conservation policy for these fishes and their habitats.  

Once community members submit their photographs of seadragons, researchers are able to analyze the unique patterns on each seadragon’s face or body. A machine learning algorithm suggests possible matches to other photos in the system, and researchers review those matches and assign each dragon to an individual identity. As sightings of individuals are repeated, the fish can be tracked by a variety of parameters, including year, season, and location.

About Scripps Oceanography

Scripps Institution of Oceanography at the University of California San Diego is one of the world’s most important centers for global earth science research and education. In its second century of discovery, Scripps scientists work to understand and protect the planet, and investigate our oceans, Earth, and atmosphere to find solutions to our greatest environmental challenges. Scripps offers unparalleled education and training for the next generation of scientific and environmental leaders through its undergraduate, master’s and doctoral programs. The institution also operates a fleet of four oceanographic research vessels, and is home to Birch Aquarium at Scripps, the public exploration center that welcomes 500,000 visitors each year.

About UC San Diego

At the University of California San Diego, we embrace a culture of exploration and experimentation. Established in 1960, UC San Diego has been shaped by exceptional scholars who aren’t afraid to look deeper, challenge expectations and redefine conventional wisdom. As one of the top 15 research universities in the world, we are driving innovation and change to advance society, propel economic growth and make our world a better place. Learn more at ucsd.edu.

Related News

Using fecal transplants to treat dolphins with gastrointestinal disease, scripps student spotlight: flora coden, study illuminates the protective role of fluorescence in neon-colored sea anemones, sign up for explorations now.

explorations now is the free award-winning digital science magazine from Scripps Institution of Oceanography. Join subscribers from around the world and keep up on our cutting-edge research.