{"title":"Students’ Holistic Reading of Socio-Scientific Texts on Climate Change in a ChatGPT Scenario","authors":"Kason Ka Ching Cheung, Jack K. H. Pun, Wangyin Li","doi":"10.1007/s11165-024-10177-2","DOIUrl":null,"url":null,"abstract":"<p>ChatGPT becomes a prominent tool for students’ learning of science when students <i>read</i> its scientific texts. Students read to learn about climate change misinformation using ChatGPT, while they develop critical awareness of the content, linguistic features as well as nature of AI and science to comprehend these texts. In this exploratory study, we investigated students’ reading performance in comprehending two ChatGPT-generated socio-scientific texts, with one focusing on cognitive-epistemic aspects of climate science and another one focusing on social-institutional aspects of climate science. We theorized such reading of ChatGPT-generated outputs as encompassing the content-interpretation, genre-reasoning and epistemic-evaluation domains. Combining Rasch partial-credit model and qualitative analysis, we explored and investigated how a total of 117 junior secondary students (grades 8 to 9) read such texts. Moreover, we also examined how 55 students’ holistic reading of socio-scientific texts on climate change in a ChatGPT scenario changes after a reading-science intervention. Our findings indicate that the content-interpretation was the easiest while the epistemic-evaluation domains were the most difficult. Interestingly, after the reading-science intervention, many students developed their tentative view on nature of science when they evaluated ChatGPT’s claims; while a small increase in number of students discussed reliability and non-epistemic nature of AI when they evaluated ChatGPT’s claims in relation to climate change. The findings also drive a pedagogical model that improves students’ holistic reading of socio-scientific texts generated by ChatGPT.</p>","PeriodicalId":47988,"journal":{"name":"Research in Science Education","volume":"20 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in Science Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1007/s11165-024-10177-2","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
ChatGPT becomes a prominent tool for students’ learning of science when students read its scientific texts. Students read to learn about climate change misinformation using ChatGPT, while they develop critical awareness of the content, linguistic features as well as nature of AI and science to comprehend these texts. In this exploratory study, we investigated students’ reading performance in comprehending two ChatGPT-generated socio-scientific texts, with one focusing on cognitive-epistemic aspects of climate science and another one focusing on social-institutional aspects of climate science. We theorized such reading of ChatGPT-generated outputs as encompassing the content-interpretation, genre-reasoning and epistemic-evaluation domains. Combining Rasch partial-credit model and qualitative analysis, we explored and investigated how a total of 117 junior secondary students (grades 8 to 9) read such texts. Moreover, we also examined how 55 students’ holistic reading of socio-scientific texts on climate change in a ChatGPT scenario changes after a reading-science intervention. Our findings indicate that the content-interpretation was the easiest while the epistemic-evaluation domains were the most difficult. Interestingly, after the reading-science intervention, many students developed their tentative view on nature of science when they evaluated ChatGPT’s claims; while a small increase in number of students discussed reliability and non-epistemic nature of AI when they evaluated ChatGPT’s claims in relation to climate change. The findings also drive a pedagogical model that improves students’ holistic reading of socio-scientific texts generated by ChatGPT.
期刊介绍：
2020 Five-Year Impact Factor: 4.021
2020 Impact Factor: 5.439
Ranking: 107/1319 (Education) – Scopus
2020 CiteScore 34.7 – Scopus
Research in Science Education (RISE ) is highly regarded and widely recognised as a leading international journal for the promotion of scholarly science education research that is of interest to a wide readership.
RISE publishes scholarly work that promotes science education research in all contexts and at all levels of education. This intention is aligned with the goals of Australasian Science Education Research Association (ASERA), the association connected with the journal.
You should consider submitting your manscript to RISE if your research:
Examines contexts such as early childhood, primary, secondary, tertiary, workplace, and informal learning as they relate to science education; and
Advances our knowledge in science education research rather than reproducing what we already know.
RISE will consider scholarly works that explore areas such as STEM, health, environment, cognitive science, neuroscience, psychology and higher education where science education is forefronted.
The scholarly works of interest published within RISE reflect and speak to a diversity of opinions, approaches and contexts. Additionally, the journal’s editorial team welcomes a diversity of form in relation to science education-focused submissions. With this in mind, RISE seeks to publish empirical research papers.
Empircal contributions are:
Theoretically or conceptually grounded;
Relevant to science education theory and practice;
Highlight limitations of the study; and
Identify possible future research opportunities.
From time to time, we commission independent reviewers to undertake book reviews of recent monographs, edited collections and/or textbooks.
Before you submit your manuscript to RISE, please consider the following checklist. Your paper is:
No longer than 6000 words, including references.
Sufficiently proof read to ensure strong grammar, syntax, coherence and good readability;
Explicitly stating the significant and/or innovative contribution to the body of knowledge in your field in science education;
Internationalised in the sense that your work has relevance beyond your context to a broader audience; and
Making a contribution to the ongoing conversation by engaging substantively with prior research published in RISE.
While we encourage authors to submit papers to a maximum length of 6000 words, in rare cases where the authors make a persuasive case that a work makes a highly significant original contribution to knowledge in science education, the editors may choose to publish longer works.
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