Students’ Holistic Reading of Socio-Scientific Texts on Climate Change in a ChatGPT Scenario

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.