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Exploring Students’ Multimodal Representations of Ideas About Epistemic Reading of Scientific Texts in Generative AI Tools

  • Kason Ka Ching Cheung
  • , Jack Pun*
  • , Wangyin Kenneth-Li
  • , Jiayi Mai
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

20 Downloads (CityUHK Scholars)

Abstract

As students read scientific texts created in generative artificial intelligence (GenAI) tools, they need to draw on their epistemic knowledge of GenAI as well as that of science. However, only a few research discussed multimodality as a methodological approach in characterising students’ ideas of GenAI-science epistemic reading. This study qualitatively explored 44 eighth and ninth graders’ multimodal representations of ideas about GenAI-science epistemic reading and developed an analyti- cal framework based on Lemke’s (1998) typology of representational meaning, namely presentational, organisational, and orientational meanings. Under each representational meaning, several categories were inductively generated while students expressed preferences in using drawn, written, or both drawn and written mode to express certain categories. Findings indi- cate that a multimodal approach is fruitful in characterising students’ semiotic resources in meaning-making of ideas about GenAI-science epistemic reading. We suggested implications regarding future intervention studies on tracking students’ ideas about GenAI-science epistemic reading using the analytical framework developed in this study. © The Author(s) 2024
Original languageEnglish
Pages (from-to)284-297
JournalJournal of Science Education and Technology
Volume34
Issue number2
Online published5 Dec 2024
DOIs
Publication statusPublished - Apr 2025

Funding

Open access publishing enabled by City University of Hong Kong Library's agreement with Springer Nature. The study reported in this manuscript is based upon work supported by the Quality Education Fund, Hong Kong SAR Government (Grant Number: 9420033).

Research Keywords

  • Generative artifcial intelligence
  • Nature of science
  • Nature of GenAI
  • Multimodality

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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