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 analytical 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 indicate 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. Copyright © 2024 The Author(s).
Original language | English |
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Journal | Journal of Science Education and Technology |
Early online date | Dec 2024 |
DOIs | |
Publication status | E-pub ahead of print - Dec 2024 |
Citation
Cheung, K. K. C., Pun, J., Kenneth‑Li, W., & Mai, J. (2024). Exploring students’ multimodal representations of ideas about epistemic reading of scientific texts in generative AI tools. Journal of Science Education and Technology. Advance online publication. https://doi.org/10.1007/s10956-024-10182-0Keywords
- Generative artifcial intelligence
- Nature of science
- Nature of GenAI
- Multimodality