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Students know more than they can tell: Understanding learners' ideas of heat transfer via model revision activities

  • Rajashri Priyadarshini*
  • , Chandan Dasgupta
  • , Sahana Murthy
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Students' preconceptions significantly influence learning as they bring prior experiences and ideas alongside formal knowledge. Considering only explicit or conscious conceptual models can misinform teachers' efforts. Framing the problem using both conscious (verbal-symbolic knowledge, conscious models) and unconscious (implicit models, core-intuitions) conceptual resources offer a powerful framework. This study interprets the ideas of heat transfer of two grade 11 students in depth (from a total N=9), through this framework. We look at how Nash and Payal use different conceptual resources to build an explanatory model of heat transfer in a cup through the model revision activities. We found different ideas of heat (heat as a substance, steam as unique property of heat) to be unconsciously influencing how students understand the concept. Harnessing core-intuitions into conscious models enabled Nash to build better explanatory models, whereas Payal extensively relied on her verbal-symbolic knowledge. In the macroscopic activities, both students tended to use their judgments from their sensory perceptions, going against their verbal-symbolic knowledge. Using the metacognitive prompts on Knowledge Forum also supported student's critical analysis about their ideas before uploading them on the forum.

Original languageEnglish
Title of host publication31st International Conference on Computers in Education, ICCE 2023 - Proceedings
EditorsJu-Ling Shih, Akihiro Kashihara, Weiqin Chen, Weiqin Chen, Hiroaki Ogata, Ryan Baker, Ben Chang, Seb Dianati, Jayakrishnan Madathil, Ahmed Mohamed Fahmy Yousef, Yuqin Yang, Hafed Zarzour
PublisherAsia-Pacific Society for Computers in Education
Pages244-249
Number of pages6
Volume1
ISBN (Electronic)9786269689019
DOIs
Publication statusPublished - Dec 2023
Externally publishedYes
Event31st International Conference on Computers in Education, ICCE 2023 - Matsue, Shimane, Japan
Duration: 4 Dec 20238 Dec 2023
Conference number: 31

Conference

Conference31st International Conference on Computers in Education, ICCE 2023
Abbreviated titleICCE 2023
Country/TerritoryJapan
CityMatsue, Shimane
Period4/12/238/12/23

Keywords

  • Conscious models
  • Explanatory models
  • Intuitive knowledge
  • Knowledge Forum
  • Perceptions
  • Representational levels
  • Unconscious models

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