The features of visual models generated by primary school students in an online learning platform

Jina Chang, Jisun Park, Hye Gyoung Yoon, Joonhyeong Park, Minsu Ha

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this study is to identify the features of student-generated visual models in an online learning platform. To this end, online-based learning activities were designed and applied to 123 primary school students. Specifically, the students were guided to generate visual models for three phenomena related to light and shadow, following three steps: (1) observing a phenomenon in a video and constructing the first visual model of the phenomenon, (2) evaluating two different models in a concept cartoon and choosing the better model, and (3) observing another similar phenomenon and constructing the second model. Six visual models per student (738 visual models in total) were collected and analysed in terms of using proper symbols and conceptual understanding. In using symbols to visualise how light travels, students were found to employ increasingly higher levels of symbols over the course of constructing the six visual models. In terms of conceptual understanding, students demonstrated their conceptual development in the visual models they used to explain simple phenomena; however, for complex phenomena, the development of the conceptual levels of their models was challenged. Based on the above results, educational implications are discussed in terms of fostering students’ visual models in an online environment.

Original languageEnglish
JournalInternational Journal of Science Education
DOIs
StateAccepted/In press - 2025

Bibliographical note

Publisher Copyright:
© 2025 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • online learning platform
  • representation
  • Visual model

Fingerprint

Dive into the research topics of 'The features of visual models generated by primary school students in an online learning platform'. Together they form a unique fingerprint.

Cite this