Assessment of students’ feedback behavior in agame-based automated feedback system: A cross-cultural replication study
2022 (English)In: Proceedings of the 30th International Conference on Computers in Education / [ed] Sridhar Iyer, Ju-Ling Shih, Weiqin Chen, Mas Nida MD Khambari, Mouna Denden, Rwitajit Majumbar, Liliana Cuesta Medina, Shitanshu Mishra, Sahana Murthy, Patcharin Panjaburee, Daner Sun, Kuala Lumpur, Malaysia, 2022, p. 292-301Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, we argue for the importance of conducting replication studies over various schools and countries when addressing topics about learning and instruction and propose educational technology to be a tool for this endeavor. We present an example of a cross-cultural replication study that makes use of educational technology in the form of a digital game-based automated feedback system. The study addresses feedback related behavior in 11-15-year-old students in US and Swedish classrooms, investigating students' choices to seek confirmatory (i.e., positive) or critical (i.e., negative) feedback, as well as their subsequent choices to revise their work based on this feedback. Comparisons of the data collected at several schools in the US and Sweden showed similar patterns of relationships among students' feedback-seeking behavior, their tendency to revise their work, and their learning outcomes in and outside the assessment environment. Overall, the findings revealed that this assessment approach seems to be generalizable from a North American to a European population. However, the findings showed both a significant difference between Sweden and the US regarding the preference for critical feedback and between different schools within each country. Thus, it is possible that the difference between countries reflects school differences rather than cultural differences.
Place, publisher, year, edition, pages
Kuala Lumpur, Malaysia, 2022. p. 292-301
Keywords [en]
assessment, cross-cultural replication study, educational technology, feedback, self-regulated learning
National Category
Human Computer Interaction Learning
Identifiers
URN: urn:nbn:se:liu:diva-198193ISBN: 9789869721493 (electronic)OAI: oai:DiVA.org:liu-198193DiVA, id: diva2:1801084
Conference
30th International Conference on Computers in Education, ICCE 2022, Kuala Lumpur, Malaysia, 28 Nov - 2 Dec, 2022
2023-09-292023-09-292023-10-04Bibliographically approved