Using a Chatbot to Provide Formative Feedback: A Longitudinal Study of Intrinsic Motivation, Cognitive Load, and Learning Performance

  • Jiaqi Yin
  • , Tiong Thye Goh
  • , Yi Hu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

This study aimed to examine sustainable effects of chatbot-based formative feedback on intrinsic motivation, cognitive load, and learning performance. A longitudinal quasi-experimental design with 173 undergraduate students was conducted. The experiment is a between-subject design. Students either received formative feedback from a chatbot or a teacher. Utilizing linear mixed model and t-test for data analysis, results showed the following. First, chatbot-based feedback resulted in increased learning interest, perceived choice, and value while decreasing perceived pressure over time. Second, chatbot-based feedback was effective in reducing cognitive load, particularly when learning contents involved conceptual or difficult knowledge. Finally, chatbot-based feedback was found to be more efficient and effective in supporting the mastery of application-based knowledge compared with teacher-based feedback. This study has practical implications for the design of chatbots, and it also enriches the methods of providing ongoing formative feedback in large-scale classrooms.

Original languageEnglish
Pages (from-to)1404-1415
Number of pages12
JournalIEEE Transactions on Learning Technologies
Volume17
DOIs
StatePublished - 2024

Keywords

  • Chatbot
  • cognitive load
  • formative feedback
  • intrinsic motivation
  • learning performance

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