Teachable Q&A Agent: The Effect of Chatbot Training by Students on Reading Interest and Engagement

Chen Chung Liu, Wan Jun Chen, Fang Ying Lo, Chia Hui Chang, Hung Ming Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Reading requires appropriate strategies to spark initial interest and sustain engagement. One promising strategy is the pedagogical approach of learning-by-teaching, transforming learners into active participants. Integrating this approach into digitalized and individualized reading contexts has the potential to foster the development of young readers. Currently, AI techniques are primarily used in chatbots as tutors, with limited focus on tutee chatbots that employ the learning-by-teaching pedagogy. Therefore, this study adopted a teachable Q&A agent and probed into the effect of chatbot training, employing AI techniques and utilizing student-generated questions and answers, with the aim of enhancing students’ reading interest and engagement. Ninety-five fifth graders participated in a 9-week reading program. A quasi-experimental design was conducted. The results proved that incorporating a learning-by-teaching approach into the chatbot training activity significantly enhanced their reading interest and engagement. However, the quantity of certain question types is negatively correlated with interest and engagement. This implies that asking diverse questions poses a certain level of challenge to young readers, which requires deliberate training and incubation. Additionally, the identification of four distinct student clusters exhibited the affordances and limitations of tutee chatbots for reading.

Original languageEnglish
Pages (from-to)1122-1154
Number of pages33
JournalJournal of Educational Computing Research
Volume62
Issue number4
DOIs
StatePublished - Jul 2024

Keywords

  • chatbot
  • engagement
  • flow
  • learning by teaching
  • reading interest

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