Chen-Chung Liu, Wan-Jun Chen, Fang-ying Lo, Chia-Hui Chang, Hung-Ming Lin
{"title":"Teachable Q&A Agent: The Effect of Chatbot Training by Students on Reading Interest and Engagement","authors":"Chen-Chung Liu, Wan-Jun Chen, Fang-ying Lo, Chia-Hui Chang, Hung-Ming Lin","doi":"10.1177/07356331241236467","DOIUrl":null,"url":null,"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.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"2011 1","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Educational Computing Research","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1177/07356331241236467","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The goal of this Journal is to provide an international scholarly publication forum for peer-reviewed interdisciplinary research into the applications, effects, and implications of computer-based education. The Journal features articles useful for practitioners and theorists alike. The terms "education" and "computing" are viewed broadly. “Education” refers to the use of computer-based technologies at all levels of the formal education system, business and industry, home-schooling, lifelong learning, and unintentional learning environments. “Computing” refers to all forms of computer applications and innovations - both hardware and software. For example, this could range from mobile and ubiquitous computing to immersive 3D simulations and games to computing-enhanced virtual learning environments.