Interacting with Educational Chatbots: A Systematic Review

Autor/inn/en	Kuhail, Mohammad Amin; Alturki, Nazik; Alramlawi, Salwa; Alhejori, Kholood
Titel	Interacting with Educational Chatbots: A Systematic Review
Quelle	In: Education and Information Technologies, 28 (2023) 1, S.973-1018 (46 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-022-11177-3
Schlagwörter	Educational Technology; Computer Mediated Communication; Artificial Intelligence; Technology Uses in Education; Interaction; Web Sites; Handheld Devices; Computers; Computer Assisted Instruction; Intelligent Tutoring Systems; Design; Individualized Instruction; Experiential Learning; Cooperative Learning; Feedback (Response); Peer Teaching; Scaffolding (Teaching Technique); Instructional Effectiveness + Suchen Sie Ihr Suchwort? Unterrichtsmedien; Computerkonferenz; Künstliche Intelligenz; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Interaktion; Web-Design; Digitalrechner; Computer based training; Computerunterstützter Unterricht; Intelligentes Tutorsystem; Individualisierender Unterricht; Experiental learning; Erfahrungsorientiertes Lernen; Kooperatives Lernen; Peer group teaching; Peer Group Teaching; Unterrichtserfolg
Abstract	Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners' behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to students' learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01