Source of Publication
Education and Information Technologies
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.
Springer Science and Business Media LLC
Chatbot, Conversational Agent, Educational Bot, Human-Computer Interaction, Interaction Styles, Literature Review
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Kuhail, Mohammad Amin; Alturki, Nazik; Alramlawi, Salwa; and Alhejori, Kholood, "Interacting with educational chatbots: A systematic review" (2022). All Works. 5208.
Indexed in Scopus
Open Access Type
Hybrid: This publication is openly available in a subscription-based journal/series