A review of integrating AI-based chatbots into flipped learning

New possibilities and challenges

Datos Bibliográficos

ID22166142
AutoresChung Kwan Lo (0000-0003-2305-9227, Education University of Hong Kong, autor de correspondencia), Khe Foon Hew (0000-0003-4149-533X, University of Hong Kong)
Año2023
Volumen8
Fecha de publicación2023-05-22
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Education (JOURNAL)
Identificadores de la revistaISSN: 2504-284X • E-ISSN: 2504-284X
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2023.1175715
OpenAlexW4377294106
IdiomaEN
Citas recibidas12
Referencias citadas24

This mini review examines the emerging concept of integrating AI-based chatbots into flipped learning and its potential to enhance students’ learning experience. We investigate the design and practice of chatbot-supported flipped learning, as well as the benefits and challenges associated with this approach. Despite an extensive database search, only 10 empirical articles were found, indicating that this cutting-edge research topic requires further exploration. The findings of this review suggest that this emerging instructional approach could result in benefits such as increased student interaction with learning content, improved class preparation, and data-driven teaching and learning. However, potential challenges included limited technical functionality, lacking authenticity, and insufficient student motivation. The review offers insights into future research and development to advance the knowledge and practice of integrating AI chatbots into flipped learning

Chatbot · Data science · Flipped Classroom · Flipped learning · Knowledge management · Mathematics education · Computer Science · E-Learning and Knowledge Management · Innovative Teaching Methods · Online Learning and Analytics · Psychology · Artificial Intelligence