TY - JOUR
T1 - Using a Chatbot to Provide Formative Feedback
T2 - A Longitudinal Study of Intrinsic Motivation, Cognitive Load, and Learning Performance
AU - Yin, Jiaqi
AU - Goh, Tiong Thye
AU - Hu, Yi
N1 - Publisher Copyright:
© 2008-2011 IEEE.
PY - 2024
Y1 - 2024
N2 - This study aimed to examine sustainable effects of chatbot-based formative feedback on intrinsic motivation, cognitive load, and learning performance. A longitudinal quasi-experimental design with 173 undergraduate students was conducted. The experiment is a between-subject design. Students either received formative feedback from a chatbot or a teacher. Utilizing linear mixed model and t-test for data analysis, results showed the following. First, chatbot-based feedback resulted in increased learning interest, perceived choice, and value while decreasing perceived pressure over time. Second, chatbot-based feedback was effective in reducing cognitive load, particularly when learning contents involved conceptual or difficult knowledge. Finally, chatbot-based feedback was found to be more efficient and effective in supporting the mastery of application-based knowledge compared with teacher-based feedback. This study has practical implications for the design of chatbots, and it also enriches the methods of providing ongoing formative feedback in large-scale classrooms.
AB - This study aimed to examine sustainable effects of chatbot-based formative feedback on intrinsic motivation, cognitive load, and learning performance. A longitudinal quasi-experimental design with 173 undergraduate students was conducted. The experiment is a between-subject design. Students either received formative feedback from a chatbot or a teacher. Utilizing linear mixed model and t-test for data analysis, results showed the following. First, chatbot-based feedback resulted in increased learning interest, perceived choice, and value while decreasing perceived pressure over time. Second, chatbot-based feedback was effective in reducing cognitive load, particularly when learning contents involved conceptual or difficult knowledge. Finally, chatbot-based feedback was found to be more efficient and effective in supporting the mastery of application-based knowledge compared with teacher-based feedback. This study has practical implications for the design of chatbots, and it also enriches the methods of providing ongoing formative feedback in large-scale classrooms.
KW - Chatbot
KW - cognitive load
KW - formative feedback
KW - intrinsic motivation
KW - learning performance
UR - https://www.scopus.com/pages/publications/85187309254
U2 - 10.1109/TLT.2024.3364015
DO - 10.1109/TLT.2024.3364015
M3 - 文章
AN - SCOPUS:85187309254
SN - 1939-1382
VL - 17
SP - 1404
EP - 1415
JO - IEEE Transactions on Learning Technologies
JF - IEEE Transactions on Learning Technologies
ER -