TY - JOUR
T1 - Chatbot’s Complementary Motivation Support in Developing Study Plan of E-Learning English Lecture
AU - Ryong, Kyungjin
AU - Lee, Daeho
AU - Lee, Jae gil
N1 - Publisher Copyright:
© 2023 Taylor & Francis Group, LLC.
PY - 2024
Y1 - 2024
N2 - The present study investigates the effects of a chatbot’s motivation support style on the learner’s experience and intention to continue the study in the context of online English lectures. Seventy-nine undergraduate students were recruited from a large private university in Seoul, South Korea, and assigned to one of three learning plan development groups: develop a plan alone, autonomy support (i.e., a chatbot stimulating intrinsic motivation), or control support (i.e., a chatbot promoting extrinsic motivation) groups. The learners were classified into two groups based on their learning motivation types (i.e., intrinsic and extrinsic), and by doing so, the present study created a chatbot’s matched and non-matched motivation support conditions in learning plan development. The two support strategies were compared with a control condition (i.e., learners’ own plan making), and the results suggest that a chatbot with a non-matched motivation strategy increases learner self-efficacy, enjoyment, and intention to continue using the lecture. Furthermore, the study also explores the moderation effect of learning motivation types, and reveals that a chatbot’s control support significantly improves the learning experience. The present study provides new insight into improving user evaluation by strategically differentiating a chatbot’s conversational style and a user’s characteristics.
AB - The present study investigates the effects of a chatbot’s motivation support style on the learner’s experience and intention to continue the study in the context of online English lectures. Seventy-nine undergraduate students were recruited from a large private university in Seoul, South Korea, and assigned to one of three learning plan development groups: develop a plan alone, autonomy support (i.e., a chatbot stimulating intrinsic motivation), or control support (i.e., a chatbot promoting extrinsic motivation) groups. The learners were classified into two groups based on their learning motivation types (i.e., intrinsic and extrinsic), and by doing so, the present study created a chatbot’s matched and non-matched motivation support conditions in learning plan development. The two support strategies were compared with a control condition (i.e., learners’ own plan making), and the results suggest that a chatbot with a non-matched motivation strategy increases learner self-efficacy, enjoyment, and intention to continue using the lecture. Furthermore, the study also explores the moderation effect of learning motivation types, and reveals that a chatbot’s control support significantly improves the learning experience. The present study provides new insight into improving user evaluation by strategically differentiating a chatbot’s conversational style and a user’s characteristics.
UR - https://www.scopus.com/pages/publications/85146733413
U2 - 10.1080/10447318.2022.2163786
DO - 10.1080/10447318.2022.2163786
M3 - Article
AN - SCOPUS:85146733413
SN - 1044-7318
VL - 40
SP - 2641
EP - 2655
JO - International Journal of Human-Computer Interaction
JF - International Journal of Human-Computer Interaction
IS - 10
ER -