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The effect of using a chatbot integrated with the ARCS motivation model in physiology education: a mixed-methods
Yasin Ali Cimen1, Gunes Bolatli2
1Department of Physiology, Faculty of Medicine, Yalova University, Yalova, Türkiye.
Introduction:
This study examined the effects of integrating the ARCS (Attention, Relevance, Confidence, and Satisfaction) Model of Motivational Design with an AI-supported chatbot on academic achievement and learner perceptions in physiology education.
Methods:
The study was conducted with 75 students enrolled in university-level physiology courses. The control group (Traditional) received instruction using traditional teaching methods, while the teaching process for the second group (ARCS) was structured according to the ARCS model. The third group used a chatbot-supported learning environment in addition to the ARCS model (ARCS +Chatbot). Academic achievement and cognitive load were assessed using pretest and post-test measurements in all groups, while technology acceptance was measured only in the ARCS+Chatbot group using the Technology Acceptance Model (TAM) before and after implementation. Additionally, to examine the chatbot-supported learning experience in greater depth, a semi-structured interview form was administered to students in this group, and the data were analyzed using thematic analysis.
Results:
Quantitative findings indicated that academic achievement increased significantly across all groups from the pre-test to the post-test (p<.001). However, the increase in achievement differed across groups, with the ARCS+Chatbot group performing significantly better than both the traditional instruction group (p<.001) and the ARCS group (p<.01) on the posttest. In contrast, no significant differences were found in pre-test and post-test measurements of cognitive load or in between-group comparisons (p>.05). TAM analyses revealed that chatbot use significantly increased perceived usefulness (p<.05) but did not result in a significant change in perceived ease of use (p>.05). Qualitative findings indicated that students tend to perceive the chatbot as a tool that supports their learning process and complements the instructor's role.
Discussion:
The integration of an AI-supported chatbot into the ARCS model improved academic achievement without increasing cognitive load, suggesting its potential as an effective instructional approach in physiology education.