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Published on: February 23, 2024
Artificial Intelligence (AI)-driven dental education: Exploring the role of chatbots in a clinical learning
Qiao Fang1, Raphael Reynaldi2, Ardelia Shaula Araminta2
1Clinical Assistant Professor, Department of Restorative Dentistry, College of Dentistry, University of Illinois Chicago, Chicago, Ill.
Statement Of Problem:
Despite their widespread use in various educational contexts, the integration of chatbots into dental clinical education has not been thoroughly investigated. The noted discrepancy signifies a lack of understanding of how chatbots could enhance the personalized and interactive learning experiences of predoctoral dental students.
Purpose:
The purpose of this study was to evaluate the awareness and perceptions of artificial intelligence (AI) technology, interaction experiences, and concerns about a custom-developed chatbot (CB) intervention in the clinical education of predoctoral dental students at the University of Illinois Chicago, College of Dentistry (UIC-COD) compared with the traditional Blackboard (BB) online platform.
Material And Methods:
Eligible participants (n=86) providing verbal consent were allocated via the random block method into BB (n=43) and CB (n=43) groups and asked to engage with their designated platforms for 10 to 15 minutes by focusing on clinical inquiries in a predoctoral implant clinic and supported by a list of 35 typical questions. After the interaction, participants responded on a 5-point Likert scale to a 19-item survey probing AI awareness, platform engagement, and technological concerns. Survey data were anonymized and analyzed using descriptive, inferential statistics and nonparametric Mann-Whitney U tests to compare interventions. The Bonferroni correction for multiple comparisons was performed (α=.0045).
Results:
Neither the BB or CB group showed any difference in their awareness and perception of AI technology. The CB group demonstrated improved timeliness (P<.001), more interaction (P<.001), reduced faculty workload (P=.001), enhanced receptiveness (P=.002), and less anxiety (P<.001) and was more satisfied (P<.001) when compared with the BB group. However, concerns regarding the potential for incorrect information (P=.003) were more pronounced in the CB group.
Conclusions:
The integration of chatbot technology into dental clinical education significantly enhanced learning and student engagement, highlighting the potential for future technological enrichment of the educational landscape.
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