Artificial Intelligence (AI)-driven dental education: Exploring the role of chatbots in a clinical learning environment

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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