Artificial Intelligence (AI)-driven dental education: Exploring the role of chatbots in a clinical learning environment
Published:April 21, 2024DOI:https://doi.org/10.1016/j.prosdent.2024.03.038
Abstract
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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