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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Empowering Future Dentists: A Comprehensive Mixed-Methods Exploration of Artificial Intelligence in Personalizing
1Faculty of Dentistry, SEGi University, Petaling Jaya, Malaysia.
Purpose/Objectives:
Dental education often struggles to bridge the gap between theoretical knowledge and clinical application. Traditional teaching methods may fail to meet individual learning needs, potentially impacting student performance and confidence. Artificial intelligence (AI)-driven platforms like Gemini offer personalized learning pathways and real-time feedback, which could enhance educational outcomes. This study investigates the integration of Gemini to personalize Year 3 dental students' learning experience. The study assesses its impact on formative and summative assessments, as well as the experiences of students and faculty.
Methods:
An explanatory sequential mixed-methods design was used, involving 46 Year 3 BDS students and six faculty members. Quantitative data were collected through pre- and post-implementation assessments, while semi-structured interviews provided qualitative insights into user experiences.
Results:
Quantitative analysis revealed a 15% mean increase in formative assessment scores post-Gemini integration (p < 0.05, Cohen's d = 0.7), with the largest observed gains in modified essay questions (MEQs). Summative assessments showed a 5% increase, though this difference was not statistically significant (p = 0.08, Cohen's d = 0.3). A strong positive correlation (r = 0.62; p < 0.01) was found between Gemini usage and student performance. Thematic analysis of interview data identified key themes, including initial technical challenges, increased student engagement, the value of personalized feedback, and suggestions for expanding the platform's use to other modules.
Conclusion:
Formative assessment gains were statistically significant (p < 0.05), reinforcing the effectiveness of AI-driven adaptive learning. However, the 5% increase in summative assessments was not statistically significant (p = 0.08), suggesting that AI platforms alone may not fully address the demands of high-stakes evaluations. This underscores the need for complementary educational strategies, such as simulation-based learning and structured clinical discussions. The study highlights the importance of thorough faculty training for the effective integration of AI tools. Gemini demonstrated potential in enhancing formative learning and student engagement, indicating its broader applicability in dental education.
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