ePoster
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Presentation Description
Michelle Mun1,2
Alastair Sloan1 and Samantha Byrne3
1 Melbourne Dental School, University of Melbourne, Melbourne, Australia
2 Centre for Digital Transformation of Health, University of Melbourne, Melbourne, Australia
3 Melbourne Dental School, The University of Melbourne
Alastair Sloan1 and Samantha Byrne3
1 Melbourne Dental School, University of Melbourne, Melbourne, Australia
2 Centre for Digital Transformation of Health, University of Melbourne, Melbourne, Australia
3 Melbourne Dental School, The University of Melbourne
Background:
The emergence of generative artificial intelligence (AI) systems, including large language models, has garnered significant attention in education and healthcare. Future dentists must be adaptable to changing healthcare landscapes, including AI integration. In dental education, simulation-based learning is grounded in experiential learning theory and has extensive support for use in skills acquisition (Gaba, 2004). Similarly, generative AI systems can be leveraged to create safe environments for learning about the use, benefits and limitations of AI in health education and clinical practice (Mohammad et al., 2023).
The emergence of generative artificial intelligence (AI) systems, including large language models, has garnered significant attention in education and healthcare. Future dentists must be adaptable to changing healthcare landscapes, including AI integration. In dental education, simulation-based learning is grounded in experiential learning theory and has extensive support for use in skills acquisition (Gaba, 2004). Similarly, generative AI systems can be leveraged to create safe environments for learning about the use, benefits and limitations of AI in health education and clinical practice (Mohammad et al., 2023).
Summary of work:
This project explores student perceptions of using large language models for writing assessments in dental education. First-year dental students are required to complete a 1000-word essay as part of their Population Oral Health subject. In 2023, the essay was designed to incorporate use of AI. Students were required to use the openly available generative AI system, ChatGPT, to formulate, critique, and edit an essay response to a given topic, using a provided rubric. The students were also asked to reflect on the utility and reliability of using AI for generating the essay. Contribution of their assessment submission to the study was voluntary.
This project explores student perceptions of using large language models for writing assessments in dental education. First-year dental students are required to complete a 1000-word essay as part of their Population Oral Health subject. In 2023, the essay was designed to incorporate use of AI. Students were required to use the openly available generative AI system, ChatGPT, to formulate, critique, and edit an essay response to a given topic, using a provided rubric. The students were also asked to reflect on the utility and reliability of using AI for generating the essay. Contribution of their assessment submission to the study was voluntary.
Results and Discussion:
Data collection is ongoing and includes transcription, manual coding and thematic analysis of qualitative data regarding student experience and perceptions of the use of ChatGPT. Key themes, discussion and conclusion resulting from the analysis will be presented at the conference.
Data collection is ongoing and includes transcription, manual coding and thematic analysis of qualitative data regarding student experience and perceptions of the use of ChatGPT. Key themes, discussion and conclusion resulting from the analysis will be presented at the conference.
Take-home messages:
In this project we seek to formalise knowledge about the effect of using generative AI systems on learning and assessment for preclinical dental students. This project addresses a gap in the literature regarding AI in health education and student perspectives of AI, and may inform the design and format of learning activities, assessments, guidelines and policy for using generative AI in health education assessment.
In this project we seek to formalise knowledge about the effect of using generative AI systems on learning and assessment for preclinical dental students. This project addresses a gap in the literature regarding AI in health education and student perspectives of AI, and may inform the design and format of learning activities, assessments, guidelines and policy for using generative AI in health education assessment.
References (maximum three)
Gaba, D. M. (2004) The future vision of simulation in health care. BMJ Quality & Safety, 13(1). https://doi.org/10.1136/qshc.2004.009878
Mohammad, B., Supti, T., Alzubaidi, M., Shah, H., Alam, T., Shah, Z. & Househ, M. (2023) The Pros and Cons of Using ChatGPT in Medical Education: A Scoping Review. Stud Health Technol Inform. 29;305:644-647. doi: 10.3233/SHTI230580.