• Journal of Korean Academy of Dental Administration
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• v.5 no.1
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• pp.22-30
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• 2017

Objective: The purpose is to study the factors to impact on the satisfaction of field practice among dental hygiene students and to provide the basic data for the quality improvement of the field practices for dental hygiene students. Methods: A self-reported questionnaires were filled out by 108 dental hygiene students in C city. Questionnaires were composed with the general characteristics, satisfaction to major, and satisfaction to field clinical practice. The data was analyzed by chi-square statistics using SPSS 20.0 program. Results: The higher satisfaction to communication with professor or seniors in department was associated with the higher satisfaction to field clinical practice (p<0.05). The higher satisfaction to field clinical practice hours per week was associated with the higher satisfaction to field clinical practice (p<0.05). The higher interest to major subjects and the satisfaction to the laboratory environment were associated with the higher satisfaction to field clinical practice (p<0.05). Conclusions: The higher satisfaction to major was associated with the higher satisfaction to field clinical practice. Therefore, the systematic curriculum development is needed to improve the satisfaction with major and clinical practice.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.