A Study on PBL-based Innovative Healthcare Data Science Specialized Education
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In this paper, the author shares the process, performance, and implications of project-based learning (PBL) education in healthcare data science (HDS). Healthcare data science education team (HET) of Soonchunhyang university's project considered that the current healthcare education is greatly different from the rapidly changing healthcare 3.0 environment, and emphasized a PBL practice-oriented HDS program as an education model. PBL focused on self-directed learning experiences, practical analysis problems, and team-oriented training. By large, it was promoted with three specialized strategies: practical 'industry inside education', 'converged track training', and 'education to strengthen resilience and change response'. To compare the effects before and after of the PBL-driven HDS trainings, it was analyzed by dividing into user confidence, change in value perception, and change in the employment success ratio in the HDS field. Consequently, it was found that there was a significant enhancement in all areas. This course and results can be applied as cornerstone data for efficient big data analysis and data science education suitable for the other universities.
Abstract
In this paper, the author shares the process, performance, and implications of project-based learning (PBL) education in healthcare data science (HDS). Healthcare data science education team (HET) of Soonchunhyang university's project considered that the current healthcare education is greatly different from the rapidly changing healthcare 3.0 environment, and emphasized a PBL practice-oriented HDS program as an education model. PBL focused on self-directed learning experiences, practical analysis problems, and team-oriented training. By large, it was promoted with three specialized strategies: practical 'industry inside education', 'converged track training', and 'education to strengthen resilience and change response'. To compare the effects before and after of the PBL-driven HDS trainings, it was analyzed by dividing into user confidence, change in value perception, and change in the employment success ratio in the HDS field. Consequently, it was found that there was a significant enhancement in all areas. This course and results can be applied as cornerstone data for efficient big data analysis and data science education suitable for the other universities.
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