The Course Design of Basic Data Science Taking into Account Both Face-To-Face and On-Demand Teaching and Effect Analysis

• Published in: 2023 Pacific Neighborhood Consortium Annual Conference and Joint Meetings (PNC) pp. 61 - 67
• Main Authors: Zhang, Zhihua, Yamamoto, Toshiyuki
• Format: Conference Proceeding
• Language: English
• Published: Pacific Neighborhood Consortium 03.11.2023
• Subjects: data science education; effect comparison; on-demand lecture design
• DOI: 10.23919/PNC58718.2023.10314978

We have conducted research on the construction of educational curricula and proposed a stage-wised refinement curriculum model for data science education at liberal arts universities. The model consists of four stages: Data Science Invitation, Data Science Basics, Data Science Practice, and Data Science Development. Based on this model, we have developed educational subjects related to the three knowledge areas, implemented them in our university's data science education program, and are conducting educational practice. In this paper, we focus on the subject of "Data Science" in Area II that we oversaw in the second half of 2022, and report on syllabus design, content creation, implementation status, and evaluation of its on-demand implementation. The researchers conducted both face-to-face and on-demand classes for proven that the content of the course is effective.