透過體驗學習與問題導向設計改善非數學統計背景學生抽象概念之學習成效--利用電腦模擬與資料視覺化學習統計推論
Other Title
Improve the Achievement of Abstract Concept for Students without Mathematics or Statistics Background through Experiential Learning and Problem-Based Learning Strategies -- Utilize Computer Simulation and Data Visualization to Learn Statistical Inference
Journal
教育部教學實踐研究計畫
Date Issued
2022
Author(s)
Abstract
The teaching field of this study is the course “Statistical Inference in Data Science.” This course is required for junior and senior students taking the Biostatistics and Health Informatics module in the Department of Public Health. The statistical inference will introduce the basic concepts and theories of statistical methods, and the contents are abstract mathematical and statistical theories. However, students have difficulty learning theories because of insufficient prior knowledge of mathematics. In addition, nowadays, students are digital natives. Their cognitive processing belongs to shallow thinking, and their learning styles have changed. As a result, they have difficulty understanding the abstract concepts of statistical theories, resulting in low learning effectiveness, weak motivation, and passive attitudes. To improve these problems and the plight of the teaching site, in this study, we adopted an action research method and utilized experiential learning with problem-based learning and information technology integrated into instruction. Students are guided to explore the role and importance of statistical theory from real-world data analysis and applications. We tried to connect the statistical theories and real-world data analysis.
Type
report
File(s)![Thumbnail Image]()
Loading...
Name
110_王彥雯_教學實踐研究計畫成果報告_20240930.pdf
Size
16.78 MB
Format
Adobe PDF
Checksum
(MD5):c63fac7c137c86b197901e6fc06a83e0