教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
115-1	366002	校務研究	1	2.0	2	★	傅遠智	技職所	3	0

教學大綱與進度：

教師姓名	傅遠智　教師諮商時間(Office Hours)
Email	fuyc20@gmail.com
最後更新時間	2026-06-05 10:48:14
課程大綱	The mission of Institutional Research is to support the evidence-based decision-making in education institutions. Therefore, in this course, the classmates would be asked to learn the programming language to deal with the real data and provide solid evidence to the leadership. You would be asked to fully engage in the data analysis during this semester. By the end of this course, you should be able to conduct complicated data analysis with confidence. Meanwhile, you should be able to provide productive suggestions for your supervisor's consideration. This course not only prepare you as a qualified IR officers. It also lead you as a professional data analytician.
課程進度 (1-16週)	Week 1: the introduction of the syllabus and course requirement Week 2: the foundation of Institutional research Week 3: the working environment in Stata Week 4: data cleaning & data manipulation Week 5: Project Task I Week 6: data visualization Week 7: data modeling: multiple regression, logistic regression, quantile regression Week 8: data reporting Week 9: Project Task II Week 10: team work in PIAAC data Week 11: team work in PISA data Week 12: team work in administration record data Week 13: Advanced topic I:panel data, fixed effect and random effect Week 14: Advanced topic II: instrument variable Week 15: quasi-experiment I: Difference in Difference, Synthetic Control Week 16: quasi-experiment II: Regression discontinuity, Coarsened Exact Matching, Propensity Score Method Week 17: Special talk: Geographic Information System, Social network analysis Week 18: Project Task III
彈性學習 (17-18週)	類別 　 內容 　 時數 (小時) 　 學習成果 　 評量比例
評量方式與標準	1.Project task I: 30% 2.Project task II: 30% 3. Project task III: 30% 4. class participation: 10%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 Angrist, J. D., & Pischke, J. S. (2008). Mostly harmless econometrics: An empiricist's companion. Princeton university press.
課程諮詢管道	Wednesday 13:10-15:00
延伸教學與資源	● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
課程對應SDGs指標	SDG4：優質教育（Quality Education）
課程是否導入AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI） ● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）
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