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課程簡介 Course Introduction
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開課年度學期 Year / Term
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114 學年度 第 2 學期
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開課班級 Department
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教育學系課程與教學碩士班 教育系課程教管數評碩博合
Master Program of Curriculum and Instruction ,Department of Education
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授課方式 Instructional Method
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課堂教學 、 英語-不加成
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課程電腦代號 Course Reference Number
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112022
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課程名稱(中文) Course Title(Chinese)
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結構方程模式專題研究
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課程名稱(英文) Course Title(English)
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The Seminar of Structural Equation Models
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學分數/時數 Credit Hours
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3 /
3
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必(選)修 Required / Elective Course
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選修 Elective
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授課老師 Instructor
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林娟如、曾明基
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助教 Teaching Assistant
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李沛容
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上課時間 Meeting Time
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星期三，節次C
Wed, Period C、D、E
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上課教室 Classroom
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A302
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Office Hours
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| 獲獎及補助情形 Awards and Grants |
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| 聯合國永續發展目標 (SDGs跨域類別) Sustainable Development Goals, SDGs |
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SDGs 17.
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多元夥伴關係：建立多元夥伴關係，協力促進永續願景
Partnerships for the Goals：Strengthen the means of implementation and revitalize the global partnership for sustainable development
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課程目標 Learning Objectives
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This course is designed for graduate students who had completed course of Educational Statistics (I) or equivalent. Content will include concepts of inferential statistics, the assumptions associated with and the application of selected inferential statistical procedures for structural equation modeling. Computer software (Mplus) will be employed to assist in the analysis of data for this course. The emphasis in this course will be upon understanding statistical concepts, developing skills for carrying out data analyses, and interpreting and reporting findings.
1. Understand the principles of commonly used statistical verification methods and when to apply them.
2. Select appropriate analytical methods to solve problems and interpret analytical results.
3. Use statistical software to perform data analysis and write a report on the analysis results.
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先修 ( 前置 ) 課程 Prerequisite
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Educational Statistics
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| 彈性教學規劃 Flexible Teaching/Planning Schedules |
| ＊本課程實施16+2週彈性教學方案，其中第17、18週之彈性規劃如下： |
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線上教學/討論
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課程大綱 Course Syllabus
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| 週次 Week |
課程單元大綱 Unit |
教學方式 Instructional Method/Style/Teaching Style |
參考資料或相關作業 References or Related Materials |
評量方式 Grading |
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1
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Course Overview, Regression Analysis
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Narration & discussion
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2
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Model Specification and Identification
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Narration & discussion
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3
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Parameter Estimation, Model and Parameter Evaluation
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Narration & discussion
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4
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Confirmatory Factor Analysis 1
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Narration & discussion
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5
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Confirmatory Factor Analysis 2
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Narration & discussion
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6
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Confirmatory Factor Analysis 3
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Narration & discussion
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7
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Mediation Analysis
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Narration & discussion
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8
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Moderation Analysis
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Narration & discussion
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9
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Growth Modeling I
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Narration & discussion
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10
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Growth Modeling I I
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Narration & discussion
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11
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Cross-Lagged Panel Modeling I
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Narration & discussion
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12
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Cross-Lagged Panel Modeling II
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Narration & discussion
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13
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Measurement Invariance
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Narration & discussion
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14
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Multigroup SEM with Big Data
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Narration & discussion
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15
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Machine Learning for SEM
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Narration & discussion
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16
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Applied SEM Practice : Q & A
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Narration & discussion
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17
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Final Project Presentation
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Report
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18
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Final Project Presentation
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Report
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單一課程對應校能力指標程度 The Degree to Which Single Course Corresponds to School Competence
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| 編號 No. |
校核心能力 School Core Competencies |
符合程度 Degree of conformity |
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1
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公民力 (Citizen)
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3
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2
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自學力 (Self-learning)
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4
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3
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資訊力 (Information)
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5
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4
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創造力 (Creativity)
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4
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5
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溝通力 (Communication)
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4
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6
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就業力(Employability)
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3
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單一課程對應系能力指標程度 The Degree to Which Single Course Corresponds to Department Competence
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| 編號 No. |
類別 Category |
系核心能力 Department Core Competencies |
符合程度 Degree of conformity |
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01
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系所
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能應用課程與教學領域的專業知能，進行文獻與實務的省思與批判
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5
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02
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系所
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能統整課程與教學理論與實務知能，進行研究、思考與批判
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5
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03
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系所
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能探究課程與教學議題並進行論文發表
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5
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單一課程對應院能力指標程度 The Degree to Which Single Course Corresponds to College Competence
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| 編號 No. |
院核心能力 College Core Competencies |
符合程度 Degree of conformity |
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1
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探究能力
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5
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2
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語文與溝通能力
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4
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3
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創新與實踐能力
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4
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4
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專業知能
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5
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教科書或參考用書 Textbooks or Reference Books
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館藏書名 Library Books
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備註 Remarks
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Reference book:
*Wang, J. & Wang, X. (2020). Structural equation modeling: Applications Using Mplus (2nd ed). John Wiley & Sons Ltd.
Byrne, B. M. (2012). Structural equation modeling with Mplus: Basic concepts, applications, and programming (2nd ed). Routledge.
Kelloway, E. K. (2015). Using MPLUS for structural equation modeling: A researcher’s guide (2nd ed). Thousand Oaks, CA: Sage.
Reference
Tseng, M. C. (2024). Fitting cross-lagged panel models with the residual structural equations approach. Structural Equation Modeling, 31(5), 923-931. https://doi.org/10.1080/10705511.2023.2296862
Tseng, M. C. (2024). Latent profile transition analysis with random intercepts (RI-LPTA). Structural Equation Modeling, 31(4), 626-634. https://doi.org/10.1080/10705511.2023.2284671
Tseng, M. C. (2025). Non-normal GMM with covariates: A modified 3-step analysis. Structural Equation Modeling, 32(4), 606-617. https://doi.org/10.1080/10705511.2025.2475102
Tseng, M. C. (2025). Latent interaction effect in the CLPM model: A two-step multiple imputation analysis. Structural Equation Modeling, 32(1), 26-35. https://doi.org/10.1080/10705511.2024.2374349
Tseng, M. C. (2025). The construction of a growth model with residual structure equation modeling: An example analysis. Structural Equation Modeling. https://doi.org/10.1080/10705511.2025.2599980
Tseng, M. C. (2025). Latent class model with covariates: One-step approaches using PSEM. Structural Equation Modeling. https://doi.org/10.1080/10705511.2025.2610828
Tseng, M. C. (2025). Residual structural equation modeling with nonnormal distribution. Multivariate Behavioral Research. Advance online publication. https://doi.org/10.1080/00273171.2025.2445371
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※請尊重智慧財產權，不得非法影印教科書※
※ Please respect intellectual property rights and do not illegally photocopy textbooks. ※
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教學方法 Teaching Method
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教學方法 Teaching Method
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百分比 Percentage
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Narration
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80 %
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Discussion
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20 %
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| 總和 Total |
100 % |
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成績評量方式 Grading
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| 評量方式 Grading |
百分比 Percentage |
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Oral presentation
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50 %
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Report
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50 %
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| 總和 Total |
100 % |
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課程大綱補充資料 Supplementary Material of Course Syllabus
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