國立中山大學 109學年度第1學期 課程教學大綱

National Sun Yat-sen University 109Academic year1st Semester Course syllabus

Course name(Chinese)


Course Code


Course name(English)


Type of the course










因應嚴重特殊傳染性肺炎(武漢肺炎),倘若後續需實施遠距授課,授課方式調整如下:Since COVID-19, if distance learning is necessary, the teaching methods would adjust as follows:

         同步遠距【透過網路直播技術,同時進行線上教學,得採Microsoft Teams、Adobe connect等軟體進行】
同步遠距含錄影【透過網路直播技術,同時進行線上教學並同時錄影,課程內容可擇日再重播,得採Microsoft Teams、Adobe connect等軟體進行】


因應嚴重特殊傳染性肺炎(武漢肺炎),倘若後續需實施遠距授課,評分方式調整如下:Since COVID-19, if distance learning is necessary, the evaluation would adjust as follows:

1.Class Discussion20%
3.Midterm Exam20%
4.Final Exam30%

課程大綱 Course syllabus

         本課程教學大綱已提供完整英文資訊(本選項僅供統計使用,未提供完整英文資訊者,得免勾記)【Provide information of course syllabus in English.(This is for statistical use only. For those who do not provide information of course syllabus in English, do not check this field.)】

This course will introduce students to Structural Equation Modeling in the Human Resource Management applications. Students will learn to examine the characteristics of observed variables (e.g., skewness and kurtosis), to use computer packages to perform parameter or model estimation, and to interpret and report the results of data analysis. General topics covered in class include: Path Analysis, Factor Analysis, Structural Regression Modeling, Latent Growth Curve Modeling, and some advanced topics in Structural Equation Modeling.

課程目標 Objectives

         1. Be familiar with basic statistical concepts, matrix operations, and the relationship between manifest/observed variables and latent variables
2. Be familiar with factor analysis including both exploratory and confirmatory approaches
3. Be familiar with structural equation modeling and its extended applications
4. Be able to empirically examine the psychometric properties of a scale through factor analytic models
5. Be able to study relational phenomena in the field of Human Resource Management using structural equation modeling and its extensions
6. Be able to set up and execute the statistical software program Mplus to perform data analysis using different analytical techniques

授課方式 Teaching methods

         Lecture & Discussion

評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference

1.Class Discussion20%
3.Midterm Exam20%
4.Final Exam30%

參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use

         1. Raykov, T., & Marcoulides, G. A. (2006). A First Course in Structural Equation Modeling (2nd edition). Mahwah, NJ: Lawrence Erlbaum Associates Inc.
2. 陳新豐 (2014)。結構方程模式:Mplus的應用。臺北:心理。

每週課程內容及預計進度 Weekly scheduled progress

WeekDateContent and topic
12020/09/06~2020/09/12Course Overview
22020/09/13~2020/09/19Basic Statistical Concepts & Matrix Operations
32020/09/20~2020/09/26Path Analysis & Introduction to Mplus
42020/09/27~2020/10/03Factor Analysis I
52020/10/04~2020/10/10Factor Analysis II
62020/10/11~2020/10/17Applications of Factor Analysis
72020/10/18~2020/10/24Structural Regression Modeling
82020/10/25~2020/10/31Applications of Structural Regression Modeling I
102020/11/08~2020/11/14Applications of Structural Regression Modeling II
112020/11/15~2020/11/21Practical Guidelines for Reporting SEM/CFA results
122020/11/22~2020/11/28Latent Growth Curve Modeling
132020/11/29~2020/12/05Applications of Latent Growth Curve Modeling
142020/12/06~2020/12/12Advanced topics related to SEM I (e.g., multiple-group CFA, multiple-group SEM)
152020/12/13~2020/12/19Advanced topics related to SEM II (e.g., categorical data)
162020/12/20~2020/12/26Advanced topics related to SEM III (e.g., missing data)
172020/12/27~2021/01/02Course Review
182021/01/03~2021/01/09Final Exam

課業討論時間 Office hours

         時段1 Time period 1:
時間 Time:星期二13:00-15:00
地點 Office/Laboratory:管4081
時段2 Time period 2:
時間 Time:星期三10:00-12:00
地點 Office/Laboratory:管4081

系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university

basic disciplines and core capabilities of the department and the university
Class activities and evaluation
本課程欲培養之能力與素養 This course enables students to achieve.紙筆考試或測驗 Test.課堂討論︵含個案討論︶ Group discussion (case analysis).個人書面報告、作業、作品、實驗 Indivisual paper report/ assignment/ work or experiment.群組書面報告、作業、作品、實驗 Group paper report/ assignment/ work or experiment.個人口頭報告 Indivisual oral presentation.群組口頭報告 Group oral presentation.課程規劃之校外參訪及實習 Off-campus visit and intership.證照/檢定 License.參與課程規劃之校內外活動及競賽 Participate in off-campus/ on-campus activities and competitions.課外閱讀 Outside reading.
※系所學生專業能力 Basic disciplines and core capabilities of the department
1.學生能注意倫理議題。 1. Students are able to notice academic ethics.V VV V    V
2.學生能具有效溝通及教學的能力。 2. Students are able to have effective communication and teaching abilities.           
3.學生能使用科學方法進行高品質的研究。 3. Students are able to use scientific methods to conduct research in high-quality.VVVV V    V
4.學生能具備國際觀並將之運用在研究中。 4. Students are able to have global viewpoint and perform it well in the research.           
5.學生能了解專業的議題並運用專業知識來解決問題。 5. Students are able to comprehend professional subjects and apply the knowledge to solve the problems.VVVV V    V
6.學生能注意並從事與社會責任相關議題的研究。 6. Students can pay attention to and conduct research on issues related to social responsibility.           
※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university
1.表達與溝通能力。 1. Articulation and communication skillsV VV V    V
2.探究與批判思考能力。 2. Inquisitive and critical thinking abilitiesVVVV V    V
3.終身學習能力。 3. Lifelong learningV VV V    V
4.倫理與社會責任。 4. Ethnics and social responsibility           
5.美感品味。 5. Aesthetic appreciation           
6.創造力。 6. Creativity           
7.全球視野。 7. Global perspective           
8.合作與領導能力。 8. Team work and leadership           
9.山海胸襟與自然情懷。 9. Broad-mindedness and the embrace of nature            

本課程與SDGs相關項目:The course relates to SDGs items:


本課程校外實習資訊: This course is relevant to internship: