National Taiwan Normal University Course Outline
 Fall , 2024

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I.Course information
Serial No. 1099 Course Level PhD
Course Code STD0006 Chinese Course Name 科學—科技—工程—數學教育研究法
Course Name Research on STEM Education
Department International Doctoral Program in Integrative STEM Education
Two/one semester 1 Req. / Sel. Sel.
Credits 3.0 Lecturing hours Lecture hours: 3
Prerequisite Course ◎1. This is a cross-level course and is available for junior and senior undergraduate students, master's students and PhD students. 2. If the listed course is a doctroal level course, it is only available for master's students and PhD students.
Comment ◎Distance learning course All distance learning courses display synchronous learning and face-to-face learning time only. Classroom: TA305
Course Description
Day & Class Period/Location ◎Face-to-Face/Synchronous Learning
Curriculum Goals Corresponding to the Departmental Core Goal
1.　Understand the core concepts of methodology commonly used in STEM education research Doctor:
　1-2 Ability to conduct research projects independently and collaboratively
　2-2 Mastery of analysis, integration, innovation, and implementation
　3-3 Excellence in leadership skills for planning and management
2.　Demonstrate the ability to design empirical quantitative research in STEM education Doctor:
　1-2 Ability to conduct research projects independently and collaboratively
　2-1 Capability of creative thinking and independent problem-solving
　2-2 Mastery of analysis, integration, innovation, and implementation
　3-1 Effectiveness of coordinating and cooperating with members from different backgrounds and perspectives
　3-3 Excellence in leadership skills for planning and management
3.　Apply appropriate statistical techniques to answer research questions Doctor:
　1-2 Ability to conduct research projects independently and collaboratively
　2-1 Capability of creative thinking and independent problem-solving
　2-2 Mastery of analysis, integration, innovation, and implementation
4.　Communicate the findings to different audiences effectively Doctor:
　1-3 Proficiency of presenting, publishing, and exchanging ideas.
　2-2 Mastery of analysis, integration, innovation, and implementation
　3-3 Excellence in leadership skills for planning and management

II. General Syllabus
Instructor(s) CHAN, Hsun-Yu/ 詹育
Schedule

Course time：1:20-4:20 pm (for in-person and online synchronous class meetings)

Classroom：Seminar Room No. 1

  1. 9/3 Course Introduction & Overview of Methodology in STEM Education (in-person)
  2. Topics in Quantitative methodology: Experimental design (asynchronous)
  3. Topics in Quantitative methodology: Quasi-Experimental design (asynchronous)
  4. Topics in Quantitative methodology: Survey methodology (asynchronous)
  5. Qualitative methodology (asynchronous)
  6. Mixed methods research (asynchronous)
  7. Data analysis: Statistical foundation (asynchronous)
  8. Data analysis: Mean Difference/ANOVA (asynchronous)
  9. Data analysis: ANCOVA (asynchronous)
  10. 11/5 Data analysis: Multiple Regression (synchronous online lecture)
  11. 11/12 Data analysis: SEM (synchronous online lecture)
  12. 11/19 Academic Writing I: Structure and Wording of Empirical Research Articles (synchronous online seminar)
  13. Academic Writing II: Introduction and Literature Review (asynchronous)
  14. 12/3 Academic Writing III: Methods, Results, and Discussion (synchronous online seminar)
  15. Academic Writing IV: APA Style (asynchronous)
  16. 12/17 Presentation; final words (in-person)
    DUE: Term paper, 12/24, 10:00 am

This syllabus is tentative and subject to change.
Instructional Approach
Methods Notes
Formal lecture In-class and online asynchronous lecture
Group discussion Seminar-type in-class and online discussion
Problem-based learning Instructors design problems for students to solve independently or collaboratively; issues raised by individual students will be resolved through open discussions.
Lab/Studio Practice questions to familiarize students with essential skills of using statistical software package
Media, audio, visual materials Multimedia resources and material will be integrated in lectures and discussion
Grading assessment
Methods Percentage Notes
Assignments 30 % Students are asked to complete and submit the assignment before deadline to demonstrate their mastery of the content knowledge.
Class discussion involvement 20 % Students are expected to participate in online discussion and in synchronous sessions.
Attendances 10 % Students are required to attend synchronous lectures.
Presentation 15 % Students will give a presentation to showcase their essay.
Case study reports 25 % Students will submit a final essay at the end of the semester to demonstrate their proficiency in the course content.
Required and Recommended Texts/Readings with References
  1. American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). Author. https://doi.org/10.1037/0000165-000
  2. Bartholomew, D. J., Steele, F., Moustaki, I., & Galbraith, J. I. (2008). Analysis of multivariate social science data (2nd ed.). CRC Press. https://doi.org/10.1201/b15114
  3. Creswell, J. W., Plano Clark, V. L., Gutmann, M., & Hanson, W. (2003). Advanced mixed methods research designs. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 209-240). Sage.
  4. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to design and evaluate research in education (10th ed.). McGraw-Hill.
  5. Headley, M. G., & Plano Clark, V. L. (2019). Multilevel mixed methods research designs: Advancing a refined definition. Journal of Mixed Methods Research, 14(2), 145–163. https://doi.org/10.1177/1558689819844417
  6. Kenny, D. A. (2008). Reflections on mediation. Organizational Research Methods, 11(2), 353–358. https://doi.org/10.1177/1094428107308978
  7. Leavy, P. (2017). Research design: Quantitative, qualitative, mixed-methods, arts-based, and community-based participatory research approaches. Guilford.
  8. Meyer, D. K., & Schutz, P. A. (2020). Why talk about qualitative and mixed methods in educational psychology? Introduction to special issue. Educational Psychologist, 55(4), 193–196. https://doi.org/10.1080/00461520.2020.1796671
  9. Miller, G. A., & Chapman, J. P. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110(1), 40–48.
  10. Murnane, R. J., & Willett, J. B. (2011). Methods matter: Improving causal inference in educational and social science research. Oxford University Press.
  11. Nicol, A. A. M., & Pexman, P. M. (1999). Presenting your findings: A practical guide for creating tables. American Psychological Association.
  12. Pearson, K., Fisher, R. A., & Inman, H. F. (1994). Karl Pearson and R. A. Fisher on statistical tests: A 1935 exchange from Nature. The American Statistician, 48(1), 2–11. https://doi.org/10.2307/2685077
  13. Schumacker, R. E., & Lomax, R. G. (2010). A beginner’s guide to structural equation modeling (4th ed.). Routledge.
  14. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Cengage.

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https://www.theanalysisfactor.com/

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