| School/Faculty/Institute |
Graduate School |
| Course Code |
MED 502 |
| Course Title in English |
Educational Statistics |
| Course Title in Turkish |
Eğitimde İstatistik |
| Language of Instruction |
EN |
| Type of Course |
Flipped Classroom,Laboratory Work,Lecture |
| Level of Course |
Introductory |
| Semester |
Spring |
| Contact Hours per Week |
| Lecture: 2 |
Recitation: |
Lab: 1 |
Other: |
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| Estimated Student Workload |
126 hours per semester |
| Number of Credits |
5 ECTS |
| Grading Mode |
Standard Letter Grade
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| Pre-requisites |
None |
| Co-requisites |
None |
| Expected Prior Knowledge |
Experience in Scientific Research |
| Registration Restrictions |
Only Graduate Students |
| Overall Educational Objective |
To gain further knowledge on the important concepts in statistics for carrying out research in
the field of education. |
| Course Description |
The course begins with the general concepts and terms of educational statistics. The course is aimed to teach prospective teachers how to analyze and interpret the data they collected related with their hypotheses determined in the scientific research methods course with appropriate statistical methods. It continues with teaching how to examine data, choosing the right analysis, analyzing the data with SPSS, visualizing the data and gaining the ability to interpret the results of analysis for effective decision making. |
Course Learning Outcomes and Competences
Upon successful completion of the course, the learner is expected to be able to:
1)
2)
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6)
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| Program Learning Outcomes/Course Learning Outcomes |
1 |
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6 |
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Relation to Program Outcomes and Competences
| N None |
S Supportive |
H Highly Related |
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Program Outcomes and Competences |
Level |
Assessed by |
| 1) |
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N |
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| Prepared by and Date |
BENGİ BİRGİLİ , December 2023 |
| Course Coordinator |
BENGİ BİRGİLİ |
| Semester |
Spring |
| Name of Instructor |
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Course Contents
| Hafta |
Konu |
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| Required/Recommended Readings | List of readings and indication whether they are required or recommended.
Required Books
Gravette, F. J. & Wallnau, L. B. (2016). Statistics for the behavioral sciences (10th ed.) Belmont, CA: Wadsworth.
Green, S. B., Salkind, N. J., & Akey, T. M. (2008). Using SPSS for Windows and Macintosh: Analyzing and understanding data (5th ed.). Upper Saddle River, NJ: Prentice Hall.
American Psychological Association (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC.
Recommended Readings
Nicol, A. A. & Pexman, P. M. (2010). Presenting your findings: A practical guide for creating tables. Washington, DC: American Psychological Association.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbuam.
Keppel, G., & Wickens, T. D. (2004). Design and Analysis: A researcher's handbook (4th ed.). Upper Saddle River, NJ: Prentice Hall.
Pallant, J. (2001). SPSS survival manual. Buckingham, UK: Open University. (HA 32. P355)
Stevens, J. (2002). Applied multivariate statistics for the social sciences. Mahwah, NJ: Lawrence Erlbaum Associates.
Tabachnick, B. G., & Fidell, L. S. (2012). Using multivariate statistics. Needham Heights, MA: Allyn and Bacon.
Suggested Online Resources:
Introductory Statistics (http://www.psychstat.missouristate.edu/Introbook/sbk00.htm)
Statistics Glossary (http://www.stats.gla.ac.uk/steps/glossary/index.html)
Statistical Analysis on the Internet (http://www.quantitativeskills.com/sisa/)
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| Teaching Methods | Flipped learning will be used as the main teaching strategy. However, course lecture, direct instruction, and group work and discussions will be used. Students will discuss in their groups about practical aspects behind each analysis techniques. In the classroom/lab, they will actively engage in quantitative data analysis with SPSS and interpreting the results. |
| Homework and Projects | Assignments: Throughout the course you will be given six assignments. Each assignment will be graded over 50 points, and the primary intent of the assignments for you is to assess your on-going learning and to guide your own learning efforts. A rubric for assessment will be provided for each assignment.
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| Laboratory Work | |
| Computer Use | SPSS Software during lab applications
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| Other Activities | Types of assessment (examinations, papers, presentations, homework, quizzes, projects, portfolio, internship report, continuous assessment (in-class participation), others); number of said activities and percentiles of total grade (weighting scheme).
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| Assessment Methods |
| Assessment Tools |
Count |
Weight |
| Ödev |
1 |
% 40 |
| Sunum |
1 |
% 10 |
| Projeler |
1 |
% 30 |
| Ara Sınavlar |
1 |
% 20 |
| TOTAL |
% 100 |
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| Course Administration |
Grading;
Assignments and Participation: 40%
Midterm examination: 20%
Article critique: 10%
Final Project: 30%
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