COURSE SYLLABUS

ADVANCED ANALYSIS TECHNIQUES IN EDUCATIONAL RESEARCH

1	Course Title:	ADVANCED ANALYSIS TECHNIQUES IN EDUCATIONAL RESEARCH
2	Course Code:	OKU6120
3	Type of Course:	Optional
4	Level of Course:	Third Cycle
5	Year of Study:	1
6	Semester:	2
7	ECTS Credits Allocated:	4
8	Theoretical (hour/week):	2
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Doç. Dr. MERAL TANER DERMAN
16	Course Lecturers:	-
17	Contactinformation of the Course Coordinator:	Dr. Öğr. Üyesi Meral TANER DERMAN mtaner@uludag.edu.tr 0224 2942184 Adres: Bursa Uludağ Üniversitesi Eğitim Fakültesi Temel Eğitim Bölümü Görükle Yerleşkesi Nilüfer / Bursa
18	Website:
19	Objective of the Course:	The aim of the course is to demonstrate the application of advanced quantitative research techniques.
20	Contribution of the Course to Professional Development	Students taking this course will be able to apply advanced quantitative data analysis techniques using statistical programs such as SPSS and AMOS.

Learning Outcomes:

1	To be able to have information about computer programs for statistical analysis;
2	Ability to organize the collected data using the appropriate data collection method;
3	To be able to recognize parametric and nonparametric tests;
4	Ability to test data using appropriate advanced statistical analysis;
5	Tabulating the values obtained as a result of data analysis;
6	To be able to interpret the values obtained as a result of data analysis;
7	Ability to report analysis results appropriately;

22	Course Content:

Week	Theoretical	Practical
1	Parametric and nonparametric tests
2	Outlier Analysis, Data mining
3	Exploratory factor analysis and confirmatory factor analysis
4	Structural equation modeling
5	Logistic Regression Analysis
6	Hierarchical Regression Analysis
7	Multiple Regression Analysis
8	Multiple Regression Analysis (Model Errors & Dummy Coding)
9	One-Way Multiple Variance Analysis (MANOVA)
10	Factorial MANOVA
11	Multiple Covariance Analysis (MANCOVA)
12	Nonparametric Reliability Analysis with SPSS (Fit Coefficients)
13	20 / 5000 Translation results Discriminant Analysis
14	Examination of sample theses and articles

23	Textbooks, References and/or Other Materials:	Can, A. (2017). Quantitative Data Analysis in Scientific Research Process with SPSS, 5th Edition, Ankara: Pegem Academy. Gürsakal, S. (2019). SPSS Applied Multivariate Statistical Analysis Techniques in Social Sciences, Bursa: Dora Publishing. Karagöz, Y. (2019). SPSS 23 and AMOS 23 Applied Statistical Analysis, Ankara: Nobel Publishing. Pektaş, A. O. (2013). Data Mining with SPSS, Istanbul: Dikeyeksen Publishing.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	0	0
Quiz	0	0
Homeworks, Performances	1	40
Final Exam	1	60
Total	2	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Homework and final exam
Information	Homework will be prepared in accordance with the course outcomes and a final exam will be made.

ECTS / WORK LOAD TABLE

CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High