İDÖ716 - STATISTICAL METHODS IN EDUCATION II

Course Name Code Semester Theory
(hours/week)		 Application
(hours/week)		 Credit ECTS
STATISTICAL METHODS IN EDUCATION II İDÖ716 3rd Semester 2 2 3 12
PrequisitesNone
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Discussion
Problem Solving
Other: Project-based Learning, Researched-based Learning,Laboratory work  
Instructor (s)Assoc. Prof. Dr. Halil YURDUGÃœL 
Course objectiveThe purpose of this course is to teach the multivariate statistics, used commonly in educational researches. 
Learning outcomes
  1. a. Buildings the multivariate statistical model and detect their assumptions b. Buildings and analyzes the multiple regression models c. Uses the exploratory factor analysis models and interpreter its results d. Uses the confirmatory factor analysis models and interpreter its results e. Examines the hypotheses in structural equating models
  2. f. Uses the factor and structural equating models in educational problems g. Analyzes the repeated measurement ANOVA, and MANOVA, MANCOVA h. Analyzes the growth models based on structural equation modeling i. Understands and applies the clustering analysis
Course ContentMultivariate statistical models and their properties, multiple regression analysis, exploratory and confirmatory factor analysis, structural equating modeling, latent growth models and repeated measure ANOVA, MAN(C)OVA, and cluster analysis 
ReferencesTabachnick, B.G. and Fidell, L.S. (1996). Using Multivariate Statistics. NY: HarperCollins.
Byrne, B.M. (1998).Structural equation modeling with LISREL, PRELIS and SIMPLIS: basic concepts, applications and programming, Erlbaum.
 

Course outline weekly

WeeksTopics
Week 1Introduction and revising fundamental statistical models
Week 2Comparison of univariate and multivariate statistical models
Week 3Investigation of the multivariate models? assumption
Week 4Principal component analysis
Week 5Exploratory factor analysis
Week 6Confirmatory factor analysis
Week 7Structural equation modeling
Week 8Midterm exam
Week 9Repeated measure ANOVA and ANCOVA
Week 10Latent growth modeling
Week 11Multivariate analysis of variance (MANOCA)
Week 12Multivariate analysis of covariance (MANCOVA)
Week 13Logistic and discriminant analysis
Week 14Cluster analysis
Week 15Revising and reviewing semester topics
Week 16Final exam

Assesment methods

Course activitiesNumberPercentage
Attendance1410
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments00
Presentation00
Project130
Seminar00
Midterms120
Final exam140
Total100
Percentage of semester activities contributing grade succes150
Percentage of final exam contributing grade succes150
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 4 56
Laboratory 0 0 0
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)14570
Presentation / Seminar Preparation17070
Project000
Homework assignment000
Midterms (Study duration)17070
Final Exam (Study duration) 19494
Total Workload31243360

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Critically evaluate advancements in English Language Teaching using scientific methods.    X
2. Recognize how cultural factors influence English Language Teaching applicationsX    
3. Analyze target student groups' language skills, learning roles, and their contributions to the fieldX    
4. Leverage information technologies for planning graduate-level teaching& learning, considering factors like teaching-learning process, learner development stages, learner differences, subject area specifics.    X
5. Design effective learning environments that consider learners' individual, social, and cultural needs, interests, and differences. Develop suitable learning materialsX    
6. Employ appropriate methods to cultivate critical and creative thinking, problem-solving skills within the research field, using English effectively. Conduct research to define and solve problems.    X
7. Utilize various assessment and evaluation methods for theses and other scientific studies.    X
8. Communicate thoughts and solutions in the field, both orally and in writing. Produce original research.X    
9. Act ethically and professionally, adhering to regulations concerning duties, rights, and responsibilities. Uphold democratic, human rights, and social/scientific/cultural values.X    
10. Take ownership of problem-solving as both an individual and a team member, continuously developing professional knowledge and skills in English language teaching.    X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest