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Information
| Unit | INSTITUTE OF SOCIAL SCIENCES |
| SCIENCE TEACHING (MASTER) (WITH THESIS) | |
| Code | FBE716 |
| Name | |
| Term | 2025-2026 Academic Year |
| Term | Fall and Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. PINAR FETTAHLIOĞLU |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to enable students to analyze and interpret more complex datasets using advanced statistical methods in educational research. Topics include structural equation modeling, multivariate analyses, types of regression, and statistical modeling. Software tools such as SPSS, AMOS, and/or R will be used throughout the course.
Course Content
This course addresses advanced quantitative data analysis techniques used in educational research. Students will engage in hands-on applications of multiple regression, logistic regression, factor analysis, construct validity, and structural equation modeling. Throughout the course, students will learn to develop statistical models aligned with research questions, test these models, and report findings according to scientific standards. Software such as SPSS, AMOS, and R will be used with sample datasets. Advanced topics such as model fit indices, mediation and moderation analysis will also be covered.
Course Precondition
Successful completion of Applied Educational Statistics I
Resources
Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson.
Notes
Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Identifies and explains advanced statistical analysis techniques. |
| LO02 | Develops statistical models appropriate to research questions. |
| LO03 | Applies analyses such as factor analysis, multiple regression, and SEM. |
| LO04 | Interprets and reports analysis results in scientific language. |
| LO05 | Uses statistical software tools effectively. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Define and apply scientific research and analysis methods used in science | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Has basic knowledge and skills related to Science Education. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explains the development and learning theories within the scope of science education. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Describes instructional strategies, methods and techniques on the level of expertise on the basis of undergraduate qualifications. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Explains the interaction between disciplines related to the field. | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Explains the knowledge in the subject areas of science education at the level of expertise. | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Relate knowledge of science education with information in different fields. | 3 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Apply the theoretical and practical knowledge in the field of expertise | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Criticize the practices related to science education at national and international level. | 3 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Plans and conducts a scientific research. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Apply teaching methods and techniques on the basis of undergraduate qualifications. | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Manages a study that requires expertise in the field independently. | |
| PLO13 | Bilgi - Kuramsal, Olgusal | Makes teamwork or leadership in situations that require resolution of problems related to the field. | |
| PLO14 | Beceriler - Bilişsel, Uygulamalı | Questions scientific and social issues with new perspectives. | |
| PLO15 | Beceriler - Bilişsel, Uygulamalı | Carries out studies in the field of lifelong learning. | |
| PLO16 | Beceriler - Bilişsel, Uygulamalı | Follow technological developments. | |
| PLO17 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Provides a scientific study in the field of science education, supported by qualitative and quantitative data, in writing, orally and visually, to experts or non-specialists. | |
| PLO18 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Uses information and communication technologies effectively | |
| PLO19 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Use the languages of the European language portfolio to understand the information in the field and to communicate verbally and in writing | |
| PLO20 | Yetkinlikler - Öğrenme Yetkinliği | Acts in accordance with social, scientific, cultural and ethical values when conducting a scientific research or project or interpreting a study. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to the course and overview of advanced statistical analyses | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 2 | Multiple linear regression: assumptions, model building, interpretation | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Multiple regression applications (using SPSS and/or R) | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 4 | Logistic regression: modeling with binary outcome variables | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 5 | Logistic regression applications (using SPSS and/or R) | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 6 | Exploratory Factor Analysis (EFA): KMO, Bartlett test, factor loadings | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 7 | Confirmatory Factor Analysis (CFA): model setup and fit indices | reading related sections | Öğretim Yöntemleri: Anlatım, Tartışma, Soru-Cevap |
| 8 | Mid-Term Exam | reading related sections | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | CFA practice with AMOS | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 10 | Introduction to Structural Equation Modeling (SEM) | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 11 | SEM application: Model building, testing, and interpretation | ilgili bolumleri okuma | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 12 | Mediation and moderation analysis | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 13 | Model improvement, modification indices, and reporting | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 14 | Project work with applied dataset | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 15 | Student project presentations and general evaluation | reading related sections | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 16 | Term Exams | reading related sections | Ölçme Yöntemleri: Ödev |
| 17 | Term Exams | reading related sections | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 15 | 3 | 45 |
| Out of Class Study (Preliminary Work, Practice) | 15 | 3 | 45 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 15 | 3 | 45 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 4 | 4 |
| Final Exam | 2 | 4 | 8 |
| Total Workload (Hour) | 147 | ||
| Total Workload / 25 (h) | 5,88 | ||
| ECTS | 6 ECTS | ||