| School/Faculty/Institute |
Graduate School |
| Course Code |
PSYC 502 |
| Course Title in English |
Advanced Research Methods II |
| Course Title in Turkish |
İleri Araştırma Metotları II |
| Language of Instruction |
EN |
| Type of Course |
Flipped Classroom |
| Level of Course |
Select |
| Semester |
Spring |
| Contact Hours per Week |
| Lecture: 1.5 |
Recitation: 0 |
Lab: 1.5 |
Other: 0 |
|
| Estimated Student Workload |
187 hours per semester |
| Number of Credits |
7.5 ECTS |
| Grading Mode |
Standard Letter Grade
|
| Pre-requisites |
None |
| Co-requisites |
None |
| Expected Prior Knowledge |
None
|
| Registration Restrictions |
Only Graduate Students |
| Overall Educational Objective |
With this course students will be able to build on their understanding of Advanced Research Methods I and conduct statistical analyses using methods such as correlational analyses, regression, ANOVA, ANCOVA, MANOVA, path analyses and the like. The will also learn to conduct meta-analyses using existing data. |
| Course Description |
The aim of the course is to build up on knowledge from Advanced Research Methods I and familiarize students with statistical analyses techniques and programmes such as SPSS, JASP and JAMOVI. The course also focuses on further enhancing analytical thinking skills, identifying research questions, operationalizing hypotheses, designing procedures to test hypotheses, interpreting results, and reporting them in a written research report. |
Course Learning Outcomes and Competences
Upon successful completion of the course, the learner is expected to be able to:
1) Evaluate own and others work with respect to the research methods of psychological science
2) Identify research questions and operationalize hypotheses
3) Design research procedures
4) Analyze advanced data with statistical packages
5) Conduct and interpret existing meta-analysis
6) Discuss findings with analytical evaluation
7) Write a research report
|
| Program Learning Outcomes/Course Learning Outcomes |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
Relation to Program Outcomes and Competences
| N None |
S Supportive |
H Highly Related |
| |
|
|
| |
Program Outcomes and Competences |
Level |
Assessed by |
| Prepared by and Date |
MÜJDE PEKER BOOTH , |
| Course Coordinator |
MÜJDE PEKER BOOTH |
| Semester |
Spring |
| Name of Instructor |
|
Course Contents
| Week |
Subject |
| 1) |
Introduction and Statistical Inference |
| 2) |
Correlational Research and Regression Analyses |
| 3) |
One-Way ANOVA |
| 4) |
Two- Way Between Subjects ANOVA |
| 5) |
Two- Way Within Subjects ANOVA |
| 6) |
Three- Way Between Subjects ANOVA |
| 7) |
Three- Way Between Subjects ANOVA |
| 8) |
Midterm
|
| 9) |
Mediation |
| 10) |
Moderation |
| 11) |
Moderated Mediation |
| 12) |
Path Analysis |
| 13) |
Conducting and Interpreting Meta-analysis
|
| 14) |
Structural Equation Modeling |
| 15) |
Final Examination Period |
| 16) |
Final Examination Period |
| Required/Recommended Readings | 1- Leary, M. R. (2014). Introduction to Behavioural Research Methods (6th Edition). Pearson Education Limited.
2- Griffith, A. (2007). SPSS for dummies. Hoboken, NJ: Wiley. 3- Articles will be given weekly to discuss in the class.
|
| Teaching Methods | Flipped format will be used for the whole course. Every week related chapters/articles will be given before classes. Before the labs pre-class videos will be uploaded. The course will have a weekly lecture and a lab session. The lecture will include a lecture by the instructor and a portion devoted for the student to discuss the materials. In the lab sessions students will engage in activates and have hand on experience of the research methods thought in the lectures. All students are expected to be prepared for all classes and actively join the discussions, ask questions and try to find answers to these questions. In case students are having difficulties, they are free to contact the instructor anytime by e-mail. |
| Homework and Projects | Students are expected to read the readings assigned by the instructor each. They are expected to actively join the discussion in the last hour. The students will also be working on a research project throughout the semester where they can apply the course material. |
| Laboratory Work | Each a lab session will be held where students will engage in activates. |
| Computer Use | Use of statistical packages and writing software. |
| Other Activities | - |
| Assessment Methods |
| Assessment Tools |
Count |
Weight |
| Attendance |
1 |
% 20 |
| Project |
1 |
% 30 |
| Midterm(s) |
1 |
% 25 |
| Final Examination |
1 |
% 25 |
| TOTAL |
% 100 |
|
| Course Administration |
mujde.peker@mef.com
mujde.peker@mef.com
Office hour: By appointment.
Attendance at all classes is compulsory. Students arriving 15 min. late will not be allowed to join. In case of missing an exam, students must provide an acceptable and documented
excuse. Make-up exam will be held for the missed exams.
Students are expected to treat university staff and others respectfully at all times. The commitment of acts of cheating, lying, and deceit in any of their diverse forms such as plagiarism, and copying during examinations will not be tolerated and will be punished according to YÖK and university regulations.
Academic dishonesty and plagiarism: Law on Higher Education Art. 54. |
Information Package / Course Catalogue