OLC635 - MEASUREMENT APPLICATIONS IN COMPUTER
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| MEASUREMENT APPLICATIONS IN COMPUTER | OLC635 | Any Semester/Year | 2 | 2 | 3 | 8 |
| Prequisites | EBB 278 or OLC 505 or OLC 525 | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Question and Answer | |||||
| Instructor (s) | Prof. Nuri DOÄžAN | |||||
| Course objective | Being able to use computer programs in test development process and measurement and evaluation process | |||||
| Learning outcomes |
| |||||
| Course Content | Data preparation and database forming. Calculating test and item statistics by matrix operations using Excel. Calculating test and item statistics by using package programs for item analysis. Performing factor and variance analysis for the measurement results by using statistical package programs. Calculating test and item statistics by using different package programs. | |||||
| References | Howell, C. D. (1995). Fundamental statistics for the behavioral sciences. California: Duxbury Press. Gravetter, J. F. & Wallnau, L. B. (1992). Statistics for the behavioral sciences. West Pub. Company. Özçelik D. A. (1989). Test hazırlama klavuzu. Ankara: ÖSYM Eğitim Yayınları 5. Baykul, Y. (2000). Eğitimde ve psikolojide ölçme: Klasik test teorisi ve uygulaması. Ankara: ÖSYM Yayınları. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Introduction and distribution of resources |
| Week 2 | Data preparation, data modification and database forming |
| Week 3 | Calculating item statistics by using Excel |
| Week 4 | Calculating test statistics by using Excel |
| Week 5 | Calculating test and item statistics by matrix operations using Excel |
| Week 6 | Midterm exam |
| Week 7 | Calculating test and item statistics by using package programs for item analysis. |
| Week 8 | Performing factor analysis for the measurement results by using statistical package programs |
| Week 9 | Performing factor analysis for the measurement results by using statistical package programs |
| Week 10 | Midterm exam |
| Week 11 | Performing reliability analysis for the measurement results by using statistical package programs |
| Week 12 | Performing item analysis and validity analysis for the measurement results by using statistical package programs |
| Week 13 | Comparing the item and test statistics obtained from different package programs |
| Week 14 | Comparing different package programs regarding the capabilities of item and test statistics |
| Week 15 | Preparation to exam |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 10 | 10 |
| Laboratory | 0 | 0 |
| Application | 5 | 5 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 5 | 5 |
| Presentation | 0 | 0 |
| Project | 2 | 5 |
| Seminar | 0 | 0 |
| Midterms | 1 | 25 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 23 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 4 | 56 |
| Laboratory | 0 | 0 | 0 |
| Application | 14 | 3 | 42 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 10 | 4 | 40 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 2 | 15 | 30 |
| Homework assignment | 4 | 5 | 20 |
| Midterms (Study duration) | 1 | 20 | 20 |
| Final Exam (Study duration) | 1 | 25 | 25 |
| Total Workload | 46 | 76 | 233 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Uses concepts related to measurement and evaluation, statistics and research methods by associating them. | X | ||||
| 2. Explains distinguishing features of fundamental theories of measurement and evaluation. | X | ||||
| 3. Explains the research methods and statistical methods that will be used with these methods. | X | ||||
| 4. Interprets the results of the national and international exams by relating them to the concepts of measurement and evaluation. | X | ||||
| 5. Develops or adapts measurement instruments, which are aligned with the objectives, by employing measurement methods. | X | ||||
| 6. Evaluates the results of the national and international exams. | X | ||||
| 7. Identifies a research problem related to measurement and evaluation, plans and administers scientific research methods for the solution | X | ||||
| 8. Provides a technical support to solve problems encountered in other areas of social sciences. | X | ||||
| 9. Interprets and critiques the recent developments related to measurement and evaluation. | X | ||||
| 10. Applies the knowledge related to measurement and evaluation in interdisciplinary studies. | X | ||||
| 11. Monitors new software related to measurement and evaluation and uses appropriate software. | X | ||||
| 12. Carries out a research related to measurement and evaluation and presents it in national and international meetings. | X | ||||
| 13. Complies with the ethical rules in the research studies related to measurement and evaluation. | X | ||||
| 14. Shares effectively the knowledge measurement and evaluation skills with the co-workers. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest