DEVELOPING EVALUATION CRITERIA OF ACADEMICIANS ’ TEACHING PERFORMANCE: DISCRIMINANT AND LOGISTIC REGRESSION APPLICATIONS

Öz

Since 1997 students’ course evaluation questionnaire (SCEQ) has been conducted in Business Administration Department of Marmara University to evaluate teaching effectiveness of instructors. In this study data obtained from 2000-2001 and 2001-2002 questionnaires are used to conduct discriminant and logistic regression analysis. As a result of these analyses evaluation criteria of academicians’ teaching performance are developed Findings of both the discriminant and logistic regression methods show similar results. In both methods “satisfaction with the way course is conducted” is the most powerful item that discriminates effective instructors from ineffective instructors. This item is followed by “instructors being competent in his/her field” and “exams being a good measuring device”.

Anahtar Kelimeler

• Discriminant Analysis,Logistic Regression Analysis,Course Evaluation,Student Evaluation,Instructor Performance

Kaynakça

1. [1] JOHNSON, P„ CASSELİ, C„ CLOSE, P„ & DUBERLEY, J. (2001). Performance Evaluation and Control Supporting Organizational Change. Management Decision. Vol 39 No 10 pp 841-850.
2. [2] ARNOLD, H.J. & Feldman, D.C. (1986). Organizational Behavior. Singapore, McGraw Hill International Editions
3. [3] AAMODT, M.G. (1996). Applied industrial/organizational psychology. Brooks/Cole Publishing Company. Pasific Grove. CA.
4. [4] AHMADI, M., HELMS, M. M. & RAISZADEH, F. (2001). Business students1' perceptions of faculty evaluations. The International Journal of Educational Management. Vol 15 No 1 pp 12-22.
5. [5] EMERY, C.R., KRAMER, T.R., & Tl AN, R.G. (2003). Return to Academic Standards: a Critique of Student Evaluations of Teaching Effectiveness. Quality Assurance in Education. Vol 11 No 1 pp 37-46.
6. [6] RADMACHER, S.A. & MARTIN, D.J. (2001). Identifying Significant Predictors of Student Evaluations of Faculty Through Hierarchical Regression Analysis. Journal of Psychology. Vol 135 issue 3 pp 259-269.
7. [7] CRUMBLEY, D.L. & FLIEDNER E. (2002). Accounting administrators’ perceptions of student evaluation of teaching (SET) information. Quality Assurance in Education. Vol 10 No 4 pp 213-222.
8. [8] LIAW, S. & GOH K. (2003). Evidence and Control of Biases m Student Evaluation of Teaching. The International Journal of Educational Management. Vol 17 No 1 pp 37-43. [9] COBURN, L. (1984). Student Evaluation of Teacher Performance. ERIC/TME Update Series. http://ericae.net/edo/ED289887.htm (Date:12.04.2003)

9. [10] HOBSON, S.M. & TALBOT,D.M. (2001). Understanding Student Evaluations College Teaching. Vol 49. issue 1. pp 26-32.
10. [11] SOJKA, J., GUPTA, A.K. & Deeter-Schmelz, D.R. (2002). Student and Faculty Perceptions of Student Evaluations of Teaching: A Study of similarities and Differences. College Teaching. Vol 20 issue 2 pp 44- 49.
11. [12] TIMPSON, W.W. & DESLEY, A. (1997). Rethinking Student Evaluations and The Improvement of Teaching: instruments for Change at the University of Queensland. Studies in Higher Education. Vol 22 issue 1 pp 55-66.
12. [13] KOH, H.C. & TAN, T. M. (1997) Empirical Investigation of the Factors Affecting SET Results. The International Journal of Educational Management. Vol 11 No4pp 170-178.
13. [14] McKINNEY, K.(1997). What Do Students Ratings Mean? The National Teaching and Learning Forum. Vol 7 No 1 pp 1-4.
14. [15] WHITWORTH, J.E., PRICE, B.A. & RANDALL, C.H. (2002). Factors that Affect College of Business students Opinion of Teaching and learning. Journal of Eduction for Business. Vol. 77. Issue 5 pp 282-289.
15. [16] TC YÜKSEK ÖĞRETİM KURULU (2000). Öğrencilerin Eğitimi Değerlendirmesi. Ankara.: Ankara Üniversitesi Basım Evi
16. [17] HAIR, Jr. J.F., ANDERSON, E.R., TATHAM, R.L., & BLACK, C.W. (1998). Multivariate Data Analysis Upper Saddle River, NJ: Prentice Hall Inc.
17. [18] LATTIN, I; CARROLL, D.; & GREEN, P.E. (2003) Analyzing Multivariate Data. Duxbury Applied Series. Pacific Grove, CA: Thomson Learning Inc.
18. [19] SHARMA, S. (1996). Applied Multivariate Statistical Analysis. New York, NY: John Wiley & Sons, Inc.
19. [20] NORUSIS, M.J. (1992). SPSS for Windows: Advanced Statistics. Chicago, IL: SPSS Inc.
20. [21] KLECKA, R.W. (1980). Discriminant Analysis. Newbury Park, California.: Sage Publications, Inc.
21. [22] BAYRAM, N.(2002). Diskriminant analizi: Akademisyenler üzerine bir uygulama. Öneri. Cilt 5. Sayı 17. s.219-229
22. [23] GREEN, S.B., SALKIND, N.J. & AKEY, M.T. (2000). Using SPSS for Windows: Analysing and Understanding Data. Upper Saddle River, NJ: Prentice Hall Inc.
23. [24] MENARD, S. (1995). Applied Logistic Regression Analysis. Thousand Oaks, California.: Sage Publications, Inc
24. [25] HOSMER, D.W. & LEMESHOW, S. (1989). Applied Logistic Regression. New York, NY: John Wiley & Sons, Inc.