An Application of Regression Models with Student Ratings in Determining Course Effectiveness.Report as inadecuate

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The purpose of this study was to construct regression models that can identify sources of desired or undesired influences on student ratings. The approach uses course effectiveness findings developed with regression models to identify a possible solution to the two problems in using student ratings as a major component of course effectiveness: (1) variables other than teacher performance may contribute to ratings; and (2) students may tend to be generous in their ratings. The sample included 114 undergraduate courses from the Department of Elementary Education at National Hualien Teachers College, Taiwan, in 1999. The Student Ratings of Instruction form was used to measure students' perceptions of faculty performance. Five background variables are included in the developed regression equation. They are student enthusiasm, participation, expected grade, grading standard, and course difficulty. The results of this study indicate that 99.1% of the courses are rated above the middle of the entire raw-score scale. The T scores (adjusted scores), converted from the residual in regression models, are between 16.45 and 74.94. Twenty courses rated effective by the unadjusted score are classified as ineffective by the adjusted score. Eighteen courses judged ineffective through the unadjusted score are classified as effective through the adjusted score. The consistency of course-ranking classification is 66.7%. The correlation between unadjusted scores and adjusted scores in 0.447. The correlation between unadjusted course rankings and adjusted course rankings is 0.334. (Contains 37 references and 8 tables.) (SLD)

Descriptors: Difficulty Level, Evaluation Methods, Foreign Countries, Higher Education, Instructional Effectiveness, Regression (Statistics), Student Evaluation of Teacher Performance, Undergraduate Students, Validity

Author: Chang, Te-Sheng


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