ERIC Number: EJ960662
Record Type: Journal
Publication Date: 2012-May
Pages: 22
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0361-0365
EISSN: N/A
Are Student Evaluations of Teaching Effectiveness Valid for Measuring Student Learning Outcomes in Business Related Classes? A Neural Network and Bayesian Analyses
Galbraith, Craig S.; Merrill, Gregory B.; Kline, Doug M.
Research in Higher Education, v53 n3 p353-374 May 2012
In this study we investigate the underlying relational structure between student evaluations of teaching effectiveness (SETEs) and achievement of student learning outcomes in 116 business related courses. Utilizing traditional statistical techniques, a neural network analysis and a Bayesian data reduction and classification algorithm, we find little or no support for the validity of SETEs as a general indicator of teaching effectiveness or student learning. In fact, the underlying structure appears to be non-linear and possibly negatively bimodal where the most effective instructors are within the middle percentiles of student course ratings, while instructors receiving ratings in the top quintile or the bottom quintile are associated with significantly lower levels of student achievement.
Descriptors: Student Evaluation of Teacher Performance, Network Analysis, Higher Education, Teacher Effectiveness, Outcomes of Education, Bayesian Statistics, Mathematics, Academic Achievement, Statistics, Business Administration Education, Teachers, Students, Teacher Student Relationship
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A