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Students’ Ratings of University Teaching: A Data Mining Analysis

Students’ Ratings of University Teaching: A Data Mining Analysis. Chuck Dziuban Research Initiative for Teaching Effectiveness Ida Cook Department of Sociology and Anthropology Faculty Senate Morgan Wang Department of Statistics. University of Central Florida. Rationale for the Study.

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Students’ Ratings of University Teaching: A Data Mining Analysis

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  1. Students’ Ratings of University Teaching:A Data Mining Analysis Chuck Dziuban Research Initiative for Teaching Effectiveness Ida Cook Department of Sociology and Anthropology Faculty Senate Morgan Wang Department of Statistics University of Central Florida

  2. Rationale for the Study • Teaching evaluation data for a 3-year period were available to allow a comparison of two different sets of items (UCF/BOR).  • Responding to faculty interest, the UCF Faculty Senate requested that an evaluation of the Student Evaluation of Instruction measures be performed. (FS 1995-96-11)

  3. The Instrument: UCF Items • Feedback on your performance in this course • The instructor’s interest in your learning • Use of class time • The instructor’s overall organization of the course • Continuity from one class meeting to the next • The pace of the course • The instructor’s assessment of your progress • The text and supplemental learning materials used

  4. The Instrument:Board of Regent Items • Description of course objectives and assignments • Communication of ideas and information • Expression of expectations for performance • Availability to assist students In or outside of class • Respect and concern for students • Stimulation and interest in the course • Facilitation of learning • Overall assessment of instructor

  5. Approximately 450,000 student responses Five Colleges: Arts and Sciences Business Administration Education Engineering Health and Public Affairs The Study Layout • Three Levels: • Lower Undergraduate • Upper Undergraduate • Graduate • Three Years: • 1996-97 • 1997-98 • 1998-99

  6. Overall Rating of the Instructor Binary Decision Tree SAS Enterprise Miner Predictors • Level • Year • College Remaining 15 Items Developmental Sample 1 Developmental Sample 2 Developmental Sample 3 Validation Sample

  7. Decision Tree Example Overall 85.9% n=11,286 Arts & Sciences, Business Admin., Hospitality Mgmt. Health & Pub. Affairs Engineering Education 85.8% n=6,460 72.7% n=378 91.5% n=2,079 86.7% n=2,369 F2F, E, M W F2F E, M, W F2F E, M 89.1% n=1,043 79.6% n=230 94.1% n=1,036 64.7% n=148 74.8% n=821 86.5% n=5,639 females males A&S BA & Hosp. mgmt 84.1% n=2,376 78.5% n=526 88.4% n=3,263 68.9% n=298

  8. Rules Leading to Overall Rating of Excellent N=46,805 Probability = .96

  9. Rules Leading to Overall Rating of Excellent N=3,462 Probability = .85

  10. Rules Leading to Overall Rating of Excellent N=6,215 Probability = .78

  11. Overall Ratings Unadjusted and Adjusted for ‘Excellent’ Decision Rules

  12. For more information… Research Initiative for Teaching Effectiveness Dr. Chuck Dziuban 407-823-5478 dziuban@mail.ucf.edu Dr. Patsy Moskal 407-823-0283 pdmoskal@mail.ucf.edu http://rite.ucf.edu

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