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1. Title: Teaching Assistant Evaluation
2. Sources:
(a) Collector: Wei-Yin Loh (Department of Statistics, UW-Madison)
(b) Donor: Tjen-Sien Lim (limt@stat.wisc.edu)
(b) Date: June 7, 1997
3. Past Usage:
1. Loh, W.-Y. & Shih, Y.-S. (1997). Split Selection Methods for
Classification Trees, Statistica Sinica 7: 815-840.
2. Lim, T.-S., Loh, W.-Y. & Shih, Y.-S. (1999). A Comparison of
Prediction Accuracy, Complexity, and Training Time of
Thirty-three Old and New Classification Algorithms. Machine
Learning. Forthcoming.
(ftp://ftp.stat.wisc.edu/pub/loh/treeprogs/quest1.7/mach1317.pdf or
(http://www.stat.wisc.edu/~limt/mach1317.pdf)
4. Relevant Information:
The data consist of evaluations of teaching performance over three
regular semesters and two summer semesters of 151 teaching assistant
(TA) assignments at the Statistics Department of the University of
Wisconsin-Madison. The scores were divided into 3 roughly equal-sized
categories ("low", "medium", and "high") to form the class variable.
5. Number of Instances: 151
6. Number of Attributes: 6 (including the class attribute)
7. Attribute Information:
1. Whether of not the TA is a native English speaker (binary)
1=English speaker, 2=non-English speaker
2. Course instructor (categorical, 25 categories)
3. Course (categorical, 26 categories)
4. Summer or regular semester (binary) 1=Summer, 2=Regular
5. Class size (numerical)
6. Class attribute (categorical) 1=Low, 2=Medium, 3=High
8. Missing Attribute Values: None
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