Teaching Assistant Evaluation
Donated on 6/6/1997
The data consist of evaluations of teaching performance; scores are "low", "medium", or "high"
Dataset Characteristics
Multivariate
Subject Area
Other
Associated Tasks
Classification
Feature Type
Categorical, Integer
# Instances
151
# Features
-
Dataset Information
Additional 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.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 5 of 5
Additional Variable 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
Dataset Files
| File | Size |
|---|---|
| tae.data | 2.1 KB |
| tae.names | 1.6 KB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset teaching_assistant_evaluation = fetch_ucirepo(id=100) # data (as pandas dataframes) X = teaching_assistant_evaluation.data.features y = teaching_assistant_evaluation.data.targets # metadata print(teaching_assistant_evaluation.metadata) # variable information print(teaching_assistant_evaluation.variables)
Loh, W. (1997). Teaching Assistant Evaluation [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C55P6M.
Keywords
Creators
Wei-Yin Loh
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.