About the dataset

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.

To load the dataset in your jupyter notebook, use the below command:

import pandas as pd
ta_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/Teaching_Assistant_Evaluation/Training_set_ta.csv')

Data Description

ES: Whether the TA is an English Speaker or not - binary (1 = English Speaker, 0 = Non - English Speaker)
Instructor: Course instructor - categorical (25 categories)
Course: Course - categorical (26 categories)
Semester: Summer or Regular - binary (1=Summer, 2=Regular)
Class_Size: Size of the class - numerical
Performance: Teaching performance over three regular semesters and two summer semesters - categorical (1=Low, 2=Medium, 3=High)

Evaluation Dataset

Load the evaluation data (name it as 'evaluation_data'). You can load the data using the below command.

evaluation_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/Teaching_Assistant_Evaluation/Testing_s

Reference

This dataset was downloaded from the UCI Machine Learning Repository - https://archive.ics.uci.edu/ml/datasets/Teaching+Assistant+Evaluation

Teaching Assistant Evaluation

Challenge Starts

Challenge Ends