ET 610 - LA & EDM 2021

Class overview

This website is for the ET 610 Learning Analytics and Educational Data Mining course offered at IIT Bombay, EdTech department from Jul to Nov 2021.

The course content and lecture videos are available as NPTEL course "Learning Analytics Tools"

Course Videos can be watched on YouTube

Content covered in this course:

Data Collection from Different learning environment
Descriptive Analytics, visualization, Dashboards
Diagnostic Analysis: Correlation, Sequential Pattern Mining, Process Mining
Predictive Analytics: Linear Regression, Naive Bayes, K-Means clustering
Intro to NLP, Multimodal Learning Analytics

Grading includes three assignments, mid and end-sem, and a course project.

Course Assignments

The list of assignment done by students in this course are listed below. Their submissions are available on respective pages

Python Programming assignment: To learn how to read, extract and plot data from LMS

Machine Learning Algorithms

Jigsaw learning method

Machine learning tools demo videos

Course Project

We used Open University Learning Analytics Dataset (OULAD) for the course project. The course project aims to answer the below three questions

As we will progress through the Course Project with the course data shared with you, here are some key questions that we will try to focus on step by step-

Descriptive Analytics: The goal of this phase is to come up with insightful graphs and plots that can present the data well. Students need to preprocess the data and select suitable plots to show that. They are expected to use some innovative visual representation that will unravel new insights into the dataset.
Prediction: This phase will focus on predicting the final course score in the dataset. Students are expected to engineer some new features and keep on experimenting and improve the performance of your predictive model.
Open-ended question: For this question, students are expected to come up with new research questions after they read the related articles and find a research gap. The aim is to select suitable methods and analytics and answer the research question in such a way that can it can contribute to the existing body of work on this dataset.

Course Project submissions are available here.

Page updated

Google Sites

Report abuse