Learning Analytics Tools

By Prof. Ramkumar Rajendran | IIT Bombay

Learners enrolled: 3163

Learning analytics is a method to collect, measure, analysis and reporting of data about learners and their interactions with a learning environment. Learning analytics is applying analytics on educational data to infer the student learning process and to provide support.
Learning analytics is important course in the data era and it will help the learner to apply analytics on data from education domain and help the students to learn.

INTENDED AUDIENCE : Any interested learners

PREREQUISITES : None

INDUSTRIES SUPPORT : None

Summary

Course Status :	Completed
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Multidisciplinary Data Science Faculty Domain for Newly Joined Faculty Domain for Experienced
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	14 Sep 2020
End Date :	04 Dec 2020
Enrollment Ends :	25 Sep 2020
Exam Date :	20 Dec 2020 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1:Lecture 1:Intro To Data Analytics

Lecture 2:What is LA! Definition

Lecture 3:Academic Analytics, and Educational Data Mining

Lecture 4:Four Levels of Analytics

Lecture 5:Descriptive, Diagnostic, Predictive and Prescriptive Analytics

Week 2:Lecture 1:Data Collection from Different learning environment

Lecture 2:Technology Enhanced Learning, Classroom and MOOC environment

Lecture 3:Preprocessing

Lecture 4:Ethics in Learning Analytics, Student Privacy

Week 3: Lecture 1:Intro to Machine Learning

Lecture 2:Supervised and Unsupervised learning

Lecture 3:Regression, Clustering and Classification

Lecture 4:Metrics for ML algorithms –Recall, Precision, Accuracy, F-Score and Kappa

Lecture 5:Demo of ML algorithms using Orange

Week 4:Lecture 1:Descriptive Analytics

Lecture 2:Data Visualization

Lecture 3:Data visualization using Excel

Lecture 4:Dashboard Analytics

Lecture 5:Dashboard of Youtube, MOOC

Week 5:Lecture 1:Intro to iSAT

Lecture 2:iSAT Demo with example

Lecture 3:Diagnostic Analysis

Lecture 4:Correlation

Week 6:Lecture 1:Sequential Pattern Mining

Lecture 2:SPM tool Demo

Lecture 3:Process Mining

Lecture 4:ProM Tool Demo

Week 7: Lecture 1:Predictive Analytics

Lecture 2:Modeling – Feature Selection

Lecture 3:Linear Regression

Lecture 4:Demo of Linear Regression using Weka

Week 8:Lecture 1:Decision Tree

Lecture 2:Demo of Decision Tree using Orange

Lecture 3:Naïve Bayes algorithm

Lecture 4:Demo of Naïve Bayes

Week 9:Lecture 1:Clustering in predictive algorithm

Lecture 2:K-Means clustering

Lecture 3:Demo of K-Means clustering

Week 10:Lecture 1:Text analytics

Lecture 2:Words, Token, Stem and lemma

Lecture 3:Minimum edit distance

Lecture 4:Develop algorithm to automatically grade subjective answers

Lecture 5:Demo of Word embedding

Week 11: Lecture 1:Intro Multimodal Learning Analytics

Lecture 2:Eye-gaze data collection

Lecture 3:Affective computing

Lecture 4:Aligning and analyzing data from Multiple sensors

Week 12:Lecture 1:Advanced topics in LA

Lecture 2:How to apply LA in our class

Lecture 3:Data repos, Research papers to read, and where to present your work

Books and references

The Handbook of Learning Analytics, 1st edition, Charles Lang, George Siemens, Alyssa Wise, Dragan Gašević

Instructor bio

Prof. Ramkumar Rajendran

IIT Bombay

Ramkumar Rajendran is an Assistant Professor in IDP in Educational Technology at Indian Institute of Technology Bombay, Mumbai. He obtained his Ph.D. in Computer Science and Engineering from IITB-Monash Research Academy, IIT Bombay and Postdoctoral training at Vanderbilt University, USA and NEC Central Research Laboratories, Japan

Course certificate

•The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

•The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

• Date and Time of Exams: 20 December 2020, Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

•Registration url: Announcements will be made when the registration form is open for registrations.

• The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

•Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE:

• Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.

• Exam score = 75% of the proctored certification exam score out of 100

•Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75.

•If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

• Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Bombay. It will be e-verifiable at nptel.ac.in/noc.

•Only the e-certificate will be made available. Hard copies will not be dispatched.