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.

Any interested learners
Course Status : Completed
Course Type : Elective
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 subjected 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.

• 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

•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.

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