• No products in the cart.

Learning analytics is the use of data, analysis, and predictive modelling to improve teaching and learning. The purpose of learning analytics is to use data for enhancing learning.

The [course_title] course covers the essential concepts of learning analytics and shows how it is used in various context in education. For example, you will see the use of Learning Analytics in the automated intervention or to inform instructors and to promote scientific discovery.

Instead of these, the course introduces you to the tools and methods you need to know for enhancing learning and securing your students’ privacy and other rights.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

  • Add the certificate to your CV or resume and brighten up your career
  • Show it to prove your success


Course Credit: University of Texas Arlington

Course Curriculum

Module: 01
Archive of ProSolo & Assessment in DALMOOC 00:22:00
Welcome to Week 1 Hangout Archive 00:33:00
Introduction to DALMOOC Topics 00:05:00
Introduction to Learning Analytics 00:07:00
Getting Started With Data Analytics Tools 00:03:00
Week 2 Introduction 00:02:00
The Data / Analytics Cycle 00:07:00
Visualization & Dashboards 00:07:00
Systems-Level Considerations 00:06:00
Tony Hirst Hangout Archive 01:01:00
Module: 02
Jason Schumacher Hangout Archive 00:28:00
Week 2 Hangout Archive 00:30:00
Introduction in Social Network Analysis 00:05:00
Network Structure and Data Sources 00:08:00
Network Measures 00:08:00
Network Modularity and Community Identification 00:06:00
Gephi Community Introduction 00:04:00
Gephi – An Introduction Tour 00:17:00
Gephi – Modularity Analysis 00:11:00
Gephi Modularity Tutorial by Jennifer Golbeck 00:09:00
Shane Dawson Hangout Archive 00:31:00
Module: 03
Week 3 Hangout Archive 00:30:00
Shane Dawson 00:04:00
Jenny McDonald 00:06:00
Week 4 Introduction 00:04:00
Social Network Analysis and Learning Design 00:06:00
Social Network Analysis and Sense of Community 00:05:00
Social Network Analysis and Creative Potential 00:04:00
Social Network Analysis and Academic Performance 00:05:00
Social Network Analysis and Social Presence 00:06:00
Social Network Analysis and Understanding of MOOCs 00:08:00
Module: 04
Results of Analytics of the Data Collected in the First Three Weeks of DALMOOC Hangout Archive 00:31:00
Week 4 Hangout Archive 00:32:00
Zach Pardos 00:06:00
Phil Winne 00:06:00
Regressors 00:09:00
Classifiers (part 1) 00:10:00
Classifiers (part 2) 00:07:00
Case Study in Classification 00:10:00
Cross-Validation and Over-Fitting 00:06:00
Week 5 Hangout Archive 00:19:00
Christopher Brooks 00:04:00
Module: 05
Negin Mirriahi 00:06:00
Behavior Detection Introduction 00:03:00
Ground Truth 00:06:00
Feature Engineering 00:09:00
Diagnostic Metrics: Kappa and Accuracy 00:09:00
Diagnostic Metrics: ROC and A’ 00:09:00
Diagnostic Metrics: Correlation and RMSE 00:11:00
Knowledge Engineering and Data Mining 00:08:00
Over Validity Considerations 00:05:00
Week 6 Hangout Archive 00:30:00
Module: 06
Caroline Haythornthwaite 00:06:00
Tiffany Barnes 00:06:00
Text Mining Introduction 00:14:00
Exploration of Collaborative Learning Process Analysis (research highlight) 00:17:00
Text Mining Conceptual Overview of Techniques 00:14:00
Tools and Resources 00:07:00
LightSIDE: A Quick Tour 00:11:00
Exploration of Student Attitudes in MOOCs (research highlight) 00:15:00
Week 7 Hangout Archive 00:31:00
Janice Gobert 00:06:00
Module: 07
Mykola Pechenizkiy 00:06:00
Data Preparation 00:11:00
Getting a Sense of Your Data 00:08:00
Exploring Basic Text Feature Extraction 00:20:00
Interpreting Feature Weights 00:09:00
Comparing Performance of Alternative Models 00:04:00
Advanced Feature Extraction 00:15:00
Week 8 Hangout Archive 00:30:00
Elle Wang 00:06:00
Week 9 Hangout Archive 00:30:00
Submit Your Assignment 00:00:00
Certification 00:00:00

Course Reviews


8 ratings
  • 5 stars0
  • 4 stars0
  • 3 stars0
  • 2 stars0
  • 1 stars0

No Reviews found for this course.

©2021 Edukite. All Rights Resereved
Edukite is A Part Of Ebrahim College, Charity Commission
Reg No 110841