Course / Course Details

Advanced Learning Analytics & Data Science

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    By - Super admin

  • N/A

Eligibility Requirements

Successful completion of Semester 1 and Semester 2 Core Modules.

Course Description

Focuses on extracting actionable insights from learning management system logs, predictive analytics, clickstream data, and student performance metrics to drive retention and efficacy.

Course Learning Outcomes

    • Analyze LMS log data and clickstream telemetry to evaluate learner engagement patterns.
    • Construct predictive models to identify at-risk students and deploy early interventions.
    • Design executive business intelligence (BI) dashboards to visualize institutional learning KPIs.
    • Establish data-driven continuous improvement loops for curriculum optimization.

Course Curriculum

  • 15 chapters
  • 15 lectures
  • 0 quizzes
  • N/A total length
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1 Introduction
10 Min

xAPI, Caliper analytics, and data standards.


1 Introduction
10 Min

Cleaning clickstream and quiz attempt logs.


1 Introduction
10 Min

Completion rates, time-on-task, and drop-off points.


1 Introduction
10 Min

Logistic regression and decision trees for retention.


1 Introduction
10 Min

Item response theory (IRT) and quiz question validity.


1 Introduction
10 Min

Automating personalized study recommendations.


1 Introduction
10 Min

Mapping student peer interactions.


1 Introduction
10 Min

Building PowerBI/Tableau visual dashboards.


1 Introduction
10 Min

Measuring efficacy between alternative teaching methods.


1 Introduction
10 Min

Eye-tracking, video engagement, and biometrics data.


1 Introduction
10 Min

System-wide operational dashboards.


1 Introduction
10 Min

Consent, transparency, and preventing student labeling.


1 Introduction
10 Min

Connecting LMS data to Salesforce and Banner.


1 Introduction
10 Min

Evaluating cost-per-learning gain metrics.


1 Introduction
10 Min

Executing an analytics audit on a live dataset.


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