6 – (L:3 C:6) – AI Data Analytics for Educators: Predictive Outcomes

About Course

Level 3: AI INNOVATOR – AI Roadmap for Educators

Every click, login, and submission a student makes in an LMS (Canvas, Moodle, Blackboard) leaves a data trail. This course teaches faculty how to harness that data using AI. Participants will move from “Descriptive Analytics” (what happened?) to “Predictive Analytics” (what will happen?) and “Prescriptive Analytics” (how can we fix it?). By using machine learning models, educators can identify “at-risk” students with up to 90% accuracy in the first three weeks of a term.

 

Benefits of Attending

  • Early Intervention: Identify struggling students before they fail a major assessment.
  • Curriculum Optimization: See exactly which course materials are being ignored and which lead to mastery.
  • Data-Backed Advocacy: Use hard evidence to request departmental resources or changes in policy.

 

Expected Outcomes

  • A customized “Early Warning System” blueprint for a specific course.
  • Proficiency in using AI to analyze Unstructured Data (e.g., sentiment analysis of forum posts).
  • A “Data Privacy & Ethics” audit for their personal or departmental data use.
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What Will You Learn?

  • Distinguish between different types of educational data (Behavioral vs. Academic).
  • Build and interpret Predictive Models to forecast student grades and retention.
  • Use AI visualization tools (Tableau/Power BI) to create Early Warning Dashboards.
  • Apply ethical frameworks to data mining to prevent "Algorithmic Profiling."

Course Content

Module 1: The Anatomy of Educational Data

  • The Anatomy of Educational Data
    00:00
  • Module 1 Quiz

Module 2: From Descriptive to Predictive Analytics

Module 3: Identifying “At-Risk” Patterns with AI

Module 4: Sentiment Analysis in Forums and Feedback

Module 5: Building Early Warning Dashboards

Module 6: Adaptive Learning and AI Interventions

Module 7: Ethics, Bias, and “The Right to be Forgotten”

Module 8: Capstone — The Student Success Blueprint

Expected Outcomes, Summary, and Conclusions

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