Predictive Modeling in Learning Analytics

Predictive Modeling in Learning Analytics

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Course
en
English
15 h
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  • 3 Sequences
  • Intermediate Level
  • Starts on August 12, 2018
  • Ends on April 13, 2019

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Course details

Syllabus

Week 1: Prediction

  • Predictive models vs. explanatory models
  • The predictive modeling lifecycle
  • Predictive models of student success
  • Ethical considerations with predictive models
  • Overview of the state of the practice in educational predictive models

Week 2: Supervised Learning

  • Supervised machine learning techniques, including Decision Trees and Naive Bayes

Week 3: Model Evaluation

  • Making predictions
  • Model evaluation and comparison
  • Practical considerations

Prerequisite

We highly recommend that you take the previous course in this series before beginning this course:


This course is intended for those who have a bachelor’s degree and are interested in developing learning and data science skills for employment in education, corporate, nonprofit, and military sectors. Experience with programming and statistics will be beneficial to participants.

Instructors

Christopher Brooks
Research Assistant Professor, School of Information, University of Michigan
University of Michigan

Craig Thompson
Learning Analytics Research Analyst at the Centre for Teaching, Learning and Technology
University of British Columbia

Editor

University of Texas at Arlington

Platform

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