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Adaptive Learning

I. What is Adaptive Learning?

Adaptive course design is a new way to present personalized, customizable courses using adaptive technology that provides students with a fundamentally different experience than they would have in standard online or hybrid courses.

 


II. How does it work?

Adaptive courses are built within an adaptive platform which houses all of the learning materials, activities, and formative assessments for specific learning units. Based upon a student’s demonstration of learning, they are then automatically directed to the most appropriate content for their current level of understanding. Some students will be directed to proceed to the next lesson or choice of lessons, while others will be guided towards remediation of previous material. The platform is constantly learning about each student’s behavior and performance and providing guidance to help them to attain the learning goals of the course.


III. Benefits of Adaptive Learning


IV.  Using Realizeit Technology

Image of Realizeit LogoThe University of Louisiana at Lafayette Office of Distance Learning is currently assisting instructors in building adaptive courses in the Realizeit software application. Realizeit will integrate into the Moodle grade book and allow for direct linking of coursework with single sign-on for the students, who can purchase an access code from the UL Bookstore. Realizeit is a very robust tool that is used by universities around the country, such as the University of Central Florida, Georgia State University, and Portland State University.

Instructional Designers here at UL Lafayette are trained in the use of this technology and ready to facilitate the implementation of an instructor’s course designs into this innovative platform.


V.  Which courses are a good fit for adaptive learning?

Courses that require students to build a knowledge base or demonstrate a skill that can be measured by objective means are very good candidates for adaptive courseware. Formative assessments within individual lessons that are automatically graded will help the software learn how to measure a student’s understanding of content and the relationships within the content. Courses that fit well into this model include courses that rely heavily on automated grading or courses that feature mainly automated grading components as well as a small number of overarching subjective assignments, such as papers or projects.

Courses that contain no objective learning and rely heavily on subjective assignments, such as forums, research projects, papers, portfolios, etc. would miss out on the redirection and remediation aspects of the software.


VI.  Adaptive Course Design Process

Phase 1: Planning

  1. Identifying Course/Module Learning Objectives
  2. Defining and Aligning Modules and Lessons
  3. Defining Prerequisites

Phase 2: Development

  1. Providing Lesson Content
  2. Creating Activities and Assessments
  3. Finalizing Grading Options and Instructions

Phase 3: Delivery

  1. Defining Due Dates for Modules
  2. Linking Modules to Moodle
  3. Discussing Common Student Issues

 


VII.  Resources

Realizeit
7 Things You Should Know About Adaptive Learning
Realizeit Case Study - University of Central Florida
Affordable Learning Louisiana OER Repository