Different Flavors of Adaptive and Personalized Learning

Audience Level: 
All
Session Time Slot(s): 
Institutional Level: 
Higher Ed
Streamed: 
Onsite
Abstract: 

How do you address the challenges in your classroom with students of diverse backgrounds and customize learning? Adaptive and personalized learning play a major role to address these challenges. We will present different approaches and technologies we used at the NC State University to incorporate adaptive learning in course design.

 
Extended Abstract: 

Overview and Background

The goal of this session is to share the processes and solutions on designing online adaptive or personalized learning modules using a selected adaptive learning platform or technology to address students with diverse backgrounds and knowledge gaps. It can be difficult and challenging to meet the learning needs of every student in the classroom. Based on the level of knowledge and competency, students can be labeled as advanced, intermediate and beginner in a classroom. How do you make the students feel that they are not wasting their time on something they already know? How do you make the students feel that the course is not too fast paced, and not giving them enough instructional materials that they might need?

Adaptive learning is an online framework for delivering material in an individualized way based on student mastery and performance. It can provide customized feedback, offer remedial pathways to prerequisite material, and show how the concepts across the curriculum are interconnected. I will discuss a few projects that I worked on over the past few years to incorporate adaptive learning and personalized learning in our course design projects.

Learning Objectives

At the end of this session, the audience will be able to:

  • Learn how to design and adaptive or personalize learning module from conception to completion
  • Differentiate between large scale complex adaptive learning and small scale adaptive learning design process
  • Recognize the instructional challenges of designing an adaptive learning module 
  • Learn the basics about commercial adaptive learning platforms and elearning software used in these projects 
  • Learn how Moodle tools and activities can be used to develop adaptive learning modules inside the learning management system
  • Apply strategies for designing an adaptive learning cycle to their own course or training modules 

The “Engineering Spine”

One of the latest projects I worked on  proposed  to develop an adaptive learning experience for the mechanics sequence, using MAE 208: Engineering Dynamics as the primary course, and embedding prerequisite material from PY 205: Physics for Engineers and Scientists and  MAE 206: Engineering Statics. This was a very large scale project involving multiple stakeholders. 

To better support learners with different levels of concept mastery and diverse prerequisite knowledge levels, North Carolina State University team has collaborated with the UNC System Office of Digital Learning Initiative to develop adaptive learning modules for interconnected engineering mechanics courses from PY 205 (Physics for Engineers and Scientists) through MAE 206 (Engineering Statics) and MAE 208 (Engineering Dynamics) creating an “Engineering Spine”. These adaptive learning modules are now being used to support students at multiple Universities to improve student success, and illustrate a strategy for rapidly scaling adoption of adaptive learning across the UNC System. At the NC State University,  this was our first initiative using a commercial adaptive learning platform Realizeit. I will discuss the project management, instructional design process and the challenges for this project. 

ST 370: Probability and Statistics for Engineers

Another major  focus of this session is to discuss the process of designing an adaptive learning module for a large undergraduate Statistics course, ST 370: Probability and Statistics for Engineers. This course is taken by approximately 1000 students each year at North Carolina State University. One of the major challenges when teaching this course is students with different statistical backgrounds and requiring different real-world applications based on their major. The  redesign goals involve switching to a hybrid class structure that makes use of adaptive learning modules. The project started with a lot of sketches, brainstorming sessions, and at the end, developing a full cycle adaptive learning module wireframe. It is also critical to decide what technology should be used and conduct a comparative and feasibility analysis before diving into the development process. In this project, adaptive modules were developed using Articulate Storyline 360. These modules begin with a pre-quiz to test the skill level for the current topic of each student. Based on the students’ performance, these modules branch out to different learning paths. Students go through additional materials on the topic as the remedial content for better understanding. This is a very small scale adaptive learning design applied to  very specific topics.

Moodle and Adaptive Learning

At the end, I will discuss how we can use some Moodle tools to implement adaptive and personalized learning. Moodle settings, activities, and resources can be combined to create adaptive learning experiences in a course that could be very efficient and cost-effective. At NC State University, we are now exploring these tools and testing their capabilities.  

Audience Engagement

We will engage the audience in discussion and online polling using online tools. We will ask questions to the audience throughout our presentation and participate in team activities. The presentation will include a combination of discussion and engagement with the audience to  identify a course context for designing an adaptive learning module, and come up with some branching scenarios and technologies that might help them implement adaptive learning in their own projects. The audience will be asked to apply those strategies in their selected course topics, solve, and share their ideas as a group.

 
Position: 
5
Conference Session: 
Concurrent Session 5
Conference Track: 
Instructional Design
Session Type: 
Discovery Session
Intended Audience: 
All Attendees