Using Adaptive Learning Environments to Overcome Background Deficiencies and Facilitate Mastery of Computer Engineering Content

This paper describes the use of web-based adaptive learning modules to improve student mastery of computer engineering concepts. Adaptive learning is an exciting pedagogical approach that can provide individual instruction to students by dynamically altering the difficulty of content based on an ongoing assessment of the students’ capability. This technique has recently become practical for large groups of students due to advances in course management systems. The computer-based adaptive material can guide a student through a set of incrementally difficult exercises. This has been shown to be nearly as effective as a live instructor guiding the student through the material. What makes computer-administered adaptive learning appealing is that it can reach an expansive student body. This provides a broader reach than can be achieved by instructor-administered guidance, which is limited by the instructor’s availability. Another potential impact of adaptive learning is tailoring the material to the demographics of the students. This can be as simple as the wording used in the problem or posing the problem as a relevant example of interest to a particular student group. This approach has the potential to enhance student perception of the value of the content. This leads to increased content retention and improves student motivation to excel in the course. This paper will discuss the work being conducted at Montana State University in developing and deploying adaptive learning modules at a diverse set of universities to collect data on how different student groups use and are impacted by the materials.