Bringing Intentional Instruction into the Adaptive Learning Environment

Concurrent Session 4

Session Materials

Brief Abstract

Targeted data analysis can strongly impact student engagement. In this session, participants will learn effective instructional strategies for adaptive learning and how to use data to determine the most effective strategy for faculty to use.


Ginger Walker in an Associate Professor and Lead Faculty of Mathematics at Colorado Technical University. She completed her B.S. in mechanical engineering from the University of Tennessee - Knoxville and then worked in the aerospace industry designing combustors for military jet engines and the space shuttle. She then earned her M.S. in Mathematics from Texas A&M and has taught math and physics for over 20 years, both online and in traditional classrooms, in numerous colleges and universities. One of her instructional goals is to show students that math can be fun, useful, and logical.

Extended Abstract

As learning institutions transition to the adaptive learning environment, faculty and administrators look for ways to enhance interaction with students. The needs of each student engaged in adaptive learning changes from subject to subject and varies across institutions. A tremendous amount of data has now been collected from within the adaptive learning classroom, but the question remains of how to use this information to bring intentional instruction into the classroom. After all, having adaptive learning allows faculty to reach each student individually instead of teaching to the middle.

From an institutional perspective, intentional data analysis can serve to determine whether there is a need for adjustments to the curriculum both in the adaptive learning platform itself and in the non-adaptive learning platform. Is there a decline in performance in one unit over all the others?  If students are historically struggling with certain topics, how can the adaptive learning content be leveraged and enhanced to provide adequate support for those students?  Are the adaptive learning components and regular classroom components sufficiently calibrated to one another?

At CTU, we use the information from our students’ performance data as one guidepost to determine what instructional strategies work well in particular classes. Instructors adjust their plans based on the collected and available data about their students to drive their initial instructional approaches to utilize that session. After receiving the first week’s outcomes, the strategy can be adjusted as necessary. This is a dynamic process throughout the session designed to align to what works best for a particular group of students, which requires flexibility on the part of the instructor. Thus we use this model: track, analyze, change and monitor.

CTU has been able to analyze data from hundreds of sections of courses since its first introduction of adaptive learning into its classrooms, which has given us insight into our students who are taking adaptive learning courses and their needs. That analysis has allowed us to develop an arsenal of instructional initiatives that we have found to be effective for our faculty to use in the classroom. In this presentation, we will discuss some of the methods that we have found to be valuable within the adaptive learning environment.  We will share the parameters that we have found to be the most beneficial to analyze for determining intentional instruction. Then, correlate outcomes to specific pedagogical approaches demonstrating how that particular method will improve student outcomes. Within a single classroom there may be multiple data-informed strategies in order to effectively engage a class roster which contains a very diverse population. These classes are not a homogeneous group where each individual will benefit from the same interventions or approaches. So, in addition to group strategies, we will look at ways to identify at-risk students and create best practices for each of these students individually without overloading faculty.

Choosing the most effective faculty initiatives is vital to the adaptive learning environment. At most postsecondary institutions today, these courses will be facilitated by an adjunct who most likely has other time commitments aside from this job, so it is vital to choose the most efficient use of time of the faculty. Faculty are looking for the best way to help students be successful and in most cases do not have access to the data and rely on others to interpret the data trends.

After discussing these strategies, the audience will receive several sets of sample data to analyze and determine their recommendation for the method of instruction. After they have selected their instructional initiatives, we will then discuss as a group which strategies they chose and the logic behind the decision.

Participants will come away from this presentation with a variety of strategies for using classroom data from adaptive learning platforms to develop effective instructional initiatives and to assess course curriculum. Further, they will be able to identify high-risk students and develop faculty initiatives that would be most apt to encourage student engagement. Participants will also learn to accurately track statistics to determine whether other changes are necessary to bring about successful student outcomes.