Improving Student Learning with Adaptive Learning Strategies in Competency-Based Curriculum

Nowadays the majority of college students are non-traditional adults who pursue a college degree while having work and family commitments. Competency-based education as an innovative educational model allows students to master new skills relevant to their career goals.  Students work at their own pace and apply what they already know.  This model can result in shorter times and lower costs to graduation for students. While competency-based education is gaining momentum among colleges and universities who aim to deliver a student-centered focus, a common challenge that institutions face is how to create a more personalized learning experience that is engaging as well as tailored to each student’s unique needs. This challenge has become more prominent as institutions have growing number of online students in the competency-based programs with limited faculty support. Students are not satisfied with a “one size fits all” course design approach, as it does not provide them immediate feedback on the progress of their understanding and mastery of the concepts. With dissatisfaction with the learning experience, students are less motivated to complete the course and more inclined to give up the pursuit of the degree.

In order to enhance student’s satisfaction with his/her learning experience, personalized learning and immediate feedback is necessary in course design.  The key to creating personalized learning is through a digital adaptive learning environment. The Education Growth Advisors (EGA) researchers define “adaptive learning” as an approach to creating a personalized learning experience for students that employs "a sophisticated, data-driven, and in some cases, nonlinear approach to instruction and remediation, adjusting to a learner's interactions and demonstrated performance level, and subsequently anticipating what types of content and resources learners need at a specific point in time to make progress”.

There are benefits in adopting adaptive learning strategies in competency-based education. First, competency-based education is a student-centered model that is self-paced. Timely feedback is an important factor that helps direct what students should do with their time and whether they are meeting the expectations. Through advanced technology, an adaptive learning system can track student’s performance on the designed activities, conduct granular data analysis to identify student’s weaknesses, and provide immediate effective feedback to guide students on what they should focus on , which, in turn, frees up instructors to spend more time with students and work with them more individually. Secondly, adaptive learning encourages reflective thinking in student learning. Studies show that students who reflect more on the learning process tend to have better learning outcomes because it helps students become more self-aware. With a “power engine” that can dynamically generate personalized instruction materials, adaptive learning can stimulate and speed up the process by providing reinforcement moments that prompt students to reflect on their progress of mastery of concepts and skills. It helps strengthen a competency-based curriculum where students learning is measured by the demonstration of their mastery of knowledge. Third, adaptive learning in online competency based education promotes self-regulation in student learning with instructional scaffolding. Competency-based learning is self-directed. Adaptive learning strategies provide students with instructional scaffolding to guide students learning, which helps accelerate learning progress with better learning outcomes. This educational method is conducive to competency-based education because adult learners can progress through a course and receive immediate feedback on mastery of skills and knowledge.  Immediate feedback improves engagement and thus, self-motivation and self-efficacy in learners.  Adaptive learning method incites this self-aware or self-monitoring attributes in adult learners where they can adjust their cognitive levels accordingly from the feedback they receive.  Self-regulation plays a significant role in this method based on students’ capacity to self-monitor and progress.  Students can observe their progress through adaptive learning and will adjust their cognitive and affective states according to their level of progress.  Bandura (1986) and Zimmerman (2000) posit that self-regulation is a reciprocal interaction, which involves personal, behavioral and environmental processes.  The environment process of adaptive learning provides students with individualized learning opportunities through formative assessments designed with immediate feedback of scaffolding cognitive levels. 

Western Governors University, an institution with 80,000 students that offers competency-based programs, has adopted the learning platform, Smart Author. Smart Author supports the adaptive learning technology designed by Acrobatiq. The key to effective adaptive learning is to create a strong alignment between the learning outcomes, learning activities and assessments, and instructional content. Developing a Skill Graph that maps what students should know or be able to do to each learning activity and assessment ensures the alignment. Through skill mapping, designers can map questions to different cognitive levels within a formative assessment. The student begins by answering a lower cognitive level question, and then will progress from lower to higher cognitive level questions by providing the correct answer. All learning activities such as knowledge checks and quizzes provide adaptive learning elements.  Learning activities are embedded within the courses to help ensure that students understand and apply the concepts rather than simply memorize facts. Embedded learning activities include “Learn by Doing” and “Did I Get This?” activities. “Learn by Doing” activities are designed to help students practice new skills or develop understanding of a new concept. “Did I Get This” activities are designed to help students assess whether they have mastered a skill or understood a specific concept. Upon completing a learning activity, students receive immediate feedback. The feedback provides more explanation of the context and prompts students to relate to a new situation. As students are doing the activities, the learning analytics tool allows the platform to capture learning data and make a predictive estimate for each student against every learning outcome. Based on their demonstrated skill gaps, the platform generates more instructional scaffolds and personalized practice for each student. The Learning Dashboard collects the entire student learning performance data and generates summaries that help instructors identify where students are succeeding and where they are struggling. It enables instructors to quickly understand students’ learning estimates and make decisions that are more informed on how to help each student succeed.

Some of the undergraduate core courses in the WGU College of Business are designed in Smart Author and implemented with adaptive learning strategies. Based on the data from these courses, the authors of this paper sought to answer the question:  Does adaptive learning within a competency-based education environment affect student outcomes? Our hypotheses on the effectiveness of the adaptive learning strategies are: 1) Students will be more engaged in their learning; and 2) Students will complete the course in a shorter time. To confirm our hypotheses, data on course completion rate and on time progress from these courses will be gathered and compared with the data from the previous course version without the implementation of adaptive learning. Data from Student Satisfaction Survey will also be gathered to see if students’ satisfaction with their learning experience is enhanced.

This education session presentation will reveal the background on adaptive learning, the conceptual framework and theory surrounding the learning experience, and finally the student outcomes in adaptive learning courses within the online competency-based education environment.  Those who will benefit from this presentation include educators in K-12 and Higher Ed institutions as well as those from all levels of expertise.  The session outcomes are as follows: 

1. Authors will present the data they are finding and demonstrate how adaptive learning elements and dashboard works within the platform.
2. Participants will recognize adaptive learning elements and how they are used in a
   competency-based environment.
3. Participants will engage in skill mapping and scaffolding adaptive learning assessments.