Do Students Really Want Learning to Be Adaptive?

Concurrent Session 6
Streamed Session

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Brief Abstract

This presentation will concentrate on students' evaluation of their adaptive learning experience with the RealizeIT platform at the University of Central Florida (UCF).

Extended Abstract

Of the current innovations in higher education, adaptive learning appears to offer potential at many levels. By giving students the ability to follow individual learning paths disparities in, educational background, prior knowledge, proficiency levels and intermediate benchmarks can be accommodated by adaptive systems that learn how students learn. While the theory and concepts of adaptive learning are not new, the technologies that facilitate the implementation of the process are relatively recent and emerging rapidly. In a number of ways adaptive learning is causing us to rethink the structure of higher education and the way in which we conduct research that will produce meaningful results. Research on adaptive learning is evolving into a learning space where the information sequence is: data, information, insight and action.

Because adaptive learning is stressing the current structure of education--including the most recent developments such as online and blended learning--many outcomes are being scrutinized (for instance, success, withdrawal, learning outcomes, engagement, student and faculty satisfaction, difficulties with the approach, programmatic concerns, scalability, early alert and dropout prevention.)

Of those many variables this presentation will concentrate on students' evaluation of their adaptive experience with the RealizeIT platform in psychology, nursing and mathematics at the University of Central Florida (UCF). Data were collected by the Research Initiative for Teaching Effectiveness via a validated data collection protocol that will be shared with the session participants. Currently, several universities are using the questionnaire developed at RITE. The issues addressed in this presentation will focus on students' reactions to adaptive learning including their perceptions of whether the learning was effective, they would take additional courses in the format, the platform was easy to use, the learning was actually personalized, the grading was accurate, they were engaged in their learning, their system reported ability estimates were accurate, the system reported learning measures were valid and the course feedback was effective.

Several statistical procedures were used in the analysis including computation of the response distribution moments, principal components, computation of components' scores, and smallest space analysis. The results of analyses suggests that:
1. Students experienced minimal difficulty with the adaptive learning platform itself,
2. Adaptive feedback was effective for them,
3. The reported system ability and growth levels were accurate,
4. The system was effective at personalizing students' learning paths,
5. Adaptive learning increased students' learning engagement,
6. Students were favorable toward taking additional adaptive courses,
7. Students interacted less with their fellow classmates in the adaptive system,
8. Students felt minimal need to interact with their fellow classmates,
9. The organization of RealizeIT was effective,
10.The course format was a challenge,
11.The underlying pattern of student reaction to adaptive learning included an effective learning climate, engagement efficacy and facilitation of learning, and
12.Students related to adaptive learning in terms of learning climate and engagement.

We will discuss these findings with the audience and share the survey instrument and research design for our evaluation of adaptive learning. Future research will be discussed as well as how the audience can evaluate adaptive learning at their institution.