Catalyst Project: Investigating Adaptive Hybrid Learning in College Algebra to Improve STEM Engagement and Persistence for HBCU Students

Catalyst Projects provide support for Historically Black Colleges and Universities (HBCU) to work towards establishing research capacity of faculty to strengthen science, technology, engineering, and mathematics (STEM) undergraduate education and research. It is expected that the award will further the faculty member's research capability, improve research and teaching at the institution, and involve undergraduate students in research experiences.

Stillman College outlines an interdisciplinary approach to investigate the combination of Self-Regulated Learning theory, Adaptive Learning Technology, and Culturally Relevant Pedagogy to promote student success in college algebra. Specifically, the major activities include the design of a theory-driven hybrid adaptive college algebra course. The anticipated outcomes are to advance persistence and success in STEM for underrepresented students as HBCUs.

This project is at the forefront of using interdisciplinary research by combining 1) self-regulated learning theory from educational psychology, 2) adaptive learning technology that leverages machine learning and data analytics to produce personalized learning paths and 3) culturally relevant pedagogy coupled with active learning to promote mathematics mastery in college algebra. The research aims of this project are to develop and examine the effectiveness of a novel, theory-driven, hybrid adaptive learning model for college algebra in 3 main areas: 1) academic performance, 2) motivation, self-efficacy, and success expectations, and 3) success in STEM for HBCU students.

The fourth aim is to explore the instructor experience with piloting a theory-driven hybrid adaptive learning model in a college algebra course at an HBCU. A sequential explanatory mixed methods study design will be conducted, where the quantitative phase will include a single group, pretest-posttest design to assess effectiveness of this novel teaching model on student learning and student motivation broadly.

In the follow-up qualitative phase, semi-structured interviews will be conducted with students who are enrolled in this novel college algebra course, as well as the course instructors. Data will be analyzed to assess student learning outcomes and to gain insight on potential barriers to a full-scale implementation at other HBCUs. This study seeks to make a significant contribution in understanding how to innovate with teaching methods at an HBCU and support student learning outcomes in STEM, as well as contribute to the knowledge base by providing more data to improve the machine learning algorithms for adaptive learning platforms.

This project is jointly funded by the Historically Black Colleges and Universities Undergraduate Program and the Established Program to Stimulate Competitive Research (EPSCoR).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.