NSF Award
1821189
The low performance and retention of students in STEM classes are often attributed to lack of engagement and motivation. Interactive online learning environments have the potential to engage students and motivate learning, and thus may contribute to increased performance and retention of students in STEM. This project seeks to examine the efficacy of different configurations and design elements in a course platform for interactive, online learning. This platform, OneUp Learning, was previously developed by project team members. The research study will measure the effects of the platform on the engagement and academic performance of students in computer science and data science courses. It is expected that results of this research will lead to better design of online learning environments that support student motivation and contribute to improving undergraduate STEM education.<br/><br/><br/>The research design of this project will be guided by Self Determination Theory, a well-validated psychological theory for understanding motivation and behavior change. The project will pursue three objectives: 1) conduct a series of empirical studies on the application of different elements of the OneUp platform in different learning contexts; 2) extend the OneUp platform by adding new elements to strengthen the platform's social dimension; and 3) develop instructional materials to help faculty use the OneUp platform to develop interactive modules for other courses at the participating institutions. To disseminate the results of these studies, the project team will solicit active community participation, through workshops, crowdsourcing, and related strategies. The project is a collaboration between two institutions, one of which is minority-serving. The partnership between institutions with different student populations will enable exploration of the impact of various platform features on diverse demographic groups.<br/><br/>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.
