Improving STEM K-12 Learning Using Optimal Spaced Retrieval in an Existing Educational Technology Platform
Effective Years: 2023-2028
Mastering material in STEM classes requires students to learn and memorize large amounts of new knowledge in a short period of time. One way that has long been argued to improve such learning is by having students practice new knowledge by spacing questions over time (spaced retrieval practice). However, the evidence for the benefits of spaced retrieval practice in STEM contexts is limited. Through multiple classroom studies involving thousands of STEM students across different US middle and high schools, this project aims to understand how spaced retrieval practice improves STEM learning and to develop spacing algorithms specific to STEM education that work in authentic contexts. This research will contribute to a better and more precise implementation of spaced retrieval practice in STEM education.
The project explores how middle and high school learners acquire knowledge using spacing and retrieval practice in the context of STEM education, and which features are critical to yield learning gains. The central hypothesis of this project is that the optimal spaced retrieval practice is adaptive. That is, it depends on each student's study history and what is being learned. Studies 1 and 2 investigate whether spacing practice by topic (regardless of the specific question) is as beneficial as spacing individual questions in at least 25 classrooms. This work will create a high-fidelity student computational model for studies 3 and 4 to investigate the learning and motivational impacts of adaptive spaced retrieval practice schedules implemented in a web-based educational application, compared to a non-optimized non-adaptive version and a frequently used heuristic algorithm for spaced scheduling. Study 5 will leverage these findings in a large-scale classroom study. Studies 2, 4, and 5 will occur in approximately 50 classrooms with over 1200 middle and high-school students. Overall, this project will contribute to a better understanding of learning and how it is sensitive to individual and temporal factors.
This project is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. This project is co-funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.
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.