Improving Online Learning with Interpolated Retrieval

Online learning represents a rapidly growing feature of post-secondary education. According to a recent report from the National Center for Education Statistics, it is estimated that 1 in 7 students enroll exclusively online, and that 1 in 3 students have taken at least one online course, notwithstanding the fact that COVID-19 has forced most education online, at least temporarily. Within the context of online learning, video-recorded lectures represent the primary mode of information delivery, but learning from online lectures is often plagued by bouts of inattention that impede effective learning. This award will allow the researchers to build on their preliminary work demonstrating that breaking long lecture videos into shorter, more manageable segments, and asking students to express what they have learned during these breaks can reliably improve attention and learning. More specifically, the researchers will aim to (1) develop and evaluate a theoretical framework to better understand why it is effective to intersperse video-recorded lectures with brief quizzes, (2) test the generalizability of this behavioral intervention across multiple STEM areas and student populations, including both students who enroll in public universities and in community colleges, and (3) construct evidence-based guidelines around optimal parameters for interspersing video-recorded lectures with brief quizzes

Higher education is increasingly being delivered online, where students are prone to inattention and poor learning outcomes relative to in-person instruction. One technique that supports attention and learning is interpolated retrieval?the act of inserting brief test questions into prolonged sequences of learning. Although substantial empirical data have provided support for its effectiveness, existing research has progressed in the absence of a guiding theoretical framework, without which future research would likely remain limited in scope. In this proposal, the investigators introduce and evaluate an Attention-Integration theoretical framework of interpolated retrieval practice. According to this framework, interpolated retrieval enhances learning via two routes. First, interpolated retrieval increases learners? engagement with and test expectancy for the material, which improves processes associated with attention. Second, interpolated retrieval induces changes in learners? strategy and increases the accessibility of the tested information, which allows learners to meaningfully integrate the contents of study into a coherent mental representation. Four studies will test the critical assumptions of this framework. Studies 1 and 2 are designed to test the attention component of the framework; Studies 3 and 4 are designed to test the integration component of the framework. All four studies will use the same set of materials and similar participant samples, which allows the investigators to conduct a large-scale mediation-moderation analysis at the conclusion of data collection for all studies. This analysis will be instrumental to the refinement and clarification of the interrelations among the various components of the Attention-Integration framework.

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.