Self-Scheduled Category Learning in College Students

Learning new information can be a complex, gradual process. It is important to understand how learning plays out over time. Research has found that spaced schedules — studying new information in multiple sessions spread out over time — are more effective for learning than massed schedules — studying everything in one long session (Carvalho & Goldstone, 2013; Cepeda et al., 2006, Kornell & Bjork, 2008). However, when people schedule their own learning, they prefer massing (Kornell & Bjork, 2008; Tauber et al., 2013). Recent research suggests another type of schedule, clustering, might be more effective than both massing and spacing. Clustering involves spacing out clumps of massed studying (Slone et al., 2022; Yan et al., 2017). Little research has examined whether people choose to cluster when studying new information. The current study aims to fill this gap by examining how often people cluster their studying when learning new categories, and comparing the effectiveness to massing and spacing. Participants will see exemplars from nine categories (or "families") of alien creatures. Importantly, on each trial participants will choose which family to study next. We will examine which schedule (spaced, massed, or clustered) each participant implemented for learning each family. Participants will then be tested on their ability to correctly classify new creatures. We will examine which schedule(s) produce the best learning. We hypothesize that categories studied with clustered schedules will be learned best because clustering helps learners identify both similarities among family members (when viewed back-to-back as in massing) as well as differences between families (when switching categories as in spacing). Finally, participants will be asked to indicate their preferred learning schedule. We predict that the majority of participants will indicate that massing and clustering are equally effective. Our study has HSRB approval, and we are currently programming the experiment. We will begin collecting pilot data later in the semester.