A Latent Profile Analysis of Student Restudy Decisions - under review

Do all learners make the same restudy decisions, or is there heterogeneity within the population? The present study combines three previously published datasets and uses latent profile analysis to determine if subpopulations of learners can be identified that make different restudy decisions. Based on multiple fit indices, cross-validation, and theoretical consideration, a 4-cluster model was selected. Two clusters of learners differentiate items based on their current knowledge focusing on either known or unknown items for restudy, whereas two clusters do not distinguish between known and unknown items and instead choose to restudy almost all or almost known of the items, regardless of whether they were retrieved correctly. Additional auxiliary variable analyses revealed that learners who chose to focus their restudy on unknown information make more accurate restudy decisions than the other clusters. Implications for future exploration of student restudy decisions and the need to explore heterogeneity are discussed.