INVOLVEMENT LOAD HYPOTHESIS PLUS

Abstract The present meta-analysis aimed to improve on Involvement Load Hypothesis (ILH) by incorporating it into a broader framework that predicts incidental vocabulary learning. Studies testing the ILH were systematically collected and 42 studies meeting our inclusion criteria analyzed. model-selection approach was used determine optimal statistical model (i.e., set of predictor variables) best learning gains. Following previous findings, we investigated whether prediction improved (a) examining influence each level individual components (need, search, evaluation), (b) adopting operationalization test format grouping, (c) including other empirically motivated variables. Results showed resulting models explained greater variance in Based models, created formulas. Using these formulas, one can calculate effectiveness index activities predict their relative more accurately