From expert to learner metrics of transfer: Examination of how learner perceived similarity predicts transfer and moderates instructional practices

Theories of transfer argue that people are more likely to transfer knowledge to a new scenario the more similar the scenario is to what they have previously learned. However, prior research predominantly relies on expert- or researcher-based judgements of how similar two scenarios are, rather than learner-based similarity metrics. Two studies (N total = 483) with undergraduate students in the United States examined how learner-based similarity judgments relate to transfer. These studies also show how using learner-based metrics can help researchers explore how features of lessons (i.e., the richness of diagrams) influence transfer. Participants sorted the stimuli in the posttest based on their similarity either at the beginning (Study 1) or the end of the study (Study 2). Participants learned about metamorphosis using either perceptually rich or bland life cycle diagrams. After the lesson, they completed a posttest after the lesson and after a month. Both studies showed that participants’ similarity judgments predict transfer. Using this metric also showed that participants were more likely to extend their knowledge to animals similar to the ladybug when they learned with the rich diagram, but to dissimilar animals when they learned with the bland diagram. This was consistent after the one-month delay.