Ability to Consolidate Instances as a Proxy for the Association Among Reading, Spelling, and Math Learning Skill - Marinelli, Chiara Valeria; Angelelli, Paola; Martelli, Marialuisa; Trenta, Mara; Zoccolotti, Pierluigi (Frontiers in Psychology, 2021)
Learning skills (as well as disorders) tend to be associated; however, cognitive models typically focus either on reading, spelling or maths providing no clear basis for interpreting this phenomenon. A recent new model of learning cognitive skills proposes that the association among learning skills (and potentially the comorbidity of learning disorders) depends in part from the individual ability to consolidate instances (taken as a measure of rate of learning). We examined the performance of typically developing fifth graders over the acquisition of a novel paper-and-pencil task that could be solved based on an algorithm or, with practice, with reference to specific instances. Our aim was to establish a measure of individual rate of learning using parameters envisaged by the instance theory of automatization by Logan and correlate it to tasks requiring knowledge of individual items (e.g., spelling words with an ambiguous transcription) or tasks requiring the application of a rule or an algorithm (e.g., spelling non-words). The paper and pencil procedure yielded acquisition curves consistent with the predictions of the instance theory of automatization (i.e., they followed a power function fit) both at a group and an individual level. Performance in tasks requiring knowledge of individual items (such as doing tables or the retrieval of lexical representations) but not in tasks requiring the application of rules or algorithms (such as judging numerosity or spelling through sublexical mapping) were significantly predicted by the learning parameters of the individual power fits. The results support the hypothesis that an individual dimension of “ability to consolidate instances” contributes to learning skills such as reading, spelling and maths, providing an interesting heuristic for understanding the comorbidity across learning disorders.