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A Computational Model of School Achievement

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Abstract

The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students’ learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational psychology through computational modeling. For example, prior research has highlighted perplexing inconsistencies in the relationship between time spent on task and academic achievement. The present simulation reveals that even under the assumption that time-on-task always positively contributes to achievement, the correlations between time-on-task and achievement can vary substantially across different contexts and, in some cases, may even be negative. Analysis of the correlation between prior knowledge and knowledge gains uncovers similar patterns. The computational model of school achievement presents a framework, bolstered through simulation, enabling researchers to formalize their assumptions, address ongoing debates, and design tailored interventions that consider both the school environment and individual student contexts.

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... For example, it is important to take into consideration when the information learned will have to be used to decide how much spacing to include, how well the student already understands the concepts, and pivot to interleaving if concepts are being confused. This is still an unfulfilled promise of educational technology, but an important next frontier (Schuetze, 2023). ...
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Cognitive science of learning points to solutions for making use of existing study and instruction time more effectively and efficiently. However, solutions are not and cannot be one-size-fits-all. This paper outlines the danger of overreliance on specific strategies as one-size-fits-all recommendations and highlights instead the cognitive learning processes that facilitate meaningful and long-lasting learning. Three of the most commonly recommended strategies from cognitive science provide a starting point; understanding the underlying processes allows us to tailor these recommendations to implement at the right time, in the right way, for the right content, and for the right students. Recommendations regard teacher training, the funding and incentivizing of educational interventions, guidelines for the development of educational technologies, and policies that focus on using existing instructional time more wisely.
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