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Does Time Matter in Learning? A Computer Simulation of Carroll’s Model of Learning

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 12214)

Abstract

This paper is an exploratory theoretical study of the role of time in learning. We present a computer simulation based on Carroll’s model of school learning. Our aim is to probe some key theoretical questions in educational research: Can all students learn well? If so, under what conditions? What is time’s role in learning achievement? How does time relate to other instructional variables such as student aptitude, student perseverance, and quality of instruction? In our approach we regard learning as a causal system in which a few variables predict and explain different levels of learning. While the simulation is not a causal analysis in the strict sense, it lays some of the groundwork for a fuller causal approach. Our main result confirms the Carroll-Bloom hypothesis that time, as opportunity to learn, is a central variable in learning achievement and also key to closing the achievement gap. We also demonstrate that time, as learner perseverance, accelerates achievement, especially for less prepared students. However, perseverance becomes effective only when the instructional environment surpasses a basic quality threshold. We conclude by considering some implications for designing alternative learning environments, particularly adaptive instructional systems.

Keywords

Time on task Adaptive instructional systems Mastery learning Computer simulation 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Simon InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Apple Inc.CupertinoUSA

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