Memory-related cognitive load effects in an interrupted learning task: A model-based explanation

IF 3.4 Q2 NEUROSCIENCES Trends in Neuroscience and Education Pub Date : 2020-09-01 DOI:10.1016/j.tine.2020.100139
Maria Wirzberger , Jelmer P. Borst , Josef F. Krems , Günter Daniel Rey
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引用次数: 5

Abstract

Background

The Cognitive Load Theory provides a well-established framework for investigating aspects of learning situations that demand learners’ working memory resources. However, the interplay of these aspects at the cognitive and neural level is still not fully understood.

Method

We developed four computational models in the cognitive architecture ACT-R to clarify underlying memory-related strategies and mechanisms. Our models account for human data of an experiment that required participants to perform a symbol sequence learning task with embedded interruptions. We explored the inclusion of subsymbolic mechanisms to explain these data and used our final model to generate fMRI predictions.

Results

The final model indicates a reasonable fit for reaction times and accuracy and links the fMRI predictions to the Cognitive Load Theory.

Conclusions

Our work emphasizes the influence of task characteristics and supports a process-related view on cognitive load in instructional scenarios. It further contributes to the discussion of underlying mechanisms at a neural level.

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中断学习任务中记忆相关的认知负荷效应:基于模型的解释
认知负荷理论为研究需要学习者工作记忆资源的学习情境提供了一个完善的框架。然而,这些方面在认知和神经层面的相互作用仍未完全了解。方法在认知架构ACT-R中建立了四个计算模型,以阐明潜在的记忆相关策略和机制。我们的模型解释了一项实验的人类数据,该实验要求参与者执行带有嵌入式中断的符号序列学习任务。我们探索了包含亚符号机制来解释这些数据,并使用我们的最终模型来生成fMRI预测。结果最终模型显示反应时间和准确性的合理拟合,并将fMRI预测与认知负荷理论联系起来。结论sour的研究强调任务特征的影响,支持了教学情境中认知负荷的过程相关观点。它进一步有助于在神经水平上讨论潜在的机制。
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来源期刊
CiteScore
6.30
自引率
6.10%
发文量
22
审稿时长
65 days
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