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Testing cognitive loads in solving algorithmic tasks

机译:在解决算法任务中测试认知负载

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In their work, educators are increasingly relying on the knowledge of information processing mechanisms such as perception, attention or memory to explain the processes involved in learning and teaching. This article discusses the results of eye tracking experiments on external cognitive load (related to perception or attention control) when solving algorithmic tasks. The analysis of eye tracking indicators has determined which factors reduce the cognitive effort. However, there were no significant differences in the parameters analyzed, which led to the assertion that the distracters presented in the task did not increase the cognitive load, which may indicate that in the case of difficult tasks, the internal cognitive load plays a dominant role. It was noted that the low efficiency of solving algorithmic tasks constitutes a major impediment to statistical inference.
机译:在他们的工作中,教育工作者越来越依赖于信息处理机制,例如感知,注意力或记忆,以解释学习和教学的过程。本文在解决算法任务时讨论了对外部认知负荷(与感知或注意力控制相关)的眼睛跟踪实验的结果。眼跟踪指标的分析确定了哪些因素降低了认知努力。但是,分析的参数没有显着差异,这导致了任务中呈现的干扰因素没有增加认知负载,这可能表明在困难的任务的情况下,内部认知负荷起到了主导作用。注意,求解算法任务的低效率构成了统计推理的主要障碍。

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