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Analysis of Task Difficulty Sequences in a Simulation-Based POE Environment

机译:基于仿真的POE环境中的任务难度序列分析

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Task difficulty (TD) reflects students' subjective judgement on the complexity of a task. We examine the task difficulty sequence data of 236 undergraduate students in a simulation-based Predict-Observe-Explain environment. The findings suggest that if students perceive the TDs as easy or hard, it may lead to poorer learning outcomes, while the medium or moderate TDs may result in better learning outcomes. In terms of TD transitions, difficulty level hard followed by a hard may lead to poorer learning outcomes. By contrast, difficulty level medium followed by a medium may lead to better learning outcomes. Understanding how task difficulties manifest over time and how they impact students' learning outcomes is useful, especially when designing for real-time educational interventions, where the difficulty of the tasks could be optimised for students. It can also help in designing and sequencing the tasks for the development of effective teaching strategies that can maximize students' learning.
机译:任务难度(TD)反映了学生对任务复杂性的主观判断。我们在基于模拟的Predict-Observe-Explain环境中检查了236名本科生的任务难度序列数据。研究结果表明,如果学生认为TD容易或困难,可能会导致学习效果较差,而中等或中等的TD可能会带来更好的学习效果。在TD过渡方面,艰苦程度紧随其后的困难程度可能会导致学习成果变差。相比之下,难度级别为中级然后是中级可能会带来更好的学习效果。了解任务困难随着时间的推移如何表现以及如何影响学生的学习成果非常有用,尤其是在设计实时教育干预措施时,可以为学生优化任务的困难。它还可以帮助设计和排序任务,以开发有效的教学策略,从而最大程度地提高学生的学习能力。

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