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Cue-based facilitation of self-regulated learning: A discussion of multidisciplinary innovations and technologies

机译:基于提示的自我调节学习的便利:关于多学科创新和技术的讨论

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This article discusses the seven contributions to the special issue Facilitation of self-regulated learning. We first introduce the cue-utilization framework to study self-regulated learning; the basic idea of this framework is that learners use whatever cues are available to monitor and control their learning processes. This framework is then used to position, discuss, and critically compare the seven contributions, which represent a wide variety of approaches to self-regulated learning. Based on our analysis, five main conclusions are presented: (1) there is a tendency to focus investigations on learners' monitoring and reflection whereas it might be more fruitful to take the full learning cycle into account, (2) there are strong indications that learners' use cues to regulate their learning but which cues they are actually using depends on many different factors including the type and level of learning, (3) there is a clear need for the provision of metacognitive prompts to learners that stimulate them to use more diagnostic cues and make better control decisions, (4) on the instructional-sequence level, facilitation of self-regulated learning might include 'second-order' scaffolding where the number of prompts decreases as learners acquire more self-regulated learning skills, and (5) affective states may serve as cues but how they interact with cognitive cues is still unknown. We conclude that a design approach to self-regulated learning might help to acknowledge its enormous complexity.
机译:本文讨论了对“促进自我调节学习”这一特殊问题的七个贡献。我们首先介绍提示使用框架来研究自我调节的学习;该框架的基本思想是,学习者使用任何可用的线索来监视和控制他们的学习过程。然后,使用此框架来定位,讨论和批判性地比较这七个贡献,它们代表了多种自我调节学习方法。根据我们的分析,提出了五个主要结论:(1)倾向于将研究集中在学习者的监督和反思上,而将整个学习周期考虑在内可能会更富有成果;(2)有充分的迹象表明,学习者的使用提示来调节学习,但是他们实际使用的提示取决于许多不同的因素,包括学习的类型和水平,(3)显然需要向学习者提供元认知提示,以刺激他们更多地使用诊断提示并做出更好的控制决策;(4)在教学顺序上,促进自我调节学习可能包括“二阶”支架,随着学习者获得更多自我调节学习技能,提示的数量会减少;和( 5)情感状态可能是线索,但是它们如何与认知线索相互作用尚不清楚。我们得出结论,一种自我调节学习的设计方法可能有助于承认其巨大的复杂性。

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