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Learner modeling for adaptive scaffolding in a Computational Thinking-based science learning environment

机译:基于计算思维的科学学习环境中的自适应脚手架学习者建模

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Learner modeling has been used in computer-based learning environments to model learners' domain knowledge, cognitive skills, and interests, and customize their experiences in the environment based on this information. In this paper, we develop a learner modeling and adaptive scaffolding framework for Computational Thinking using Simulation and Modeling (CTSiM)-an open ended learning environment that supports synergistic learning of science and Computational Thinking (CT) for middle school students. In CTSiM, students have the freedom to choose and coordinate use of the different tools provided in the environment, as they build and test their models. However, the open-ended nature of the environment makes it hard to interpret the intent of students' actions, and to provide useful feedback and hints that improves student understanding and helps them achieve their learning goals. To address this challenge, we define an extended learner modeling scheme that uses (1) a hierarchical task model for the CTSiM environment, (2) a set of strategies that support effective learning and model building, and (3) effectiveness and coherence measures that help us evaluate student's proficiency in the different tasks and strategies. We use this scheme to dynamically scaffold learners when they are deficient in performing their tasks, or they demonstrate suboptimal use of strategies. We demonstrate the effectiveness of our approach in a classroom study where one group of 6th grade stu-dents received scaffolding and the other did not. We found that students who received scaffolding built more accurate models, used modeling strategies effectively, adopted more useful modeling behaviors, showed a better understanding of important science and CT concepts, and transferred their modeling skills better to new scenarios.
机译:学习者建模已用于基于计算机的学习环境中,以对学习者的领域知识,认知技能和兴趣进行建模,并基于此信息自定义他们在环境中的体验。在本文中,我们使用模拟与建模(CTSiM)开发了一种用于计算思维的学习者建模和自适应支架框架,这是一个开放式学习环境,支持中学生科学与计算思维(CT)的协同学习。在CTSiM中,学生在建立和测试模型时可以自由选择和协调使用环境中提供的不同工具。但是,环境的开放性使得难以解释学生的行为意图,难以提供有用的反馈和提示,从而增进学生的理解并帮助他们实现学习目标。为了解决这一挑战,我们定义了一个扩展的学习者建模方案,该方案使用(1)CTSiM环境的分层任务模型,(2)支持有效学习和模型构建的一组策略,以及(3)帮助我们评估学生在不同任务和策略上的熟练程度。当学习者缺乏执行任务的能力,或者他们表现出对策略的选择不理想时,我们使用这种方案来动态地支持学习者。我们在课堂研究中证明了我们的方法的有效性,其中一组六年级学生接受了脚手架,而另一组则没有。我们发现接受脚手架的学生建立了更准确的模型,有效地使用了建模策略,采用了更多有用的建模行为,对重要的科学和CT概念有了更好的理解,并将建模技巧更好地转移到了新的场景中。

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