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Discrepancy-Detection in Virtual Learning Environments for Young Children with ASC

机译：ASC幼儿在虚拟学习环境中的差异检测

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This PhD project lays the groundwork for a future VLE that adap-tively introduces discrepancies (i.e. novel or rule-violating occurrences) in order to support young children with autism spectrum conditions (ASC) in practicing foundational social skills. This paper suggests a taxonomy of discrepancy types and briefly summarises a completed analysis of discrepancy-detection in existing video data from 8 children with ASC using the ECHOES VLE. It then describes planned future work, which will explore possible types of discrepancies for exploratory social content (as present in ECHOES) and address other key questions about how they might impact this group of learners, and be incorporated into the design of a future VLE. It also considers how the current work relates to existing literature on metacognition and use of erroneous worked examples in tutoring systems.
机译：该博士项目为未来的VLE打下了基础，该VLE自适应地引入差异（即新颖或违反规则的现象），以支持患有自闭症谱系条件（ASC）的幼儿练习基础社交技能。本文提出了差异类型的分类法，并简要总结了使用ECHOES VLE对来自8名ASC儿童的现有视频数据中差异检测的完整分析。然后，它描述了计划中的未来工作，该工作将探索探索性社交内容可能存在的差异类型（如ECHOES中所述），并解决有关它们如何影响这一组学习者的其他关键问题，并将其纳入未来VLE的设计中。它还考虑了当前的工作与现有的关于元认知和在辅导系统中使用错误的工作示例的文献之间的关系。

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