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User-adaptive explanatory program visualization: evaluation and insights from eye movements

机译:用户自适应的解释程序可视化:眼动的评估和见解

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摘要

User-adaptive visualization and explanatory visualization have been suggested to increase educational effectiveness of program visualization. This paper presents an attempt to assess the value of these two approaches. The results of a controlled experiment indicate that explanatory visualization allows students to substantially increase the understanding of a new programming topic. Furthermore, an educational application that features explanatory visualization and employs a user model to track users' progress allows students to interact with a larger amount of material than an application which does not follow users' activity. However, no support for the difference in short-term knowledge gain between the two applications is found. Nevertheless, students admit that they prefer the version that estimates and visualizes their progress and adapts the learning content to their level of understanding. They also use the application's estimation to pace their work. The differences in eye movement patterns between the applications employing adaptive and non-adaptive explanatory visualizations are investigated as well. Gaze-based measures show that adaptive visualization captivates attention more than its non-personalized counterpart and is more interesting to students. Natural language explanations also accumulate a big portion of students' attention. Furthermore, the results indicate that working memory span can mediate the perception of adaptation. It is possible that user-adaptation in an educational context provides a different service to people with different mental processing capabilities.
机译:已经建议用户自适应可视化和解释性可视化以提高程序可视化的教育效果。本文提出了评估这两种方法的价值的尝试。受控实验的结果表明,解释性的可视化使学生能够大大提高对新编程主题的理解。此外,与不遵循用户活动的应用程序相比,具有解释性可视化功能并采用用户模型来跟踪用户进度的教育应用程序使学生可以与大量材料进行交互。但是,找不到两个应用程序之间的短期知识获取差异的支持。尽管如此,学生们还是承认他们更喜欢这样一种版本,它可以估算并可视化他们的进度,并使学习内容适应他们的理解水平。他们还使用应用程序的估算来调整工作进度。还研究了采用自适应和非自适应解释性可视化的应用程序之间的眼睛运动模式差异。基于凝视的测量表明,自适应可视化比非个性化可视化更吸引人的注意力,并且对学生更有吸引力。自然语言的解释也积累了很大一部分学生的注意力。此外,结果表明工作记忆跨度可以介导适应感。教育环境中的用户适应可能会为具有不同心理处理能力的人们提供不同的服务。

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