A novel interaction for competence assessment using micro-behaviors:: Extending CACHET to graphs and charts

Fiorenzo Colarusso, P. Cheng, Grecia Garcia Garcia, Aaron Stockdill, Daniel Raggi, M. Jamnik
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引用次数: 1

Abstract

Competence Assessment by Chunk Hierarchy Evaluation with Transcription-tasks (CACHET) was proposed by Cheng [14]. It analyses micro-behaviors captured during cycles of stimulus viewing and copying in order to probe chunk structures in memory. This study extends CACHET by applying it to the domain of graphs and charts. Since drawing strategies are diverse, a new interactive stimulus presentation method is introduced: Transcription with Incremental Presentation of the Stimulus (TIPS). TIPS aims to reduce strategy variations that mask the chunking signal by giving users manual element-by-element control over the display of the stimulus. The potential of TIPS, is shown by the analysis of six participants transcriptions of stimuli of different levels of familiarity and complexity that reveal clear signals of chunking. To understand how the chunk size and individual differences drive TIPS measurements, a CPM-GOMS model was constructed to formalize the cognitive process involved in stimulus comprehension and chunk creation.
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一种利用微行为进行能力评估的新型交互:将CACHET扩展到图形和图表
基于转录任务的Chunk Hierarchy Evaluation with transcriptional -tasks (CACHET)能力评估方法由Cheng等人提出。它分析在刺激观察和复制周期中捕获的微行为,以探测内存中的块结构。本研究将CACHET扩展到图形和图表领域。由于绘制策略的多样性,提出了一种新的交互式刺激呈现方法:刺激增量呈现转录(TIPS)。TIPS旨在通过让用户对刺激的显示进行逐个元素的手动控制,减少掩盖分块信号的策略变化。通过对六名参与者不同熟悉程度和复杂程度的刺激转录的分析,揭示了组块化的清晰信号,表明了TIPS的潜力。为了了解块大小和个体差异如何驱动TIPS测量,我们构建了CPM-GOMS模型来形式化涉及刺激理解和块创建的认知过程。
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