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

要旨

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.

著者
Fiorenzo Colarusso
University of Sussex, Brighton, United Kingdom
Peter Cheng
University of Sussex, Brighton, United Kingdom
Grecia Garcia Garcia
University of Sussex, Brighton, United Kingdom
Aaron Stockdill
University of Sussex, Brighton, United Kingdom
Daniel Raggi
University of Cambridge, Cambridge, United Kingdom
Mateja Jamnik
University of Cambridge, Cambridge, United Kingdom
論文URL

https://doi.org/10.1145/3544548.3581519

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Learning and Education

Hall F
6 件の発表
2023-04-27 18:00:00
2023-04-27 19:30:00