A novel interaction for competence assessment using micro-behaviors: Extending CACHET to graphs and charts
Data for paper published in: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23)
These files contain:
- The data from the Graph Familiarity questionnaire used in our study (competence assessment using micro-behaviours_Demographic data and questionnaire)
- The interactions produced by our participants on each stimulus (competence assessment using micro-behaviours _interactions on all stimuli)
- All the pauses produced by our participants on each stimulus (competence assessment using micro-behaviours _Pauses)
Paper 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 view- ing 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 In- cremental 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 com- plexity 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.
Funding
Automating Representation Choice for AI Tools
Engineering and Physical Sciences Research Council
Find out more...Automating Representation Choice for AI Tools
Engineering and Physical Sciences Research Council
Find out more...