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.