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Competence assessment by stimulus matching: an application of GOMS to assess chunks in memory
conference contribution
posted on 2023-06-10, 01:02 authored by Hadeel Bakr M IsmailHadeel Bakr M Ismail, Peter ChengPeter ChengIt has been shown that in hand-written transcription tasks temporal micro-behavioral chunk signals hold promise as measures of competence in various domains (e.g., Cheng, 2014). But data capture under that an approach requires the use of graphics tablets which are relatively uncommon. In this paper we propose and explore an alternative method – Competence Assessment by Stimulus Matching (CASM). This new method uses simple mouse-driven interfaces to produce temporal chunk signals as measures of learner’s ability. However, it is not obvious what features of CASM will produce effective competence measures and the design space of CASM tasks is large. Thus, this paper uses GOMS modelling in order to explore the design space to find factors that will maximize the discrimination of chunk measures of competence. Results of a pilot experiment show that CASM has potential in using chunk signals to measure competence in the domain of English language.
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Publication status
- Published
File Version
- Accepted version
Journal
Proceedings of 19th Internation Conference on Cognitive ModelingPublisher
Society for Mathematical PsychologyPublisher URL
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19th Internation Conference on Cognitive ModelingEvent location
VirtualEvent type
conferenceEvent date
July 1 - July 12, 2021Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-09-21First Open Access (FOA) Date
2021-09-22First Compliant Deposit (FCD) Date
2021-09-21Usage metrics
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