Please use this identifier to cite or link to this item: https://hdl.handle.net/1822/66931

TitleDevelopment and validation of a descriptive cognitive model for predicting usability issues in a low-code development platform
Author(s)Silva, Carlos César Loureiro
Vieira, Joana
Campos, José C.
Couto, Rui
Ribeiro, António Nestor
Keywordsend-user development
low-code development platforms
descriptive cognitive models
usability
human-computer interaction
Issue date2021
PublisherSAGE Publications Inc
JournalHuman Factors
CitationSilva, C., Vieira, J., Campos, J. C., Couto, R., & Ribeiro, A. N. (2021). Development and Validation of a Descriptive Cognitive Model for Predicting Usability Issues in a Low-Code Development Platform. Human Factors, 63(6), 1012–1032. https://doi.org/10.1177/0018720820920429
Abstract(s)ObjectiveThe aim of the study was the development and evaluation of a Descriptive Cognitive Model (DCM) for the identification of three types of usability issues in a low-code development platform (LCDP).BackgroundLCDPs raise the level of abstraction of software development by freeing end-users from implementation details. An effective LCDP requires an understanding of how its users conceptualize programming. It is necessary to identify the gap between the LCDP end-users' conceptualization of programming and the actions required by the platform. It is also relevant to evaluate how the conceptualization of the programming tasks varies according to the end-users' skills.MethodDCMs are widely used in the description and analysis of the interaction between users and systems. We propose a DCM which we called PRECOG that combines task decomposition methods with knowledge-based descriptions and criticality analysis. This DCM was validated using empirical techniques to provide the best insight regarding the users' interaction performance. Twenty programmers (10 experts, 10 novices) were observed using an LCDP and their interactions were analyzed according to our DCM.ResultsThe DCM correctly identified several problems felt by first-time platform users. The patterns of issues observed were qualitatively different between groups. Experts mainly faced interaction-related problems, while novices faced problems attributable to a lack of programming skills.ConclusionBy applying the proposed DCM we were able to predict three types of interaction problems felt by first-time users of the LCDP.ApplicationThe method is applicable when it is relevant to identify possible interaction problems, resulting from the users' background knowledge being insufficient to guarantee a successful completion of the task at hand.
TypeArticle
URIhttps://hdl.handle.net/1822/66931
DOI10.1177/0018720820920429
ISSN0018-7208
Publisher versionhttps://journals.sagepub.com/doi/10.1177/0018720820920429
Peer-Reviewedyes
AccessOpen access
Appears in Collections:HASLab - Artigos em revistas internacionais

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