An Eye Movement Study in Unconventional Usage of Different Software Tools.

XAML classic C# cognition load eye-tracking programming

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
08 Apr 2023
Historique:
received: 09 03 2023
revised: 02 04 2023
accepted: 06 04 2023
medline: 1 5 2023
pubmed: 28 4 2023
entrez: 28 4 2023
Statut: epublish

Résumé

One of the main challenges of Human-Computer Interaction is the creation of UIs that enable the use of different systems in an easy and understandable method. The study analyses the student audience who uses software tools differently from the basis. In the research, two languages supporting UI implementation related to .NET technology, XAML and classic C#, were compared in terms of the cognitive load of test subjects. The results of the traditional knowledge level assessment tests and the answers to the questionnaires show that the UI implementation described in XAML is easier to read and understand than the same description in classic C#. When viewing the source codes, the eye movement parameters of the test subjects were also recorded and then evaluated, where a significant difference in the number and duration of fixations was observed, i.e., the interpretation of the classic C# source code showed a larger cognitive load. Overall, the results of the eye movement parameters supported the results of the other two measurement methods when comparing the different types of UI descriptions. The results established in the study and its conclusion may have an impact on programming education as well as industrial software development in the future, and also clearly shows the importance of choosing the development technology that best suits the person or development team.

Identifiants

pubmed: 37112165
pii: s23083823
doi: 10.3390/s23083823
pmc: PMC10145290
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Sensors (Basel). 2022 Jan 25;22(3):
pubmed: 35161659

Auteurs

Jozsef Katona (J)

CogInfoCom Based LearnAbility Research Team, Department of Software Development and Application, Institute of Informatics, University of Dunaujvaros, 2400 Dunaujvaros, Hungary.
Department of Instrumentation and Automation, Institute of Electronics and Communication Systems, Kandó Kálmán Faculty of Electrical Engineering, Obuda University, 1034 Budapest, Hungary.
Department of Computer Science, Electrical Engineering and Mathematical Sciences, Faculty of Engineering and Science, Western Norway University of Applied Sciences, 5063 Bergen, Norway.

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Classifications MeSH