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dc.contributor.authorReid, Clodagh
dc.contributor.authorKieghrey, Conor
dc.contributor.authorDunbar, Rónán
dc.contributor.authorMurray, Niall
dc.contributor.authorBuckley, Jeffrey
dc.date.accessioned2020-03-10T10:24:30Z
dc.date.available2020-03-10T10:24:30Z
dc.date.copyright2019
dc.date.issued2019-06
dc.identifier.citationReid, C., Keighrey. C., Dunbar, R., Murray, N., Buckley, J. (2019). Developing a methodological approach to measure cognitive load during complex problem solving. 37th Pupils' Attitudes Towards Technology Conference: Developing a knowledge economy through technology and engineering education, University of Malta, 3-6 June 2019.en_US
dc.identifier.otherTechnology Education Research Group - Conference Papersen_US
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/3034
dc.description.abstractProblem solving is an important element of engineering and technology disciplines and spatial ability contributes to learners’ success in problem solving in these areas (Wai, et al., 2009). As excessive cognitive load can impede an individual’s capacity to process information (Kirschner, Paas & Kirschner, 2009) it is posited that higher levels of spatial ability may reduce the cognitive load experienced when problem solving and thus support increased learner performance and capacity to learn from problem solving episodes. Based on this hypothesis, there is a need to establish appropriate methods to measure cognitive load in educational contexts. Using Cognitive Load Theory (Sweller, 1988) as a theoretical framework, this paper presents a pilot study of a methodological approach to measure cognitive load experienced in real-time during complex problem solving activities through the use of physiological sensors. Postgraduate students (n=26) were administered the Tower of Hanoi, a complex problem solving task (Eielts et al, 2018). While completing the task, physiological sensors were worn by participants on their non-dominant hand capturing details of electrodermal activity, which is an indicator of cognitive load experienced in real time (Setz, et al., 2010). Subjective data on the levels of cognitive load experienced was also captured following the task, where participants completed a 9-point Likerttype item. The analysis of the data for this study illustrated that through the use of a physiological sensor and application of novel time monitoring software, the electrodermal activity of an individual can provide an insight into their experience whilst problem solving. This approach may present a valid way to capture cognitive data of students throughout authentic problem solving scenarios which would support the determination of variables underpinning success.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.publisherTechnology Education Research Groupen_US
dc.relation.ispartofPATT37 Conference 2019: Developing a knowledge economy through technology and engineering education.en_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/ie/*
dc.subjectCognitive loaden_US
dc.subjectSpatial abilityen_US
dc.subjectProblem solvingen_US
dc.subjectPhysiological sensorsen_US
dc.titleDeveloping a methodological approach to measure cognitive load during complex problem solving.en_US
dc.typeOtheren_US
dc.description.peerreviewyesen_US
dc.identifier.conference37th Pupils' Attitudes Towards Technology Conference: Developing a knowledge economy through technology and engineering education, University of Malta 3-6 June 2019.
dc.identifier.orcidhttps://orcid.org/0000-0002-8593-1730
dc.identifier.orcidhttps://orcid.org/0000-0002-3612-0413
dc.identifier.orcidhttps://orcid.org/0000-0002-0379-1763
dc.identifier.orcidhttps://orcid.org/0000-0003-4199-4753
dc.identifier.orcidhttps://orcid.org/0000-0002-8292-5642
dc.rights.accessOpen Accessen_US
dc.subject.departmentTERGen_US


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Attribution-NonCommercial-NoDerivs 3.0 Ireland
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