Using working memory to predict other domains within the learner profiler in an older adolescent sample

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dc.contributor.advisorSchrieff-Brown, Leigh
dc.contributor.authorPetersen, Asheeqa
dc.date.accessioned2026-05-07T12:58:26Z
dc.date.available2026-05-07T12:58:26Z
dc.date.issued2023
dc.date.updated2026-05-07T12:52:13Z
dc.description.abstractLearning difficulties and disabilities (LDD) are the most frequently diagnosed of childhood developmental disorders. In South Africa (SA), however, a standard and nationally accepted tool has not yet been established for assessing LDDs and thus, specific incidence rates are not known. An underlying factor which may be important to consider in the context of LDDs is working memory (WM) which has been reported as playing a crucial role in learning and WM deficits appear to be higher in the context of LDDs. Thus, it may be imperative to adopt, and adapt to, new technologies that are both cost-effective and easily accessible, addressing the gap in resource availability. The Learner Profiler (LP) is an example of one such computerised test, being relatively cost effective and accessible. It should be noted, however, that research on the LP test method is particularly limited due to both a scarcity in the literature and the use of small sample sizes in said literature. The aim of this research was to investigate whether a computerised tool of WM on the LP could predict scores on other computerised cognitive domains on the LP. This quantitative study used a within-subjects experimental design to investigate the predictive value of LP WM module in other LP modules, namely, Visuospatial, Spelling, Missing Word, Word Choice, and New Word Spelling. The sample comprised of 1175 participants aged between 16 to 19 years old. At the time, participants attended a Technical Vocational Education and Training college (TVET) situated in an urban area in Gauteng, SA. The LP modules were administered during normal admissions processes at the college. To assess the predictive value of the LP WM module, the scores of the modules were analysed using multiple regression analyses.
dc.identifier.apacitationPetersen, A. (2023). <i>Using working memory to predict other domains within the learner profiler in an older adolescent sample</i>. (). University of Cape Town ,Faculty of Humanities ,Department of Psychology. Retrieved from http://hdl.handle.net/11427/43201en_ZA
dc.identifier.chicagocitationPetersen, Asheeqa. <i>"Using working memory to predict other domains within the learner profiler in an older adolescent sample."</i> ., University of Cape Town ,Faculty of Humanities ,Department of Psychology, 2023. http://hdl.handle.net/11427/43201en_ZA
dc.identifier.citationPetersen, A. 2023. Using working memory to predict other domains within the learner profiler in an older adolescent sample. . University of Cape Town ,Faculty of Humanities ,Department of Psychology. http://hdl.handle.net/11427/43201en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Petersen, Asheeqa AB - Learning difficulties and disabilities (LDD) are the most frequently diagnosed of childhood developmental disorders. In South Africa (SA), however, a standard and nationally accepted tool has not yet been established for assessing LDDs and thus, specific incidence rates are not known. An underlying factor which may be important to consider in the context of LDDs is working memory (WM) which has been reported as playing a crucial role in learning and WM deficits appear to be higher in the context of LDDs. Thus, it may be imperative to adopt, and adapt to, new technologies that are both cost-effective and easily accessible, addressing the gap in resource availability. The Learner Profiler (LP) is an example of one such computerised test, being relatively cost effective and accessible. It should be noted, however, that research on the LP test method is particularly limited due to both a scarcity in the literature and the use of small sample sizes in said literature. The aim of this research was to investigate whether a computerised tool of WM on the LP could predict scores on other computerised cognitive domains on the LP. This quantitative study used a within-subjects experimental design to investigate the predictive value of LP WM module in other LP modules, namely, Visuospatial, Spelling, Missing Word, Word Choice, and New Word Spelling. The sample comprised of 1175 participants aged between 16 to 19 years old. At the time, participants attended a Technical Vocational Education and Training college (TVET) situated in an urban area in Gauteng, SA. The LP modules were administered during normal admissions processes at the college. To assess the predictive value of the LP WM module, the scores of the modules were analysed using multiple regression analyses. DA - 2023 DB - OpenUCT DP - University of Cape Town KW - Working memory KW - Learner Profiler KW - computer-based testing KW - adolescents KW - South Africa LK - https://open.uct.ac.za PB - University of Cape Town PY - 2023 T1 - Using working memory to predict other domains within the learner profiler in an older adolescent sample TI - Using working memory to predict other domains within the learner profiler in an older adolescent sample UR - http://hdl.handle.net/11427/43201 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/43201
dc.identifier.vancouvercitationPetersen A. Using working memory to predict other domains within the learner profiler in an older adolescent sample. []. University of Cape Town ,Faculty of Humanities ,Department of Psychology, 2023 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/43201en_ZA
dc.language.isoen
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Psychology
dc.publisher.facultyFaculty of Humanities
dc.publisher.institutionUniversity of Cape Town
dc.subjectWorking memory
dc.subjectLearner Profiler
dc.subjectcomputer-based testing
dc.subjectadolescents
dc.subjectSouth Africa
dc.titleUsing working memory to predict other domains within the learner profiler in an older adolescent sample
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMasters
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