Learning Style Preferences of First Year Statistics Undergraduates

dc.contributor.authorTalagala, T.S.
dc.contributor.authorTalagala, P.D.
dc.date.accessioned2015-09-25T04:58:16Z
dc.date.available2015-09-25T04:58:16Z
dc.date.issued2015-09-25T04:58:16Z
dc.date.published2014
dc.description.abstractEveryone learns differently. Learning styles affect on students’ level of performance in many different ways. It is important to assess the learning styles of students in order to cater for their different learning needs. The aim of this study was to determine the learning styles of first year statistics undergraduates and their relation to gender and academic performance. VARK instrument, which categorized learning preferences as visual(V), auditory(A), reading-writing(R), kinesthetic(K) was used to collect data. According to the VARK questionnaire, students were divided into four groups as visual learners, read-write learners, auditory learners and kinesthetic learners. Ward’s hierarchical cluster analysis using binary distance was used to identify clusters, based on students’ responses to thirteen questions in VARK questionnaire. Cluster analysis identified four groups of individuals with similar learning patterns. The repeated measures ANOVA was used to compare the mean level of performance across different leraning styles: visual, aural, kinesthetic and read. According to the results of both VARK classification and cluster analysis it reveals that respondents in all the four clusters have not restricted to a single learning style. Respondents in cluster 1 are bimodal learners while cluster 4 respondents are tri mode learners. In both cluster 1 and cluster 2 the respondents are less sensitive to visual learning mode. The third and fourth clusters represent a more balanced profile with all the learning styles: aural, kinesthetic, read-write and visual. According to the multinomial logistic regression analysis these four clusters differed significantly with respect to their academic performance but the learning styles did not differ between male and female students. These results can be used to facilitate student learning. Moreover, students themselves can use this knowledge to identify their learning habits and that will be very helpful for them to adjust to the new learning environment effectively without wasting much time and energy.en_US
dc.identifier.citationTalagala, T.S., & Talagala, P.D. (2014). Learning Style Preferences of First Year Statistics Undergraduates. International Statistical Conference of Institute of Applied Statistics, Sri Lanka.
dc.identifier.urihttp://dr.lib.sjp.ac.lk/handle/123456789/1903
dc.language.isoenen_US
dc.publisherInstitute of Applied Statistics, Sri Lanka
dc.subjectLearning Stylesen_US
dc.subjectCluster Analysisen_US
dc.subjectBinary Dataen_US
dc.subjectRepeated measures ANOVAen_US
dc.titleLearning Style Preferences of First Year Statistics Undergraduatesen_US
dc.typeArticleen_US

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