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dc.contributor.authorHan, Binglan
dc.contributor.authorWatts, Michael J.
dc.date.accessioned2016-10-10T22:30:56Z
dc.date.available2016-10-10T22:30:56Z
dc.date.issued2016-07
dc.identifier.urihttps://hdl.handle.net/10652/3578
dc.description.abstractThe academic success of international students is crucial for many tertiary institutions. Early predictions of students’ learning outcomes allow for targeted support and therefore improved success rates. In this study, international students’ demographic information, past academic histories, weekly class attendance records, and assessment results in an ongoing course were used to develop models to predict student success and failure in the course on a weekly basis. The prediction models were produced with three decision tree classification algorithms: REPTree, J48 tree, and LMT on the data-mining platform WEKA. Of these, the LMT algorithm has the highest level of accuracy, but the REPTree and J48 models are simpler and easier to interpret. While the accuracies of all three models are above 75%, further research is needed to more accurately predict student failure at early stages.en_NZ
dc.language.isoenen_NZ
dc.subjectAuckland Institute of Studies (AIS) coursesen_NZ
dc.subjectinternational studentsen_NZ
dc.subjectacademic performanceen_NZ
dc.subjecteducational data miningen_NZ
dc.subjectdecision treesen_NZ
dc.subjectassessmenten_NZ
dc.subjectREPTreeen_NZ
dc.subjectJ48 treeen_NZ
dc.subjectLogistic Model Tree (LMT)en_NZ
dc.titlePredicting the academic performance of international students on an ongoing basisen_NZ
dc.typeConference Contribution - Paper in Published Proceedingsen_NZ
dc.rights.holderAuthorsen_NZ
dc.subject.marsden130303 Education Assessment and Evaluationen_NZ
dc.identifier.bibliographicCitationHan, B., & Watts, M. J. (2016, July). Predicting the Academic Performance of International Students on an Ongoing Basis. Michael Verhaart, Emre Erturk, Arron Steele and Scott Morton (Ed.), ITx 2016 CITRENZ New Zealand's Conference of IT (pp.48-53)en_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.institutionAuckland Institute of Studies (AIS)en_NZ
unitec.publication.spage48en_NZ
unitec.publication.lpage53en_NZ
unitec.publication.titleITx 2016 CITRENZ New Zealand's Conference of ITen_NZ
unitec.conference.titleITx 2016 CITRENZ New Zealand's Conference of ITen_NZ
unitec.conference.title29th Annual Conference of the National Advisory Committee on Computing Qualificationsen_NZ
unitec.conference.title7th Annual Conference of Computing and Information Technology Research and Education New Zealand (CITRENZ2016)en_NZ
unitec.conference.orgIT Professionals NZen_NZ
unitec.conference.orgIT Service Management Forum (itSMF) New Zealanden_NZ
unitec.conference.orgNZTechen_NZ
unitec.conference.orgNZRiseen_NZ
unitec.conference.orgHealth Informatics New Zealanden_NZ
unitec.conference.orgAgileDayen_NZ
unitec.conference.orgTelecommunications Users Association of New Zealand (TUANZ)en_NZ
unitec.conference.orgInternetNZen_NZ
unitec.conference.orgTest Professionals Network (TPN)en_NZ
unitec.conference.orgProject Management Institute New Zealand Chapteren_NZ
unitec.conference.orgNew Zealand Open Source Society (NZOSS)en_NZ
unitec.conference.locationWellington, New Zealanden_NZ
unitec.conference.sdate2016-07-11
unitec.conference.edate2016-07-13
unitec.peerreviewedyesen_NZ
unitec.identifier.roms59447en_NZ


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