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Description
  • In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities.
  • In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities. (en)
Title
  • Predicting Student Performance in Higher Education
  • Predicting Student Performance in Higher Education (en)
skos:prefLabel
  • Predicting Student Performance in Higher Education
  • Predicting Student Performance in Higher Education (en)
skos:notation
  • RIV/00216224:14330/13:00069109!RIV14-MSM-14330___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(LG13010), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 98564
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/13:00069109
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • student performance; recommender system; data mining; social network analysis (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E54C656A7528]
http://linked.open...v/mistoKonaniAkce
  • Prague, Czech Republic
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • 24th International Workshop on Database and Expert Systems Applications - Dexa 2013
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Bydžovská, Hana
  • Popelínský, Lubomír
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1529-4188
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/DEXA.2013.22
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 9780769550701
http://localhost/t...ganizacniJednotka
  • 14330
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