• DocumentCode
    183075
  • Title

    Occupation recommendation based on student achievement mining in vocational skill training

  • Author

    Yue Wang ; Xiubang Zhang ; Lilan Nan ; Daling Wang

  • Author_Institution
    Neusoft Corp. Shenyang, Shenyang, China
  • fYear
    2014
  • fDate
    19-21 Aug. 2014
  • Firstpage
    686
  • Lastpage
    691
  • Abstract
    Vocational skill training aims to teach students more knowledge and skills from professional knowledge, general knowledge, practice skill, and behavioral capacity, and plays an important role for the students to obtain employment. In this paper, we propose a practical and effective approach, in which we first analyze the correlation between students´ achievement with their employment situation (i.e. whether they have obtained an employment) according history data. For the data of students obtained employment, we further discover association rules from students´ achievement and concrete occupations by data mining. Moreover, for a new or not obtained employment student, we recommend appropriate occupation for him (her) based on above association rules. Experimental results from a real dataset show the feasibility and effectiveness of our approach.
  • Keywords
    computer based training; data mining; employment; professional aspects; recommender systems; teaching; vocational training; association rules; behavioral capacity; correlation analysis; data mining; general knowledge; occupation recommendation; practice skill; professional knowledge; student achievement; student achievement mining; student employment; student knowledge; student skills; student teaching; vocational skill training; Association rules; Companies; Correlation; Educational institutions; Employment; Training; achievement mining; association rule; correlation analysis; occupation recommendation; vocational skill training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4799-5147-5
  • Type

    conf

  • DOI
    10.1109/FSKD.2014.6980918
  • Filename
    6980918