Process mining analysis of conceptual modeling behavior of novices – empirical study using JMermaid modeling and experimental logging environment.

Previous studies on learning challenges in the field of modeling focus on cognitive perspectives, such as model understanding, modeling language knowledge and perceptual properties of graphical notation by novice business analysts as major sources affecting model quality . In the educational context...

Descripción completa

Detalles Bibliográficos
Publicado en:Computers in Human Behavior Vol. 41; pp. 486 - 504
Autores principales: Sedrakyan, Gayane, Snoeck, Monique, De Weerdt, Jochen
Formato: Artículo
Publicado: Elsevier B.V. Dec2014
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=99828996&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 99828996
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        07475632
        JC4
      jtl: Computers in Human Behavior
      issn: 07475632
      maglogo: N
    pubinfo:
      dt: Dec2014
      vid: 41
      pid: 2410
      pub: Elsevier B.V.
    artinfo:
      ui:
        99828996
        10.1016/j.chb.2014.09.054
      ppf: 486
      ppct: 18
      formats:
      tig:
        atl: Process mining analysis of conceptual modeling behavior of novices – empirical study using JMermaid modeling and experimental logging environment.
      aug:
        au:
          Sedrakyan, Gayane
          Snoeck, Monique
          De Weerdt, Jochen
        affil:
          K.U. Leuven, Faculty of Business and Economics, Department of Decision Sciences and Information Management, Research Center for Management Informatics (LIRIS), Naamsestraat 69, B-3000 Leuven, Office number: HOG 03.114, Belgium
          K.U. Leuven, Faculty of Business and Economics, Department of Decision Sciences and Information Management, Research Center for Management Informatics (LIRIS), Naamsestraat 69, B-3000 Leuven, Office number: HOG 03.118, Belgium
          K.U. Leuven, Faculty of Business and Economics, Department of Decision Sciences and Information Management, Research Center for Management Informatics (LIRIS), Naamsestraat 69, B-3000 Leuven, Office number: HOG 03.122, Belgium
      su:
        Philosophy of education
        Learning
        Empirical research
        Information storage & retrieval systems
        Mathematical models
        Theory
      sug:
        subj:
          Philosophy of education
          Learning
          Empirical research
          Information storage & retrieval systems
          Mathematical models
          Theory
      keyword:
        Conceptual modeling pattern
        Information systems education
        Learning data analytics
        Process mining
        Process-oriented feedback
        Teaching/learning conceptual modeling
        Conceptual modeling pattern
        Information systems education
        Learning data analytics
        Process mining
        Process-oriented feedback
        Teaching/learning conceptual modeling
      ab: Previous studies on learning challenges in the field of modeling focus on cognitive perspectives, such as model understanding, modeling language knowledge and perceptual properties of graphical notation by novice business analysts as major sources affecting model quality . In the educational context outcome feedback is usually applied to improve learning achievements. However, not many research publications have been written observing the characteristics of a modeling process itself that can be associated with better/worse learning outcomes, nor have any empirically validated results been reported on the observations of modeling activities in the educational context. This paper attempts to cover this gap for conceptual modeling. We analyze modeling behavior (conceptual modeling event data of 20 cases, 10.000 events in total) using experimental logging functionality of the JMermaid modeling tool and process mining techniques. The outcomes of the work include modeling patterns that are indicative for worse/better learning performance. The results contribute to (1) improving teaching guidance for conceptual modeling targeted at process - oriented feedback , (2) providing recommendations on the type of data that can be useful in observing a modeling behavior from the perspective of learning outcomes. In addition, the study provides first insights for learning analytics research in the domain of conceptual modeling.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N