Int. J. of Learning Technology   »   2014 Vol.9, No.1

 

 

Title: Diagnosing knowledge using learning activity traces generated by various problem-solving modalities

 

Authors: Sandra Michelet; Vanda Luengo; Jean-Michel Adam; Nadine Mandran

 

Addresses:
ACTION ON LINE, zLe Contemporain, 52 chemin de la Bruyère, 69574 Dardilly, France
LIG – MeTAH team, Domaine Universitaire de Saint-Martin d'Hères, 11 rue des mathématiques – BP 53 – 38041 Grenoble cedex 9, France
LIG – MeTAH team, Domaine Universitaire de Saint-Martin d'Hères, 11 rue des mathématiques – BP 53 – 38041 Grenoble cedex 9, France
LIG – MeTAH team, Domaine Universitaire de Saint-Martin d'Hères, 11 rue des mathématiques – BP 53 – 38041 Grenoble cedex 9, France

 

Abstract: Learners work increasingly with a large panel of learning environments that involve them in various activities thanks to a number of tools. These tools generate activity traces, which must then be taken into consideration and combined so as to establish the most accurate diagnosis about the learner's activity. This paper presents a diagnosis model, called DiagElec. This model considers traces generated by various independent tools. DiagElec integrates a notion of uncertainty in the diagnoses that it generates thanks to the notion of 'degree of belief' which is defined by the rules of the diagnosis. To evaluate our model, we carried out a two-phase experiment, first with learners and then with teachers. From the corpus of diagnoses compiled by the teachers, we look for the emergence of a model of human behaviour in order to ascertain whether or not it is necessary to readjust the degree of belief defined by the rules of the diagnosis.

 

Keywords: diagnosis modelling; problem solving modalities; PSM; data mining; learning activity traces; learner activities; uncertainty; degree of belief; human behaviour.

 

DOI: 10.1504/IJLT.2014.062449

 

Int. J. of Learning Technology, 2014 Vol.9, No.1, pp.67 - 90

 

Available online: 05 Jun 2014

 

 

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