De la compréhension de programmes en génie logiciel à la reconnaissance d’algorithmes d’apprenants en EIAH

International audienceIn order to assess learners in algorithmics, we suggest a methodbased on the automatic understanding of the algorithms proposed by thestudents using comprehension methods from the domain of the softwareengineering. We use prebuilt models of student’s propositions, each onerepresenting algorithms, organized into tasks and subtasks and documentedwith information and pedagogical characteristics. The mark is based on adistance calculus between the model and the proposition. A first experimentoccurs with exam forms. It gives interesting recognition rates and marks forrecognized forms close to the marks obtained during the exam.Dans le but d’évaluer les productions d’apprenants en algorithmique,nous présentons une méthode de reconnaissance des algorithmes proposés parles apprenants basée sur les techniques de compréhension des programmes dugénie logiciel. Notre méthode repose sur une décomposition des algorithmes entâche et sous-tâche à accomplir ; à associer à chaque sous-tâche des « lignescritiques » et des propriétés spécifiques. Cette décomposition/modélisationpermet l’utilisation des techniques de compréhension de programmes de GénieLogiciel et mène à une évaluation/notation des propositions d’algorithmesbasée sur le modèle identifié d’une base de modèles étiquetés et sur la distanceentre le modèle et la proposition. Une première expérimentation à partir decopies d’examen donne des taux de reconnaissance intéressants et des notespour les copies reconnues proches des notations manuelles

Towards a Distributed Pedagogical Simulator

Abstract. The use of simulation for a pedagogical purpose is very interesting. One of the essential repercussions of the construction of a pedagogical simulator is the perennisation of the ‘know ’ and especially ‘know-how ’ held by the human experts. This deals with an expert system, ` kernel of the simulator´, able to diagnose and detect faults, as well as to describe scenarios of maintenance. Our major concern is to take into account the diversity of the types of knowledge held by the human expert, because they tend to be procedural (functional) or declarative, founded on a confirmed theory or a simple experience lived by the expert. Unfortunately, the more the structures of knowledge are complex, the more it is difficult to choose one of them. This difficulty still increases with the next setting in œuvre. This is really related to the different interactions of this expert system in the architecture of our pedagogical simulator

De la compréhension des programmes dans le génie logiciel à la reconnaissance des algorithmes d'apprenants en EIAH

Conférence EIAH 2015Dans le but d’évaluer les productions d’apprenants en algorithmique, nous présentons une méthode de reconnaissance des algorithmes proposés par les apprenants basée sur les techniques de compréhension des programmes du génie logiciel. Notre méthode repose sur une décomposition des algorithmes en tâche et sous-tâche à accomplir ; à associer à chaque sous-tâche des « lignes critiques » et des propriétés spécifiques. Cette décomposition/modélisation permet l’utilisation des techniques de compréhension de programmes de Génie Logiciel et mène à une évaluation/notation des propositions d’algorithmes basée sur le modèle identifié d’une base de modèles étiquetés et sur la distance entre le modèle et la proposition. Une première expérimentation à partir de copies d’examen donne des taux de reconnaissance intéressants et des notes pour les copies reconnues proches des notations manuelles

Diag-Skills: A Diagnosis System Using Belief Functions and Semantic Models in ITS

International audienceThis work is related to the diagnosis process in intelligent tutoring systems (ITS). This process is usually a complex task that relies on imperfect data. Indeed, learning data may suffer from imprecision, uncertainty, and sometimes contradictions. In this paper, we propose Diag-Skills a diagnosis model that uses the theory of belief functions to capture these imperfections. The objective of this work is twofold: first, a dynamic diagnosis of the evaluated skills, then, the prediction of the state of the non-evaluated ones. We conducted two studies to evaluate the prediction precision of Diag-Skills. The evaluations showed good precision in predictions and almost perfect agreement with the instructor when the model failed to predict the effective state of the skill. Our main premise is that these results will serve as a support to the remediation and the feedbacks given to the learners by providing them a proper personalization

Knowledge Acquisition for Importing Existing Traces to a Trace Base Management System

International audienceTrace Base Management System (TBMS) offers processing and querying functionalities for traces that may be of interest to users of tracked systems. Our goal is to ensure the importing of various external traces into kernel for Trace-Based System (kTBS), which is a TBMS developed in the LIRIS laboratory. To overcome the problem of traces heterogeneity, we propose to define a generic collector. To this end, a user with enough knowledge of the tracked system is prompted to define its kTBS trace model and correspondences between the elements of this model and the elements of the trace to import. The system generalises the mappings previously elicited by the user through interaction to create mapping rules. After this phase, the collector will generate modelled traces from the existing ones and the already defined mapping rules

Knowledge Acquisition for Importing Existing Traces to a Trace Base Management System

International audienceTrace Base Management System (TBMS) offers processing and querying functionalities for traces that may be of interest to users of tracked systems. Our goal is to ensure the importing of various external traces into kernel for Trace-Based System (kTBS), which is a TBMS developed in the LIRIS laboratory. To overcome the problem of traces heterogeneity, we propose to define a generic collector. To this end, a user with enough knowledge of the tracked system is prompted to define its kTBS trace model and correspondences between the elements of this model and the elements of the trace to import. The system generalises the mappings previously elicited by the user through interaction to create mapping rules. After this phase, the collector will generate modelled traces from the existing ones and the already defined mapping rules

Conception et realisation d'un tuteur pour la formation en milieu industriel. Application a la gestion d'un didacticiel cimentier

SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : T 78380 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc