Can abstraction be used as a unifying guideline to design intelligent educational systems
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
ion appears as a good approach to study educational systems. Firstly, teaching by itself is a complex process, where the educator normally is able to present a given topic in various ways, according to the learners background and goals. Secondly, the domains actually taught vary considerably in range, depending on whether and how they refer to memory, to problem-solving, to behaviours and attitudes, etc. Thirdly, almost all teachable domains vary in complexity, from simple basics to intricate constructs and relatively complex problems to solve. For all these reasons, when a human tutor detects errors or misunderstandings, he usually draws the learners attention on a small subset of the involved knowledge, so that the detected errors and/or misunderstandings can be corrected at the proper abstraction level. 2. Discussion objectives For the discussion, I propose to use abstraction as the unifying guideline for the design of IESs and abstraction levels to formalise this design. Questions to be addressed are: This content downloaded from 207.46.13.76 on Wed, 24 Aug 2016 05:59:29 UTC All use subject to http://about.jstor.org/terms 3 ! How are defined the level(s) at which two modules interact? ! To what extent can educational computer modules be defined only by their specifications, like electrical or electronic circuits are? ! How can be defined the level(s) at which a human teacher and a student interact? ! Can such level(s) be simulated by a computer artefact? Under what conditions? ! Are there different ways to define abstraction, depending on the type of concept, of activity, or of process at hand? Depending on the discussants preferences or interests, such questions can be tackled from two complementary perspectives. One more practical may attempt to define and show how abstraction is or can be used in the design and analysis of various modules or functions of educational systems (see examples in section 5.2, item 4). Another perspective, more theoretical, may consist in defining and formalising some various facets of abstraction, like generalisation, complexity levels, hierarchical organisation of concepts, metalevel descriptions, etc., both within an educational subject domain and in domain-independent studies. Of course, it would be great if the two perspectives were to converge... As a more immediate starting point, I suggest the following approach (although the discussants may elect to proceed otherwise). In a problem-solving domain educational system, one can define four fundamental operating modes (Lelouche & Morin, 1997b), based solely on the students main goal for using the system (either to learn or to assess his learning) and the underlying type of knowledge (either domain knowledge or problem-solving knowledge). Thus we could begin by making explicit the abstraction types and abstraction levels used in these four operating modes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle