L’utilisation des textes procéduraux
Lecture, compréhension et exécution d’instructions écrites
Bibliographic Data
| ID | 14815516 |
|---|---|
| Authors | Laurent Heurley, Franck Ganier |
| Year | 2006 |
| Volume | 44 |
| Issue | 2 |
| Pages | 45-62 |
| Publication date | 2006-01-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Intellectica Revue de l Association pour la Recherche Cognitive (JOURNAL) |
| Journal identifiers | ISSN: 0769-4113 • E-ISSN: 2273-9262 |
| Publisher | PERSEE Program (PUBLISHER) |
| DOI | 10.3406/intel.2006.1291 |
| OpenAlex | W2417768246 |
| Language | FR |
| Citations received | 1 |
The Processing of Procedural Texts : Reading, Understanding and Executing Written Instructions. This review presents the main models that have been proposed in cognitive psychology to explain how users follow the directions contained in procedural texts (instructions for use, explanatory leaflets, etc.). This review is organised in two parts. The first part briefly describes the methods used in cognitive psychology to study the process by which procedural instructions are used. The second part presents different models of the use of procedural documents and of the processing of instructions for use. At a global level, the using process (instructions reading, comprehension and execution) can be described as being organised into a series of cycles. Each cycle corresponds to the processing of a few textual segments. At a local level, following instructions can be described as a (direct or indirect) translating process of knowledge into action. This review shows that research dealing with the processing of procedural texts still requires specific modelling
Cognition · Cognitive psychology · Cognitive science · Comprehension · Knowledge base · Linguistics · Natural language processing · Procedural knowledge · Programming language · Reading comprehension · Text processing · Computer Science · Innovative Teaching and Learning Methods · Intelligent Tutoring Systems and Adaptive Learning · Linguistics and Discourse Analysis · Psychology · Artificial Intelligence
| Citations per year | 0.17 |
|---|---|
| Citation span | 2020 - 2020 (1) |
| Highly cited | No |