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Science Students' Document Literacy Skills

2006· article· en· W2766113159 sur OpenAlex

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aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
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Notice bibliographique

RevueeScholarship (California Digital Library) · 2006
Typearticle
Langueen
DomainePsychology
ThématiqueVisual and Cognitive Learning Processes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésScientific literacyMathematics educationConstruct (python library)Test (biology)Variety (cybernetics)Cognitive skillLiteracyPsychologyCognitionTask (project management)Representation (politics)Information literacyComputer scienceScience educationPedagogyArtificial intelligenceEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Science Students’ Document Literacy Skills Silvia d’Apollonia (sdapollonia@place.dawsoncollege.qc.ca) Dawson College and Concordia University 3040 Sherbrooke W., Montreal, QC, H3Z 1A4, Canada Introduction Science students are expected to interpret, reason, and construct charts, graphs, and flow charts in many of their science courses. These are cognitively complex skills, involving interactions among three factors: the cognitive skills of the student, the properties of the graphical representation, and the task demands (Peebles & Cheng, 2003). In most science courses, students are exposed to a variety of graphical representations, but are rarely explicitly taught the underlying structure of such representations. graphs. Moreover, directions. many have difficulty following Table1. Documentary Literacy for College Science Students N The recent advances in graphical technologies have stimulated interest in external cognition (Scaife & Rogers, 1996). Moreover, several instruments (ALLS, IALS, TOWES) measuring document literacy (i.e., the knowledge and skills required by adults to locate and use information from complex documents containing graphical representations such as tables, maps, diagrams, and flow charts) have been developed. Lev Methodology As part of a larger study, investigating students’ co- construction of conceptual understanding of mechanics, we explored students’ document literacy. Subjects Forty-one students (between the ages of 17 and 19) at an urban CEGEP, volunteered to take a document literacy test. Of these, 31 completed the test. Measures Twenty tasks (5 questions assessing each of four levels) were taken from the TOWES (TOWES, 2004). Their written responses were then compared to the answer key provided by TOWES. Students were required to score at least 80% in order to be categorized as achieving each level. Task Characteristics locating a single piece of information by matching the information required with information presented in an identical form; entering a specific piece of information into a given form; locating multiple pieces of information by repeating a limited search. In all tasks there is no ambiguity and students are not required to make any inferences. locating and entering information by comparing the information given and the information required; locating a single piece of information by matching ambiguous information or eliminating distractors; locating multiple pieces of information and making some limited analysis; locating one piece of information using low level inference. . In all tasks students are required to use work with multiple pieces of information and go slightly beyond what is given. comparing and analyzing information from multiple searches from multiple document types; integrating information from different parts of a document or from different document types. integrating and synthesizing information using high-level inferences; locating information in one format and reorganizing it in another format satisfying several conditions Acknowledgments Results and Discussion This research was funded by Programme d'aide a la recherche sur l'enseignement et l'apprentissage and Fonds quebecois de la recherche sur la societe et la culture. Most of the science students had surprisingly low levels of document literacy (see Table 1). More than 90% of the students were only at level 2, indicating that they could only deal with graphical representations which were clear, simple, and/or explicitly described. Although these students have adapted their literacy skills to everyday life, they have great difficulty with many of the reading tasks found in university science courses or in jobs requiring science degrees. Interviews with the students suggest that many students have only a superficial understanding of tables and References Peebles, D., & Cheng, P.C.-H. (2003). Modeling the effects of task and graphical representation on response latency in a graph reading task. Human Factors, 45, 28-45. Scaife, M. & Rogers, Y. (1996). External cognition: how do graphical representations work? Int. J. Human-Computer Studies, 45, 185-213. Towes (2004)http://measureup.towes.com/english/index.asp

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,634
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,000
Communication savante0,0040,005
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,019

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,298
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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