Scientific literacy and contexts in PISA 2006 science
Notice bibliographique
Résumé
International assessments contribute to a greater understanding of science education around the world by helping participating countries understand potential changes in policies, programs, and practices in science teaching.In 2006, science was the primary domain for the Programme for International Student Assessment (PISA), supported by the Organization for Economic Cooperation and Development (OECD) and conducted by the Australian Council for Educational Research (ACER).Compared to the school program orientation of Trends in International Math and Science Study (TIMSS), PISA provides a unique and complementary perspective by focusing on the application of knowledge to science and technology-related life situations.The orientation of PISA is one of scientific literacy, a theme of great importance to the science education community.One question formed the basis for the PISA 2006 Science survey of 15-year-olds-What is important for citizens to know, value, and be able to do in situations involving science and technology?The question is deceptively simple.Answering the question in the form of a framework for an international assessment and a survey that included a test and questionnaires for students and administrators differentiates PISA 2006 Science from other assessments, both international and national.The question and answer also broadens our understanding of the purposes of science education.Several features of the question clarify the uniqueness of PISA 2006 Science.First, the question centers on citizens.As citizens, what scientific knowledge is important?Certainly, basic concepts of the disciplines, but that knowledge must be understood and applied in contexts that individuals encounter in life.At this point we also note that citizens often encounter situations that require some knowledge and understanding of science itself.That is, they need to know something about the processes of scientific inquiry and scientific explanations.Now, and in the foreseeable future, citizens will have to address numerous challenges that are clearly related to science and technology.Contemporary challenges include: Health maintenance and appropriate responses to infectious diseases; for example, applying biomedical advances and responding to H1N1 virus and Swine flu.Natural resources use and appropriate conservation and efficiency use of renewable and nonrenewable energy resources in an increasingly carbon-constrained world; for example, increased use of wind and solar energy.Environmental quality and an appropriate response to global climate change; for example, reduction of carbon emissions through cap and trade agreements.Citizens confront these and other challenges from perspectives that are personal, social, and global.The PISA 2006 Science survey used the contexts displayed in Table 1.Scientific literacy involves more than scientific knowledge.The PISA 2006 Science survey uses contexts to present science in a variety of situations that citizens confront.Assessment tasks had to be part of a 15-yearold's experience.Assessment items were framed with contexts that included the details needed to formulate specific questions.To be clear, the PISA 2006 Science survey was not an assessment of contexts.The primary
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,000 | 0,010 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».