Analysis of Science Education Reform Resources on the World Wide Web.
Notice bibliographique
Résumé
Abstract This study analyzed World Wide Web-based K-12 science education resources in the United States using the Science, Technology, and Society (STS) competencies developed from the National Science Education Standards (NRC, 1996). Out of the 51 resources analyzed, only 12% addressed 25% or more of the STS competencies. Twenty percent were aimed at K-12 level, and 10% each at high school and middle grade levels. The study raises concerns about the quality and availability of STS instructional materials on the web in the US, and calls for more research and evaluation in this area of STS education. Science, Technology, and Society (STS) is a reform in science education. STS emphasizes the interactions between science, technology and society (Roy, in press; Hurd, 1991). Making science and technology literacy available for all students, and preparing students to make informed decisions in an increasingly science and technology based global workforce are a few of the major goals of STS (Kumar & Chubin, in press). STS is seen as a promising approach to improving science education in the twenty-first century dominated by technological applications and to address consequent societal issues. STS is part of science education in the United States and several foreign countries such as the United Kingdom, Canada, Japan, China, and Australia. In a national survey, Kumar and Berlin (1996) found that, as of 1993, STS had been a required, recommended, or encouraged part of K-12 science curricula in 38 states in the United States. Nevertheless, an analysis of STS components in state science curriculum frameworks revealed a meager representation (Kumar & Berlin, 1998). [STS competencies from the National Science Education Standards (National Research Council, 1996) were used as a criterion for this analysis.] In a statewide study of STS implementation in Florida, Kumar and Fritzer (1998) found a lack of suitable curriculum resources as one of the reasons why teachers were reluctant to implement STS in science and social studies classrooms. Similarly, the Independent Commission on Environmental Education (1997) noted a lack of science-based instructional resources as one the major problems in environmental education in the United States, as STS often deals with environmental issues. While STS makes its way into science education, strides in high speed hypermedia networks such as the Internet and the World Wide Web (WWW) open up unprecedented opportunities for implementing STS for classroom instruction (Kumar, 1991). In this context, the availability and the quality of STS curriculum resources on the WWW are matters of research interests, and will be analyzed in this paper. Method The study analyzed systematically collected K-12 STS instructional resources on the WWW using the following STS competencies for curriculum analysis developed from the National Science Education Standards (NRC, 1996) and reported in Kumar and Berlin (1998). The STS competencies are: 1. Ability to distinguish between natural objects and objects made by humans; 2. Ability of technological design; 3. Understanding about science and technology; 4. Personal and community health; 5. Characteristics and changes in populations, population growth, resources, and environments; 6. Types of resources and natural resources; 7. Changes in environments; 8. Environmental quality; 9. Risks and benefits; 10. Natural and human-induced hazards; 11. Science and technology in society; 12. Science and technology in local, national, and global challenges; 13. Science as a human endeavor; 14. Nature of science and scientific knowledge; 15. History of science and historical perspectives. Sample The sample for this study consisted of webbased STS instructional resources collected between September and October 1998. …
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 tête enseignante, 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 ».