Notice bibliographique
Résumé
E-learning in Indonesia began in mid-nineties with the advent of internet preceded by information technology which was introduced in Indonesia in late 1970s and early19 80s. However, those elearning initiators hit hard by the economic and political crises which hit Indonesia in 1997s until early 21st century. Beginning the year 2000, many schools, especially senior high school, took the initiatives to conduct e-learning in their environments, in spite of the economic crises. Based on data available from the Department of national Education, a survey conducted toward high school Websites. A virtual visit and randomly selected physical visits to high schools situated in Jakarta, Yogyakarta (Central Java), Makassar (South Sulawesi) and Padang(West Sumatera) yielded result that those Websites mainly used for disseminating school profiles including name and address, principals and teaching staffs, facilities, extracurricular works etc, but none specially directed to e-learning materials. The research orientation changed to vocational high school with the assumption that the vocational high school graduates are geared toward working market hence the courses are directed to more practical application and subsequently can improved with e-learning activities. Based on data from National Library of Indonesia and Directorate of Vocational High School, purposive sampling was done. The criteria are (a) the school has conducted e-learning for at least five years; (b) agree to be interviewed; (c) has trained other schools on e-learning development; (d) own a school library (e) appointed by Directorate of Vocational High School as a pilot project (f) accessible economically from Jakarta so it is more convenient to visit. Using snowball method, from interview with Wikrama principal and teachers, yielded data on other vocational schools in many regions. Those vocational high schools are randomly selected, interviewed by volunteer researchers . The results are analysed and showed that e-learning in vocational high school is limited to facilities designed by the school such as commonly found in Intranet, the constraints mainly on physical infrastructure and e-learning spread because of lack of facilities from school library. The development of e-learning activities is separated from school library, a cause resulted from the wrong perception of the school principals. It is suggested that the development of e-learning should synchronised with school library because in the future, even right now, school library will developed into learning resource centres, in which e-learning is covered. However, it needs better understanding among school principals which in Indonesia who will decide the fate of school library, either like it or not.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 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 ».