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Enregistrement W3217265184 · doi:10.21009/jpud.151.01

Moving Home Learning Program (MHLP) as an Adaptive Learning Strategy in Emergency Remote Teaching during the Covid-19 Pandemic

2021· article· en· W3217265184 sur OpenAlex
Eko Setiawan, Bahroin Budiya

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Notice bibliographique

RevueJPUD - Jurnal Pendidikan Usia Dini · 2021
Typearticle
Langueen
DomaineComputer Science
ThématiqueEducational Methods and Media Use
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDocumentationPandemicPrincipal (computer security)Coronavirus disease 2019 (COVID-19)PsychologyClosure (psychology)Early childhoodMathematics educationMedical educationComputer scienceMedicinePolitical scienceDevelopmental psychologyComputer security

Résumé

récupéré en direct d'OpenAlex

The Covid-19 pandemic had a dangerous impact on early-childhood education, lost learning in almost all aspects of child development. The house-to-house learning, with the name Moving Home Learning Program (MHLP), is an attractive offer as an emergency remote teaching solution. This study aims to describe the application of MHLP designed by early-childhood education institutions during the learning process at home. This study used a qualitative approach with data collection using interviews, observation, and documentation. The respondents involved in the interview were a kindergarten principal and four teachers. The research data were analyzed using the data content analysis. The Findings show that the MHLP has proven to be sufficiently in line with the learning needs of early childhood during the Covid-19 pandemic. Although, the application of the MHLP learning model has limitations such as the distance from the house that is far away, the number of meetings that are only once a week, the number of food and toy sellers passing by, disturbing children's concentration, and the risk of damage to goods at home. The implication of this research can be the basis for evaluating MHLP as an adaptive strategy that requires the attention of related parties, including policy makers, school principals, and teachers for the development of new, more effective online learning models.
 Keywords: Moving Home Learning Program (MHLP), Children Remote Teaching
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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)0,003
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,494
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,067
Tête enseignante GPT0,386
Écart entre enseignants0,319 · 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