NEP 2020 : reversing the trend of brain drain from elite schools of India?
Notice bibliographique
Résumé
The yearning for high quality education and better employment opportunities has compelled millions of bright and talented Indian students to explore better prospects overseas for years. Several studies indicate that in the last two decades, more than half of the high school toppers have left the country to countries such as UK, USA and Canada because of the many push factors in India. To crackdown this trend, India has recently proposed few transformative re-forms in the National Education Policy( NEP 2020) \n \nThe purpose of this thesis was to investigate whether the NEP 2020 reforms in higher education would limit brain drain from elite schools of India. The response of guidance counsellors from elite private schools of India was used to gather the primary data for this study. Based on the theoretical framework, previous studies on human capital, student mobility and guidance counselling were examined. The research questions were selected on the basis of the theoretical study related to education policies in higher education and their link to human capital theory and international student mobility. In addition, guidance counselling theories were included to understand counselling practices in students’ transition to tertiary education. As the study was commissioned by an EdTech company which provided support for college counselling, the study also explored if the current features in their tool was equipped to handle the new demand for Indian universities in light of the reforms in NEP 2020. \n \nThe research involved collecting data using a survey and group interview of counsellors and for this sequential mixed method was adopted. Quantitative data was collected by surveying counsellors with close ended questions while qualitative data was gathered by interviewing counsellors with semistructured questions. 47 counsellors from elite schools of India participated in the survey. Further clarification was sought to gather deeper insights on the future trends in Indian student mobility by interviewing three of these counsellors. Overall, the results indicate that, the brain drain is most likely going to reverse because of the reforms proposed in NEP 2020 and as a result the country stands to benefit eventually from the human capital gain. However, further research is required to determine other externalities which could influence student mobility trends.
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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 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 ».