Hybrid Education in the Context of the Covid-19 Pandemic: Peculiarities of Training Humanitarian Specialists
Notice bibliographique
Résumé
The global Covid-19 pandemic has changed the established approaches and methods of the educational space. The education system was forced to obey the requirements and regulations implemented by the authorities to prevent spreading infectious diseases. Therefore, the evaluation of the training of humanitarian specialists requires thorough study and analysis. The study aims to consider the components of hybrid education within humanitarian education; to establish students' assessment of hybrid education. The research methodology is based on an integrated approach—the method of pedagogical experiment, statistical methods, and descriptive methods allowed to form an empirical basis. The hypothesis of the study lies in the fact that adaptation to hybrid learning involves the use of digital technologies. They include software, educational platforms, social networks, and tools for non-formal humanitarian education. However, education still requires full-time education and practical experience, which is challenging to obtain virtually. The result of the study determines the effectiveness of hybrid forms of learning using the capabilities of digital technologies for the training of a specialist in the humanities. The study involves: conducting experiments to solve the problem of training humanitarian specialists in the era of the pandemic and researching the right balance between studying at university and home. The primary purpose of such training is to maintain readiness for professional activities, reduce stress among students and teachers, and avoid professional combustion, which has become a fundamental problem of training during a pandemic. The study results made it possible to note that the majority of surveyed students have a positive attitude to the new conditions and methods of organizing the educational process. At the same time, students recognized the advantage of non-formal education. The article proved that the main problem of the implemented education systems for students was the lack of possibility of personal communication "student-student" and "student-teacher". A comparative description of forms of education (classical and hybrid) is provided. The main problem that is not solved by the introduction of hybrid education is the ineffective use of academic support, which is basic for humanitarian specialties. Based on the survey, a decreasing-increasing trend in the attendance of classes according to the mixed form of education was revealed, and the intensity of attendance increases before the final control of knowledge.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».