Perceptions of Students from Northwestern Romania on Online Education during the Pandemic COVID-19
Bibliographic record
Abstract
The current spatio-temporal context, in which the didactic activities in our country (Romania) are still carried out, is, beyond its form of social experiment, a form devoid of spiritual content. In the transition from classical to modern, through multimedia technologies, the interactions based on the teaching-learning-assessment activity are severely widowed by the physical lack of those closely involved in the educational system. In such a context, considered to be still cloudy, unsettled, the level of perception of those trained is questioned. Thus, through this study, our emphasis and attention fall on how online education is received, accepted, or not among Romanian students; for the study being interviewed only the students from the third year of study, from various specializations (technical and non-technical), aged over 21-22 years. This study took place between November 2020 and February 2021, on a sample of 463 students. Only students with whom the teachers had contact, who actively participated in online courses, seminars, and laboratories (especially computer-assisted training seminars), participated and were interviewed. The whole debate focused on the students' report on the teaching activity carried out exclusively online. Their answers, under anonymity and voluntary commitment, being an overview, which we decided to present both descriptive (only fragments) and infographics (only a summary of answers).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".