The Impact of Media Culture on Future Professionals’ Training
Bibliographic record
Abstract
The relevance of the research is substantiated by the fact that the information society can be addressed as a stage in the modern civilization formation, which is characterized by the increasing role of knowledge, information, as well as information processing technologies. The number of people employed in the information sphere is growing steadily. The information products and information services are gaining additional shares in the market. It is specifically the prerequisites for a future specialist to have high media and cultural competence to tackle current challenges. The research aims to ascertain experimentally the pedagogical conditions for media culture formation and its impact on future professionals’ training. The study was conducted using such tools as questionnaires and testing. Diagnosis of cognitive interest (according to N. Kuzmina’s scale), the scale for assessing students' operational skills (according to M. Chobitko), Pearson's criterion (chi-square). In the experimental group, only 1.9% of students at the control stage of the experiment corresponded to the low level of media culture according to the cognitive criterion, while in the control group there were 18.4% f students. However, in the experimental group at the control stage of the experiment more than 61% of respondents yielded a high level of media culture according to the cognitive criterion. That said, in the experimental group only 1.9% respondents at the control stage of the experiment corresponded to a low level of media culture according to the cognitive criterion. The obtained results give grounds to argue that media culture formation has a positive effect on the future professionals’ training. This is due to the fact that media culture is underlying the general professional competence of the XXI century specialist. The enhancement of the students training through the use of new information and Internet technologies has all chances to be one of the prospects for further research in the relative to the issue addressed.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".