The Use of Binary Online Lessons in the Context of Forming Critical Thinking in Future Journalists
Bibliographic record
Abstract
The emphasis is placed on changes in the educational field of Ukraine and the importance of forming the competencies of future journalists. Features of the application of modern information technologies in distance learning are outlined. A review of scientific sources of Ukrainian and foreign scientists on the stated issues. The relevance of the introduction of integrated technologies in modern journalism education, which contributes to improving the training of future professionals, the formation of his competencies. Definitions of the concepts "integrated learning", "interdisciplinary approach", "team learning" are defined. The focus is on the need to use an integrated approach - binary classes to increase the level of cognitive activity and activity of higher education. The focus is on forming multi-qualification of the modern journalist working in convergent newsrooms. Means of practical training of students that significantly affect the formation of professional competencies are identified. The importance of media literacy and critical thinking for the training of future journalists has been updated. According to the results of an online survey of students, it was found that interactive teaching methods increase the level of critical thinking and form skills of verification of information as a program competence of future media professionals. Scientific approaches to understanding the concept of "binary class", the organization and methods of its implementation, the features of distance learning during the pandemic. The binary online lesson "Critical Thinking: Verification of Online Content" for students-journalists in the disciplines of journalism (photo and online journalism) on the Zoom platform is described. The skills and abilities necessary for the future mediator, which create a positive professional image and public authority, are generalized and classified. Summarized the application of new learning technologies for self-realization of students, the atmosphere of cooperation, increased responsibility of teachers for the results of their work. Vectors of further research of integrated interdisciplinary classes in the educational process are outlined.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".