Introduction and Evaluation of the Notice Boards Designed for Pre-school Children and Their Parents within the Framework of “Media Literacy” Theme
Bibliographic record
Abstract
The aim of this study was to raise the awareness of pre-school teacher candidates within the framework of medialiteracy the importance of which has been noticed recently in Turkey and which has attracted attention of academiccircles as a research topic. In addition, by providing opportunities for pre-school candidates to design materials onthis topic, it also aimed to help them practice what they know and internalize the information they would obtain onmedia literacy. In this regard, the article introduces the notice board practices of media literacy theme performed byteacher candidates for pre-school students and their parents. Teacher candidates made their own choices on designingnotice boards either for children or for their parents. Encouraging candidates to design such notice boards and to usethem in training and then in their professional life is extremely important for them both to discover their owncreativity and to develop their hand skills. Moreover, dealing with the media literacy theme and expecting them todevelop materials by informing the candidates on this issue is a step taken towards raising the awareness of teachercandidates who will educate future generations. From this point of view, it could be recommended to providepractices on board and material development and use within the framework of media literacy theme throughin-service seminars for teachers currently continuing their professional life; and to share functional teachingmaterials among teachers on various platforms (conferences, congress, workshops etc.).
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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 | 0.014 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".