The Relationship between the Teacher Candidates’ Level of Media Literacy and Participation Levels to Protest and Social Change
Bibliographic record
Abstract
The term active citizenship is defined as participation in civil society, community and/or political life, characterized by mutual respect and non-violence and in accordance with human rights and democracy within the European context (Hoskins & Mascherini, 2009). Promoting active citizenship is one of the European Commission’s strategies for increasing social cohesion and reducing the democratic deficit across European countries within the context of the wider Lisbon process. Developing citizen awareness, knowledge and skill level of democratic rights, sensitiveness to social issues and defense against negative impact of media messages are among these objectives. European Commission considers media literacy an extremely important factor for active citizenship in today's information society. Within the European context active citizenship is defined as the combination of four dimensions; (1) protest and social change, (2) community life, (3) representative democracy and (4) democratic values (Hoskins & Mascherini, 2009). Teachers’ perceptions of citizenship are among the frequently researched subjects in terms of both their effect on students’ perception of citizenship and as a citizen. The aim of this study is to explore the relationship between teacher candidates’ level of media literacy and active citizenship, in terms of their participation level to protest and social change. Survey method is used to collect data in this casual comparative research. Sample of the study is 1101 freshman and senior teacher candidates studying in Faculty of Education at Çanakkale Onsekiz Mart University in the academic year of 2011-2012. The relationship between media literacy level and participation level to protest and social change is explored after controlling for the effect of socio-economic factors. It is explored that there is a significant relationship between media literacy level and participation level to protest and social change which is preserved after controlling for socio-economic factors. According to results, this study discusses how to handle digital and media literacy education in formal and informal settings in teacher education programs in relation to active citizenship.
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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 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 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".