Classroom emotions in civic education: A multilevel approach to antecedents and effects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Classroom emotions are major predictors of student learning and academic outcomes. Emotions might be of particular significance in civic education, where oftentimes highly controversial and heated debates take place. We aimed to examine antecedents and effects of emotions in civic education through the lens of the control-value theory. Specifically, we investigated the classroom climate during discussions of political and social issues as an antecedent of students’ enjoyment, shame, anxiety, and boredom, in addition to a possible mediation effect of these emotions on political knowledge and participation as core outcomes in this domain. Participants were 1162 students from vocational schools (grades 10–13). Multilevel structural equation modeling was used for the analysis. We found a positive relation between an open classroom climate and enjoyment and negative relations with anxiety and boredom. No support was provided for the relation to shame. Enjoyment related positively, and all negative emotions (shame, anxiety, boredom) negatively to achievement on the knowledge test. All activating emotions (enjoyment, shame, anxiety) related positively to intended political participation. Furthermore, enjoyment mediated the association between classroom climate and intended political participation at the student level. This study strongly supports the theoretical assumptions of the control-value theory. Pedagogically, the results imply that fostering a classroom context that is open to diverse opinions can prevent the experience of negative emotions and increase students’ experience of enjoyment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it