Preservice Teachers’ Perceptions of the Pedagogical Function of Heroes and Hero Stories
Bibliographic record
Abstract
Teachers serve as gatekeepers to the implementation of curriculum in their classroom (Thornton, 2005). Their beliefs about a topic and the wider political environment can influence what they teach. To this end, our goal was to investigate whom preservice teachers identify as heroes and why, which heroes should be included in the curriculum, and how this might influence instruction of the NCSS theme Individual Development and Identity. This study was an exploratory study using the qualitative methods of an open-ended survey and focus group. We were guided by the research question: How do preservice elementary teachers conceptualize heroes? The participants were elementary preservice teachers in their final semester prior to teacher internship. We surveyed participants to determine their perceptions of heroes. We conducted a follow up focus group with five participants. The participants conceptualized heroes as serving a pedagogical function. We learned that these preservice teachers had a balanced concept of heroes and considered heroes valuable to the school curriculum. They saw heroes as role models for students to imitate. Of interest to the study of heroes in the social studies curriculum, these preservice teachers were able to overcome the barrier of the flawed hero. Rather than shifting away from teaching heroes and focusing on heroic actions as Barton and Levstik (2004) recommend, they were able to keep the curricular gate open (Thornton, 2005) to teaching heroes by developing the concept of the gray hero.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".