Deepening historical consciousness through museum fieldwork: Implications for community-based history education [Dissertation Abstract]
Bibliographic record
Abstract
This case study explores how community museum fieldwork can deepen middle school students’ historical consciousness through engagement with historical thinking. Over a 14-week unit, seventh-grade students and museum volunteers participated in structured inquiry centred on analyzing artifacts, interpreting narratives, and constructing evidence-based historical accounts. Grounded in sociocultural theory, the study distinguishes between explicit historical thinking and the more tacit development of historical consciousness. Findings show that students shifted from passive acceptance of historical narratives to active, critical engagement, demonstrating greater awareness of multiple perspectives and the complexity of interpreting the past. Their historical consciousness evolved toward more sophisticated, contextual understandings, while adult participants showed limited change in their own perspectives but greater appreciation of students’ capabilities. The study concludes that museum-based learning fosters inquiry, collaboration, and critical thinking, supporting more nuanced and reflective relationships with the past.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| 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".