Students' Desires for Connected, Complex National Histories: Developing a New "We" — A View From Canada
Bibliographic record
Abstract
Students' desires for connected, complex national histories: Developing a new "we" -A view from Canada PAPER (1,972 words) In an increasingly confusing and volatile "post-truth" world, how can history education provide a sense of connection amongst young people and develop a new national "we" that brings together more than it divides?A key element of this work is for educators and educational researchers to better listen to students themselves and how they articulate their needs and desires for history education.This attention to youth in developing a pedagogical throughline in history education will invite multi-modal and interdisciplinary calls to envisioning formal history education in ways that educators alone may not envision.In this paper, the voices of students from a 2011 research intervention will be used to draw a picture of students' strong desires to learn history in ways that are connected, complex, and taught with care.However, this paper goes a step further by having the researcher and two former students from the research reflect on the 2011 findings and speak to the ongoing need for history education to speak to the diversity of the world young people experience.As both a return to the research and as a new set of conversations held without the power dynamics of teacher-research/student, this paper will broaden the ways educational research can engage with youth, classroom practice, and community to create and demonstrate broader ways of engendering conversations about teaching history in the 21 st century.Author 1 engaged in a research intervention in four history classrooms across three schools in 2011 using a Design-Based research methodology (Barab and Squire 2004, Design-BasedResearchCollective 2003).This intervention was designed to understand the relationships in a history classroom that could support "meaningful" learning from a critical antiracist, feminist, and poststructuralist lens (Biesta 2009, Delgado 1989, Freire 2006, hooks 2010, Novak 2010, Peters and Biesta 2009).This research garnered data about classroom practice, teachers' perceptions of their pedagogy, and, most importantly for this paper, students' articulations about their experiences and desires with learning national history in schools.In 2018, Author 1 connected with Authors 2 & 3, who were student-participants during the research.Through informal and formal conversations, Authors 2 & 3 provided feedback to Author 1 about her research findings, but also broadened the conversation to speak about the importance of connection and complexity in the ways history education is taught in today's "post-truth" world.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.047 | 0.039 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".