Fostering Educative Experiences in Virtual High School History
Bibliographic record
Abstract
This position paper on virtual learning in high school history argues for situating integration of information and communication technologies (ICT) in an ethically defensible vision of education. Our main purpose is to establish a broad theoretical platform to enable critique of new technologies in history classrooms. However, we also argue in favor of embracing ICT integration within a theoretical framework that places teaching and learning as the driving force behind adopting new technologies. First, we remind history teachers in computer-supported classrooms that their teaching is grounded in educational aims and in well-formulated ideas about what constitutes educative experiences. We place the development of the historical mindedness of the student at the core of educational aims in history teaching. Further, it is our contention that high school history modules should become steeped in a vision of education that recognizes its cultural-psychological dimensions. This means dovetailing the construction of content knowledge with teaching the cultural practices of historians and the functions of history. Key words: technologies of information and communication, history teaching and learning, historical mindedness, cultural psychology, educative experiences
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".