Bibliographic record
Abstract
Interactive Digital Testimonies (IDTs) are increasingly utilized in educational settings to engage students with narratives of historical and contemporary events. However, their effectiveness likely depends on the contextual framing provided before the interaction and the structured reflection phase that follows. This article explores the critical role of contextualization and reflection in ensuring the pedagogical value of IDTs by showcasing selected studies. Using examples from Holocaust education and beyond, it argues that context helps students understand the broader historical and social frameworks surrounding testimonies, while reflection fosters critical thinking, empathy, and meaningful connections to the material. The discussion highlights that without these components, IDTs risk being perceived as isolated narratives rather than tools for a deeper understanding of history and memory. The article concludes by offering practical recommendations for educators to design and implement IDT-based lessons that balance immersive engagement with critical analysis, thereby enhancing their potential to contribute to broader educational goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| 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".