L’altérité: une composante clé de l'apprentissage par l'expérience?
Bibliographic record
Abstract
Taking the view that learning is only learning when it is accompanied by experience, this research focuses on the identifiable variables of this experiential dimension. To do this, the researchers followed learners as they discovered cultural otherness through the Dialogue en route project (https://enroute.ch/fr/), which involves a dual encounter with a cultural site and a witness to that site. To reach the learners' semiosis, the researchers documented their learning activity using two types of trace, visual and verbal. Because of their fundamentally different intrinsic characteristics, the two types of trace opened up a process-space of intelligibility that enabled the researchers to empirically document the complexity of meaning-making, its situated nature and its potential impact on learning. To this end, the temporality of trace production was used as an instrument, since the learners photographed moments in the double encounter situation and then captioned them afterwards. Reconstructing the situation as it unfolded turned the visual and verbal modalities into semiotic resources that the learners used to reconstruct their potential experience. For the researchers, the study of the relationships between these two modal traces makes it possible to qualify the experience lived by the learners. The limited number of so-called 'rupture' relationships between the images and their verbal captions, revealing a singular experience with a high learning potential, raises questions about both the pedagogical device and the emergence of collectively constructed knowledge, captured here in its 'average' restitution rather than in its negotiation.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".