Pour une approche sémantique de l'enseignement de la morphologie flexionnelle verbale française aux apprenants anglophones adultes
Bibliographic record
Abstract
Inflectional verbal morphology, the system of correspondences between grammatical meanings and their means of expression, is an area of language which is difficult for adult L2 learners. The purpose of this thesis is to develop a pedagogical tool for Anglophone adult learners presenting French verbal morphology with a focus on semantics. This thesis adopts the view that explicit teaching of grammar is the most effective with these learners. Using theoretical insights from the Meaning-Text Theory, Le Morpheur, an Internet-based conjugator, has been developed. In order to see a fully-conjugated form using Le Morpheur, the user selects from a table of inflectional meanings those he wishes to express. In this way, the user becomes aware of all the meanings which must be combined to produce a verbal form. This resource was tested with a group of first-year French students at Dalhousie University. The participants were enthusiastic about Le Morpheur and the manner in which it presents French verb conjugation. These encouraging results indicate that continuing development and evaluation of this semantic-based pedagogical approach is desirable.
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.015 |
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".