Processing Unfamiliar Words: Strategies, Knowledge Sources, and the Relationship to Text and Word Comprehension
Bibliographic record
Abstract
This study examines strategies (inferencing and ignoring) and knowledge sources (semantics, morphology, paralinguistics, etc.) that second language learners of English use to process unfamiliar words in listening comprehension and whether the use of strategies or knowledge sources relates to successful text comprehension or word comprehension. Data were collected using the procedures of immediate retrospection without recall support and of stimulated recall. Twenty participants with Chinese as their first language participated in the procedures. Both qualitative and quantitative analyses were made. The results indicate that inferencing is the primary strategy that learners use to process unfamiliar words in listening and that it relates to successful text comprehension. Among the different knowledge sources that learners use, the most frequently used knowledge sources are semantic knowledge of words in the local co-text combined with background knowledge and semantic knowledge of the overall co-text. The finding that the use of most knowledge sources does not relate to the comprehension of the word suggests that no particular knowledge source is universally effective or ineffective and that what is crucial is to use the various knowledge sources flexibly. Résumé Cette étude examine les stratégies (la déduction et l'omission de mots) et les sources de connaissances (sémantique, morphologie, connaissance antérieure, etc.) utilisées par les étudiants d’anglais langue seconde (ALS) pour comprendre les mots inconnus à l'oral, et s'interroge sur les liens entre l’emploi des stratégies ou sources de connaissances et la bonne compréhension des textes et des mots. Les données ont été recueillies immédiatement après observation, sans rappel ni simulation ultérieure. Vingt locuteurs de langue maternelle chinoise ont participé à l’étude. Des approches qualitative et quantitative ont été utilisées. Les résultats indiquent que la déduction est la stratégie de toute premiѐre importance utilisée par les sujets pour comprendre les mots inconnus à l'oral, et ceci est lié à une bonne compréhension du texte. Parmi les sources de connaissances, celles qui sont les plus souvent utilisées par les étudiants sont la connaissance sémantique des mots du contexte immédiat alliée avec la connaissance de fond et la connaissance sémantique du texte global. Les résultats indiquent que l'emploi de la plupart des sources de connaissances n’a aucun rapport avec la compréhension des mots, suggérant ainsi qu' aucune source de connaissance en particulier n'est universellement efficace ou inefficace . Ce qui est crucial est l’emploi flexible de diverses sources de connaissances.
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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".