The Visibility of Oral Corrective Feedback Research in Teacher Education Textbooks
Bibliographic record
Abstract
The issue of whether, when, and how to respond to learners’ oral errors is something every teacher has to consider. Early studies of teachers’ feedback practices consisted of observations of how they managed this complex process (e.g., Lyster & Ranta, 1997). Beginning with these descriptions, a large body of research on types of oral corrective feedback (OCF) and their relative impact on L2 learning has emerged over the past few decades. OCF is thus an ideal topic for examining the degree to which second language acquisition (SLA) research-based discourse has influenced pedagogical discourse (Ellis & Shintani, 2014). This study examined how the topic of OCF is represented in 30 textbooks used in language teacher education courses. The amount of text dealing with OCF and the number of cited SLA references were quantified, and the textbooks’ advice was analyzed and compared to the findings from research. The results revealed variability across the textbooks in the degree to which OCF is treated, what is said about it, and the extent to which research is cited. Some textbook authors clearly have chosen not to highlight the contribution of research for language teaching, thus potentially limiting novice teachers’ exposure to researchers’ insights about error correction.
 La question de savoir s’il faut réagir aux erreurs orales des apprenants, quand et comment y réagir doit se poser à chaque enseignant. Les premières études sur les pratiques de rétroaction des enseignants étaient composées d’observations sur la façon dont ils géraient ce processus complexe (par ex., Lyster & Ranta, 1997). À partir de ces descriptions, un vaste corpus de recherche sur les types de rétroaction corrective orale (RCO) et sur leur impact relatif sur l’apprentissage de la langue seconde a vu le jour au cours des quelques dernières décennies. Par conséquent, la RCO est un sujet idéal pour examiner dans quelle mesure le discours fondé sur la recherche en matière d’acquisition de la langue seconde (ALS) a influencé le discours pédagogique (Ellis & Shintani, 2014). Cette étude examine comment le sujet de la RCO est représenté dans 30 manuels utilisés dans les cours de formation des enseignants de langue. On a quantifi le nombre de textes parlant de la RCO ainsi que le nombre de références d’ALS citées, et les conseils fournis par les manuels ont été analysés et comparés aux résultats de la recherche. Les résultats de ce travail ont révélé une variabilité entre les manuels par rapport à la mesure dont on traitait de la RCO, ce qu’on en disait, ainsi que le degré où l’on citait la recherche. Certains auteurs de manuels ont clairement choisi de ne pas souligner la contribution de la recherche sur l’enseignement des langues, limitant de ce fait l’exposition des enseignants novices aux perspectives des chercheurs sur la correction des erreurs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".