From theory to practice: Understanding the long-term impact of an L2 writing education course on writing teachers
Bibliographic record
Abstract
Research on second language (L2) writing tends to focus much more on student learning of writing than teachers’ teaching and learning of the teaching of writing. While a few studies have considered the influence of formal education on teachers’ L2 writing instruction, such as by examining the changes in teacher beliefs and practices across one semester (Lee, 2010), little is known about the long-term impact (e.g., 2 or 3 years) of such training on the professional development of L2 writing teachers. The present study adopted a multiple-case study approach to examine the long-term effects of a course on teaching L2 writing on five teachers of writing who taught writing in different contexts (primary school, secondary school, private language training center, and university) in the Chinese EFL context and how the teachers may apply the theoretical knowledge and recommended pedagogies presented in such a course. Drawing upon multiple sources of data, including interviews, stimulated recalls, and teaching materials, this study revealed that despite the peripheral position of writing in current L2 literacy education, training teachers to teach L2 writing can have both immediate and lasting effects on their thinking, practices, and learning as L2 writing teachers. The course enhanced the teachers’ understanding of L2 writing and writing instruction and enabled them to adopt new pedagogies and feedback practices, whereas previously they had neglected writing instruction and taught writing based on their prior learning experiences. However, the teachers’ teaching experience determined their appropriation of the new pedagogies when contextual constraints such as students’ language proficiency, limited class hours, and exam pressure hindered their adoption of the changes. The study draws attention to L2 teachers’ knowledge gaps (thinking), their teaching practices, and their learning to teach writing (learning) and elucidates the impact of educating language teachers to teach writing across various educational settings.
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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 | 0.051 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".