Advancing e-assessment for learning in the primary EFL writing classroom: the role of collaborative teacher professional learning
Bibliographic record
Abstract
While research on teacher implementation of e-assessment for learning (E-AfL) in EFL writing is conducted increasingly at the tertiary level, the scope of research on primary teachers’ E-AfL in writing is limited, particularly regarding how teacher professional learning influences their actual practices. The study moves along this line of inquiry and investigates the impact of a year-long collaborative teacher professional learning opportunity on a primary teacher’s practices of E-AfL in EFL writing in China. The collaborative teacher professional learning opportunity was carried out to involve one contact teacher, one instructional leader, two school colleagues and two researchers via a workshop focusing on content knowledge and pedagogical principles of E-AfL in L2 writing and follow-up sessions of experiential and collaborative learning through five cycles of “planning, action and reflection” activities. The collected data included documents, interviews, reflections, observations and teacher’s written feedback. The findings indicated that the teacher navigated through three phases of development: E-AfL implementation strictly following researcher guiding principles; developing capacities regarding E-AfL; and matured E-AfL practices and established leadership. The study concludes with implications for supporting teacher professional learning and implementation regarding E-AfL in writing, emphasizing a contextualized, experiential, collaborative, sustainable framework for promoting teacher professional development.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".