The Effect of Using Portfolio-based Writing Assessment on Language Learning: The Case of Young Iranian EFL Learners
Bibliographic record
Abstract
This study investigated the effectiveness of portfolio-based writing assessment in EFL situations. Participants were 40 pre-intermediate young Iranian English learners. They were randomly divided into experimental and control groups of 20 each. The experimental group wrote on five pre-established topics from their coursebook. Their writings were checked in terms of ideas, organization, voice, word choice, sentence fluency, and conventions of writing by two raters. They were given another opportunity to revise their writings to be corrected again. In contrast, the control group wrote only once and their writings were corrected only by their own teacher. The participants were also required to complete a questionnaire to assess their reflection and self-assessment. Results of the study indicate that portfolio-based writing assessment has a positive effect on language learning and writing ability. It also shows that it helps students’ self-assessment and almost all students are satisfied with this method of assessment.
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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 | 0.009 | 0.008 |
| 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) | 0.000 | 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".