The Centrality of Cognitively Diagnostic Assessment for Advancing Secondary School ESL Students' Writing: A Mixed Methods Study
Bibliographic record
Abstract
The primary purpose of this investigation was to examine the effects of cognitively diagnostic feedback (CDF) on secondary school English as a second language (ESL) students' writing development using a validity framework. CDF is information that is generated by diagnosing gaps in learners' cognitive processing and strategy use in a specific domain, to guide learners towards desired goals. A diagnostic rubric for assessing writing (DRAW) was developed through an iterative process involving teachers and students, founded in both theory and curriculum, and used to generate CDF. Key validity assumptions were identified related to the use of DRAW in secondary school classrooms. These assumptions were used to generate inquiry questions that guided the investigation addressing the diagnostic potential of DRAW, the effect of students' perceptions of DRAW feedback on their writing development, the interaction between students' perceptions of DRAW feedback and their goal orientations, anxiety, and self-efficacy, and the influence of teachers on students' use of feedback. Using a mixed methods research design, evidence was gathered from three Grade 10 classrooms comprising a total of 52 ESL learners and their teachers. DRAW was used to generate CDF providing students with strengths and areas for improvement on their ideas, vocabulary, grammar, organization, mechanics, and sentence fluency. Students' perceived understanding, reflection, perceived usefulness, and intent for future use of the CDF were measured through a survey and structured interviews. Students' use of the CDF was evaluated across writing samples at multiple times, and examined in relation to their goal orientations, writing anxiety and self-efficacy. Teachers' use of DRAW was also evaluated through observations and interviews. Multiple sources of evidence were used to warrant claims about DRAW practice: 1) DRAW provided cognitively, diagnostically rich information about adolescent students' writing compared to competing feedback sources used in these classrooms; 2) Students' perceptions of DRAW feedback varied according to self-efficacy, writing anxiety, and goal orientations; 3) DRAW feedback had a positive effect on students' writing skill development; 4) Teachers' assessment beliefs and feedback practices influenced and shaped students' perceptions and use of feedback and contributed to their writing performance; and 5) Teachers valued DRAW.
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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 | 0.037 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".