Digital Literacies and Generational Micro-Cultures: Email Feedback in Lebanon
Bibliographic record
Abstract
This study reports on the introduction of email feedback, in a private university in Lebanon with marked generational differences and a traditional instructor culture focused on grammar correction. The instructor profile showed insufficient ELT training and a disjuncture between those with low and those with long service. Instructors were trained, and an email form used during one semester. A survey elicited instructors’ views. Appraisal analysis identified attitudes in personal responses written by students and instructors. Analysis of feedback quality was undertaken. Results showed students responded positively, instructors negatively to email feedback. Instructors perceived students’ positive response, but reasserted traditional understandings of teacher roles, reflecting a lack of understanding of the role of emotion in acquiring form. Training in ELT and digital literacies, management oversight of accountability structures, and sufficient remuneration for part-timers’ grading hours, are recommended. The study also implicates long years of service in resistance to needed change.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".