Multiple Responses Through Verbal Discourse in the Reading of Literary Texts
Bibliographic record
Abstract
The past decade has viewed the important role literature plays in enhancing the learning process among students in Malaysian English classrooms. However, most English teachers in particular are not prepared to teach literature due to the lack of training and exposure on the subject. This paper seeks to explore the ways teacher trainees from one teacher training institute attempt to provide multiple responses on two Malaysian short stories through verbal discourse. This qualitative study uses the transcripts from the audio recorded discussion among dyads to analyze the ways subjects respond to two short stories. Using a constant comparative method, recurring themes were lifted based on Newell’s (1996) typology of responses. The findings of this study revealed that the subjects used four different types of responses, namely associations, interpretation, personal response and evaluation. These responses describe the subjects’ maturity in relating their understanding of the literary texts besides the capability of making critical judgments and rationalization.
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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 | 0.018 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| 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".