Articles Development of a Teaching Module on Written and Verbal Communication Skills1, 2
Bibliographic record
Abstract
To provide statistical proof of their effectiveness, Language for Learning (LFL) writing strategies used in Writing Across the Curriculum programs were incorporated into a regular verbal communication class. Students taking the communication course in the quarter prior to incorporating LFL served as the control group. Both groups took pretests and posttests evaluating written and verbal communication skills. The major statistical analyses involved comparing the mean of the differences between the control subjects ’ pretest and posttest scores with that of the experimental subjects ’ pretest and posttest scores. Results showed that the typical writing apprehension expressed by pharmacy students was significantly decreased for the experimen-tal group. The experimental group showed significant improvement in four dimensions—writing, verbal skills, ability to formulate ideas, and identifying the appropriate target audience. The control group showed improvement in only one—verbal skills. Resultant materials have been made available to U.S. and Canadian schools of pharmacy in the book Writing Across the Curriculum for Colleges of Pharmacy: A Source Book.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.089 | 0.023 |
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".