Learning strategies of dental undergraduates of orthodontics and prosthodontics.
Bibliographic record
Abstract
It is very important for faculty members to know how students learn so that they can modify teaching methods accordingly. To measure the learning preferences of dental undergraduates at Faisalabad Medical University, Pakistan. Study Design: A Cross-sectional study. Setting: Orthodontic Department, Dental Section- Faisalabad Medical University, Faisalabad. Period: Session 2017-18. Materials and Methods: Present study was conceived on the final year dental undergraduates (n=40) of Faisalabad Medical University, Pakistan to determine the learning preferences. Questionnaire was administered using Felder and Soloman’s Index of Learning Styles. The descriptive statistics were applied and survey data were converted in to scores. Results: The results showed that most of the undergraduate dental students were verbal learners (50%). On the sequential/global scale, 55% were balanced and 40% were sequential learners. On the active/reflective scale, 45% were balanced, and 30% were active. On the sensing/intuitive scale, 50% were balanced, and 38% were sensing. Conclusion: The undergraduate dental students were found to be mostly verbal learners.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".