Exploring the usability of the andragogical process model for learning for designing, delivering and evaluating a workplace communication partner training
Bibliographic record
Abstract
Purpose This study aims to explore the usability of the andragogical process model for learning to develop, deliver and evaluate training to improve communication between adapted transport drivers and people living with communication disabilities and to identify the successes and limitations of the model in this context. Design/methodology/approach Two aspects were considered to explore the usability of the andragogical process model for learning: a comparison between the elements of the model and the designing, delivering and evaluating processes of the training; and an appreciation evaluation. Findings The model was useful to systematically design, deliver and evaluate workplace training that was appreciated by the learners, even though most of the model’s elements were modified to meet the constraints of the trainer and the organization. Assessing the needs for learning, establishing a human climate conducive to learning and choosing appropriate training methods emerged as key elements that contributed to a successful appreciation of this training. Originality/value This study is one of the few that examines the possibility of a systematic application of the andragogical process model for learning to workplace training. Its results suggest that the model could be considered for application by non-professional trainers or external trainers from a workplace, but that organizational constraints must be considered when using it.
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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 | 0.063 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".