An exploration of authentic and appropriate teaching, learning, and assessment practice in continuing professional development to identify opportunities for learning enhancement in the built environment
Bibliographic record
Abstract
While annual continuing professional development is a membership requirement for all professional bodies in the built environment, it is under increased focus in recent years, alongside competence-mapping, and the requirement for further qualifications, given the catastrophic consequences of tragedies such as the Grenfell Tower fire in 2017. The aim of this paper was to explore authentic and appropriate teaching, learning, and assessment practice in continuing professional development, through a multidisciplinary and international lens, to identify opportunities for learning enhancement in the built environment. A literature review on the professional development competence requirements in construction and equivalent professions was conducted. A questionnaire survey was circulated prior to hosting an online seminar. Eight established expert academics and professional body representatives from Ireland, England, Scotland, Wales, Malaysia, and Canada, presented their opinions and positions, exploring authentic and appropriate built environment continuing professional development educational practice. Research findings revealed that the current professional development landscape, while complex and challenging, was rich with opportunity and diversity. Findings presented multiple opportunities for the enhancement of learning through tailored professional development practices, with many novel and innovative suggestions made. Findings suggested that the onus was on practitioners to make professional, strategic, careful, and ethical choices when planning annual personal professional development, but with a call for greater support from academia and professional bodies to work together and with each other to foment positive change to the professional development landscape.
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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 | 0.022 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".