Bridging the Gap: Integrating Global Practices in CPD with the Lived Experiences of Filipino CPA Educators
Bibliographic record
Abstract
This paper examines how global best practices in Continuing Professional Development (CPD) from leading accounting education systems can be integrated with the lived experiences of Certified Public Accountant (CPA) educators in the Philippines.Anchored in findings from a prior phenomenological study involving six CPA teachers from a state university, this article critically juxtaposes their insights with established CPD frameworks in Australia, the United Kingdom, Canada, and Singapore.Thematic analysis surfaced five core themes: regulatory-driven compliance, financial and institutional constraints, limited perceived CPD relevance, recognized benefits in professional updating, and strong calls for policy and structural reform.A comparative matrix reveals that Philippine CPD policies currently fall short in key areas such as flexible delivery modes, institutional integration, outcome-based assessment mechanisms, and state-supported subsidies.In response, this study proposes a hybrid CPD model that contextualizes international best practices to better fit the Philippine higher education system.The model emphasizes institutional and financial support, alignment with educators' specific teaching roles, and enhanced accessibility through blended and modular learning platforms.By bridging lived experiences with global standards, the study contributes a research-informed, actionable pathway towards a more responsive, equitable, and sustainable CPD framework tailored for Filipino CPA educators.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".