Determining factors impacting the application of IFRS in teaching: Evidence from Vietnam
Bibliographic record
Abstract
With the aim of determining the factors affecting the application of IFRS in teaching for universities and colleges with accounting and auditing training, the research was conducted at 30 universities, colleges with accounting and auditing majors, and 208 lecturers who are engaged in teaching accounting and auditing in Vietnam. Next, the study employed the method of regression analysis by PLS_SEM software to process and analyze the collected data. Research results show that eight factors are affecting the application of IFRS in teaching at universities and colleges in Vietnam in the order of influence from high to low, respectively (i) Training program; (ii) Teaching staff; (iii) Regulation on the application of IFRS of the Ministry of Finance; (iv) Request of the related parties; (v) Faculty/Institution administrators; (vi) Teaching aids; (vii) IFRS teaching methods and (viii) Learners (students, trainees). At the same time, the study also shows that the financial capability of the institutions does not affect the application of IFRS in teaching.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".