Factors Affecting the Success in Certified Public Accountant Exam in Kuwait
Bibliographic record
Abstract
The aim of the article is to assess the variables that are influenced performance on the Certified Public Accountant (CPA) exam in Kuwait. To achieve the aim of the study, structure questionnaire was improved and delivered to a sample of (150) of the study population of candidates recently licensed CPAs to find out their interpretations of the causes that influence their performance on the CPA exam, the amount of questionnaires returned and ready for analysis was (120),with a reply rate of 80%. The study showed that the success of the CPA exam in Kuwait is generally dependent on factors related to the exam itself and the candidate who is taking the exam. It reported that the most important challenges linked to the CPA exam are unlimited scope of the CPA exam followed by the exam's questions do not cover all subjects and the exam does not measure the examinee's capabilities. Moreover, the analysis showed that insufficient preparation of the exam is the main variable affecting the performance of CPA exam followed by accepting the idea of repeating the exam. Finally, the study recommends that academicians in accounting should train the students for the exam. They should pay attention to curriculum to assure that learners are provided the good training for the examination.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".