Students’ Self-Efficacy in Accounting Education: Evidence from a Greek University
Bibliographic record
Abstract
Students' self-efficacy has sparked research interest worldwide, as it has been found to impact their learning performance and engagement during their studies. High self-efficacy results in students feeling more capable of achieving success in their coursework and goals. In accounting education, research is limited, especially in blended learning environments. However, studies have shown that high student self-efficacy is linked to participation levels and active exchange of opinions and knowledge, making them more satisfied and capable. This study aims to explore the levels of self-efficacy among undergraduate accounting students by comparing traditional and blended classes. The research is a case study with a quantitative methodological design, using the scientific tool of questionnaires, and the data collected were analyzed using the statistical program SPSS v 2023. The findings revealed that the blended teaching approach contributes to students' self-efficacy, influenced by their commitment and dedication to the subject. These results are significant for the academic community, raising issues of adopting modern teaching approaches like blended learning and offering opportunities for students to become more autonomous and develop academic self-confidence.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".