The Application of Digital Transformation in Accounting Education: A Case Study of Internet + Technology Improving Academic Performance
Bibliographic record
Abstract
This study aims to evaluate the impact of the application of Internet + technology in accounting education on academic performance, with a special focus on the academic performance changes of 2022 accounting students of Ningxia Vocational and Technical College of Finance and Economics. The study adopted a quantitative analysis method to evaluate the effects of these technologies by comparing and analyzing students' scores before and after receiving Internet + technology teaching. The data was collected from the school's student status management system, covering the performance records of 124 students. SPSS software was used for data processing and analysis, and the academic performance before and after the technology application was compared through Wilcoxon signed-rank tests. The results show that the average score of students increased significantly after the application of technology, from 48.27 points to 85.40 points, indicating that Internet + technology has played a significant role in improving academic performance in accounting. This performance improvement is attributed to the flexible learning resources, enhanced interactive learning environment, and practical learning materials provided by Internet+ technology. Research also explores the potential of these technologies to improve the quality of teaching and develop students' critical thinking and problem-solving skills. Based on these findings, the study recommends that educators integrate Internet+ technology in accounting course design and calls for future research to expand the sample scope and use qualitative methods to gain an in-depth understanding of students' feelings and feedback on digital learning tools. Overall, this study highlights the importance of integrating digital technology into accounting education and provides empirical support and reference direction for other educational institutions to implement teaching reforms in similar fields. As technology continues to develop, the education field should continue to explore and adapt to new technologies to prepare students for the needs of the future accounting industry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".