<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Teaching RPA technology to accounting students can be better adapted to the changing market demand. Therefore, this paper proposes the RPA financial automation process model generated by the data flow classification algorithm using integrated learning, which combines the development and application of RPA into the daily teaching of accounting students and combines the data analysis and application with practical scenarios. The questionnaire survey reflects the students’ comprehensive evaluation of the course’s teaching quality, application effect, satisfaction, and maturity of the RPA model. In the survey results on the stereoscopic satisfaction of the cultivation of professional knowledge, skills and vocational ability, the average score of each item exceeds 2 points, and the satisfaction of RPA technology is high. In the evaluation of application, the scores of curriculum dimension and teaching method dimension are 80.37 and 82.06 respectively, which are at a better level, and the score of accounting process dimension is 77.83, which brings a positive impact. The learning dimension achieved a score of 73.66, which is a satisfactory level. According to 95.6% of the students, RPA is advantageous for their profession and future work. 99.7% of the students are willing to recommend studying to other students. However, the final score of RPA’s maturity level is 71.6, which is still in progress, and it still needs to continuously promote the transformation of digital intelligence.</p>
</abstract>

Teaching RPA technology to accounting students can be better adapted to the changing market demand. Therefore, this paper proposes the RPA financial automation process model generated by the data flow classification algorithm using integrated learning, which combines the development and application of RPA into the daily teaching of accounting students and combines the data analysis and application with practical scenarios. The questionnaire survey reflects the students’ comprehensive evaluation of the course’s teaching quality, application effect, satisfaction, and maturity of the RPA model. In the survey results on the stereoscopic satisfaction of the cultivation of professional knowledge, skills and vocational ability, the average score of each item exceeds 2 points, and the satisfaction of RPA technology is high. In the evaluation of application, the scores of curriculum dimension and teaching method dimension are 80.37 and 82.06 respectively, which are at a better level, and the score of accounting process dimension is 77.83, which brings a positive impact. The learning dimension achieved a score of 73.66, which is a satisfactory level. According to 95.6% of the students, RPA is advantageous for their profession and future work. 99.7% of the students are willing to recommend studying to other students. However, the final score of RPA’s maturity level is 71.6, which is still in progress, and it still needs to continuously promote the transformation of digital intelligence.

Research on the Transformation of Digital Intelligence of Accounting Profession Based on Big Data Technology

Department of Accounting, Management College

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Teaching RPA technology to accounting students can be better adapted to the changing market demand. Therefore, this paper proposes the RPA financial automation...

Research on the Transformation of Digital Intelligence of Accounting Profession Based on Big Data Technology

Pubblicato online: 03 mag 2024

Pagine: -

Ricevuto: 06 apr 2024

Accettato: 17 apr 2024

DOI: https://doi.org/10.2478/amns-2024-0901

Parole chiave
Integrated learning, Data stream classification, RPA, Number-wise transformation, Accounting program

© 2024 Su Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Transformation of Digital Intelligence of Accounting Profession Based on Big Data Technology

Pubblicato online: 03 mag 2024

Pagine: -

Ricevuto: 06 apr 2024

Accettato: 17 apr 2024

DOI: https://doi.org/10.2478/amns-2024-0901

Parole chiaveIntegrated learning, Data stream classification, RPA, Number-wise transformation, Accounting program

© 2024 Su Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Integrated learning, Data stream classification, RPA, Number-wise transformation, Accounting program