Accounting students’ perceptions of learning Python: a technology acceptance model study using natural language processing

This paper aims to examine accounting students’ perceptions of learning Python through the lens of the Technology Acceptance Model (TAM). Reflective survey data were collected from 25 accounting students enrolled in a Python module at a UK university. A structured scaffolding approach was adopted to support students without prior coding experience, progressing from conceptual introduction to guided practice and independent tasks. Natural language processing techniques were used to analyse the data, including topic modelling and sentiment analysis. The findings show that students perceived Python as useful for automating tasks, handling data, and supporting employability, while reporting moderate ease and varied technical challenges. Positive attitudes persisted despite challenges. The paper contributes to accounting education by showing how TAM can explain accounting students’ experiences of coding. From a teaching excellence perspective, the paper shows that a structured scaffolding approach could support teaching by building confidence among non-technical learners.