Artificial Intelligence in Economic Education: Adoption, Uses and Student Perceptions in Higher Education
Purpose: The aim of this article is to identify ways in which economics students use artificial intelligence tools and to assess their perception of AI as a tool supporting the learning process and academic teaching. Design/Methodology/Approach: A quantitative CAWI survey was conducted in June 2024 among economics students at the John Paul II University in Biala Podlaska. A population of N=100 was invited to participate; n=50 responses were obtained (RR=50%), which justifies the pilot nature of the study. The questionnaire included a personal data section, a module on the use of AI, and a module on the perception of AI (Likert scales). The analysis was performed in Statistica 13, using descriptive statistics, Pearson's correlation and t-tests (including Welch's variant) at α=0.05. Findings: All respondents (100%) declared that they used AI tools; 44% used them daily, and 94% at least several times a month. The most popular tool was ChatGPT (94%), followed by Grammarly (66%) and DeepL (56%). AI was mainly used for writing term papers (88%), explaining issues from the curriculum (84%) and preparing presentations (78%). Most students did not report any difficulties in using AI (90%). A strong positive correlation was confirmed between the frequency of AI use and its effectiveness in learning (r=0.90; p<0.001). Students who had completed AI courses/training used AI significantly more often than others (t=4.00; p<0.001; d≈0.88). No significant differences were found in the assessment of AI potential between first and second cycle studies (t≈-1.90; p=0.064). Practical Implications: The results indicate a very high acceptance of AI among economics students and justify the implementation of teaching solutions including (1) course modules on AI competencies (including prompt quality and critical evaluation of results), (2) training to improve staff competence in the educational use of AI, (3) formal guidelines on the ethical and transparent use of AI in coursework, and (4) institutional support in accessing tools (e.g. licences/educational versions) to reduce the risk of technological inequality. Originality/Value: The article provides empirical, pilot evidence on the intensity of AI use and perceptions of its usefulness in economics education, combining a description of usage patterns with verification of hypotheses about determinants (AI training) and relationships between usage and effectiveness ratings. The added value lies in embedding the results in the realities of the field of economics and indicating implications for the design of study programmes and the organisation of teaching in higher education.