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All Journal Journal of Economic Education and Entrepreneurship Studies Artificial Intelligence in Lifelong and Life-Course Education
Shera Afidatunisa
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Computer Science & IT Economics, Econometrics & Finance Education Social Sciences Other

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Determinants of Tax Compliance Intention on Pre-Service Tax Payer with Extended Theory of Planned Behavior Della Fadhilatunisa; Shera Afidatunisa; Rosidah; M. Miftach Fakhri
Journal of Economic Education and Entrepreneurship Studies Vol. 5 No. 2 (2024): VOL. 5, NO. 2 (2024): JE3S, JUNE 2024
Publisher : Department of Economics Education, Faculty of Economics, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62794/je3s.v5i2.3281

Abstract

This study investigates the determinants of tax compliance intention among pre-service taxpayers using an extended Theory of Planned Behavior (TPB) framework. Integrating attitudes towards tax compliance (ATC), subjective norms (SN), and perceived ease with tax laws (PETX) enhances the traditional TPB model's predictive power. Data collected via a survey of pre-service taxpayers and analyzed with structural equation modeling (SEM) reveal that ATC significantly enhances tax awareness (TA) with a path coefficient of 0.397 (p < 0.001), while SN and PETX also positively affect TA with path coefficients of 0.293 (p < 0.001) and 0.195 (p < 0.001), respectively. ATC and PETX show significant direct effects on tax compliance behavior (TCB), with total effects of 0.399 (p < 0.001) and 0.403 (p < 0.001). Although SN does not directly affect TCB, its indirect effect through TA (0.082, p < 0.05) is significant. TA significantly impacts tax compliance (TC) with a path coefficient of 0.277 (p < 0.001). These results suggest that enhancing positive attitudes towards tax compliance, leveraging social norms, and simplifying tax laws are crucial for increasing tax awareness and compliance among pre-service taxpayers. The study offers valuable insights for policymakers and tax authorities to develop effective educational and regulatory strategies aimed at fostering voluntary tax compliance, contributing to the literature by validating the extended TPB model and emphasizing early intervention in tax education.
Artificial Intelligence Use and Emotional Well-Being in Higher Education: A Life-Course Perspective on Technology Acceptance and Trust Nailha Dinda Aprilia; Kartika Ratna Sari; Putri Nirmala; Rosidah; Shera Afidatunisa
Artificial Intelligence in Lifelong and Life-Course Education Vol 1 No 1 (2026): Artificial Intelligence in Lifelong and Life-Course Education
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aillce.v1i1.5

Abstract

Purpose – The growing integration of artificial intelligence (AI) in higher education has reshaped students’ cognitive and emotional learning experiences. From a life-course education perspective, higher education represents a critical phase of early adulthood in which interactions with AI may influence emotional regulation and readiness for lifelong learning. However, empirical studies examining the affective consequences of AI use through technology acceptance and trust mechanisms remain limited. This study investigates how AI usage frequency, perceived usefulness, perceived ease of use, and trust in AI influence university students’ emotional well-being.Design/methods/approach – A quantitative cross-sectional survey was administered to university students who actively used AI to support their learning activities. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the direct effects of technology acceptance factors and trust in AI on emotional well-being.Findings – The results indicate that AI usage frequency and trust in AI have significant positive effects on students’ emotional well-being. In contrast, perceived usefulness and perceived ease of use do not directly influence emotional well-being. These findings suggest that affective benefits of AI-supported learning are shaped more by familiarity and psychological trust than by technical efficiency alone.Research implications/limitations – The cross-sectional design, reliance on self-reported measures, and single-institution sample limit causal interpretation and generalizability. Future studies are encouraged to adopt longitudinal or mixed-method approaches to capture emotional dynamics across educational stages.Originality/value – This study extends the Technology Acceptance Model by positioning emotional well-being as a key outcome within a life-course framework, offering insights into how AI interaction during early adulthood may support psychological sustainability and lifelong learning readiness
Co-Authors Della Fadhilatunisa M. Miftach Fakhri Nailha Dinda Aprilia Putri Nirmala Ratna Kartika Sari Rosidah