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The implications of artificial intelligence usage on management students’ academic productivity

2025·1 Zitationen·Artificial Intelligence in EducationOpen Access
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1

Zitationen

2

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2025

Jahr

Abstract

Purpose This study investigates the influence of integrating artificial intelligence on the academic productivity of management students in Morocco. It explores how significant factors contribute to academic outcomes, including the quality of AI chatbots, task–technology fit, social influence, perceived usefulness and actual usage. Design/methodology/approach The study employs a quantitative research design that utilizes the SEM-PLS methodology to analyze data collected from a sample of 392 management students. This model evaluates the interrelationships among the quality of AI chatbots, user engagement and academic productivity. Findings The results show that AI tools, particularly chatbots like ChatGPT, significantly boost academic performance by enhancing learning efficiency, providing personalized support and streamlining both academic and administrative tasks. Perceived usefulness, satisfaction and chatbot usage are critical determinants of academic productivity. Additionally, task–technology fit and social influence play essential roles in technology adoption, reinforcing the need for alignment between AI tools and academic requirements. Practical implications The findings stress the importance for higher education institutions to incorporate AI chatbots strategically by ensuring their design aligns with student needs and promotes engagement. A structured approach to AI adoption, emphasizing usability and peer influence, can enhance learning outcomes and academic development. Originality/value This study enriches the dialogue on AI’s role in higher education by providing empirical insights into the factors that facilitate effective AI adoption. It underscores the significance of aligning technology with academic needs to improve student learning and productivity.

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