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This research examines the impact of AI-driven learning tools, particularly GPT-based tutoring systems, on Business Mathematics education. It explores how AI-assisted interventions mitigate mathematics anxiety, enhance technological adaptability, and improve problem-solving abilities among undergraduate commerce learners. The research aims to determine whether AI-powered learning can complement or transform traditional teaching methodologies. A quantitative research design was employed, by collecting data from 253 first-year undergraduate learners across five private universities in India. Using a 5-point Likert scale, the study measured mathematics anxiety, technological adaptability, use of GPT and AI in learning, and Business Mathematics performance. Structural equation modeling (SEM) confirmed that mathematics anxiety negatively impacts performance (β = 0.331, p < 0.001), while technological adaptability positively influences academic success (β = 0.234, p < 0.001). AI-powered tutoring systems significantly enhance mathematical comprehension and problem-solving skills (β = 0.354, p < 0.001). The study underscores the potential of AI-assisted education in reducing cognitive barriers, fostering engagement, and improving student outcomes. Unlike previous research, it highlights AI tutors as active learning collaborators, emphasizing their role in conceptual reinforcement and personalized feedback. The findings advocate for AI-driven learning as a scalable and inclusive approach, urging educational institutions to integrate AI tools for enhanced Business Mathematics education.

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Empowering Business Mathematics Learners: Leveraging Generative AI for Academic Excellence

  • 会议论文

  • 发表日期：

    2026年

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  • A. Sakthivel,
  • V. T. Srikrishna Swaroop,
  • Abdullah Malik,
  • Reji Meprathe,
  • Salini Suresh,
  • Anjali Shukla

摘要

This research examines the impact of AI-driven learning tools, particularly GPT-based tutoring systems, on Business Mathematics education. It explores how AI-assisted interventions mitigate mathematics anxiety, enhance technological adaptability, and improve problem-solving abilities among undergraduate commerce learners. The research aims to determine whether AI-powered learning can complement or transform traditional teaching methodologies. A quantitative research design was employed, by collecting data from 253 first-year undergraduate learners across five private universities in India. Using a 5-point Likert scale, the study measured mathematics anxiety, technological adaptability, use of GPT and AI in learning, and Business Mathematics performance. Structural equation modeling (SEM) confirmed that mathematics anxiety negatively impacts performance (β = 0.331, p < 0.001), while technological adaptability positively influences academic success (β = 0.234, p < 0.001). AI-powered tutoring systems significantly enhance mathematical comprehension and problem-solving skills (β = 0.354, p < 0.001). The study underscores the potential of AI-assisted education in reducing cognitive barriers, fostering engagement, and improving student outcomes. Unlike previous research, it highlights AI tutors as active learning collaborators, emphasizing their role in conceptual reinforcement and personalized feedback. The findings advocate for AI-driven learning as a scalable and inclusive approach, urging educational institutions to integrate AI tools for enhanced Business Mathematics education.