<p>This study aims to provide a comprehensive understanding of how AI is influencing and shaping various aspects within the academic context by using a mixed-methods approach, combining quantitative investigation and qualitative analysis to explore AI impacts on undergraduate education. The findings indicate a significant positive correlation between AI usage and academic morale in the quantitative investigation, while results for research skills and ethical issues are not conclusive. Qualitative insights reveal positive factors affecting academic motivation and learning opportunities (e.g., increasing engagement with course content, tailored content, and saving time), but they can present ethical considerations. Given that this is a relatively new field of exploration, and taking into account the rapidly evolving nature of AI itself, there is a relatively insufficient amount of secondary data covering the relationships being studied in this paper. However, this study offers original contributions as variables derived from reviewed literature may have been inadequately explored in previous studies, lacking precision and depth. This study offers insights into the changing nature of AI in academia and identifies areas for further investigation.</p>

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AI in Academia: An In-Depth Analysis of the Impact of AI on Undergraduate Studies

  • Mohammad Alawamleh,
  • Rabab Alatout,
  • Worud Awamleh

摘要

This study aims to provide a comprehensive understanding of how AI is influencing and shaping various aspects within the academic context by using a mixed-methods approach, combining quantitative investigation and qualitative analysis to explore AI impacts on undergraduate education. The findings indicate a significant positive correlation between AI usage and academic morale in the quantitative investigation, while results for research skills and ethical issues are not conclusive. Qualitative insights reveal positive factors affecting academic motivation and learning opportunities (e.g., increasing engagement with course content, tailored content, and saving time), but they can present ethical considerations. Given that this is a relatively new field of exploration, and taking into account the rapidly evolving nature of AI itself, there is a relatively insufficient amount of secondary data covering the relationships being studied in this paper. However, this study offers original contributions as variables derived from reviewed literature may have been inadequately explored in previous studies, lacking precision and depth. This study offers insights into the changing nature of AI in academia and identifies areas for further investigation.