This study examines the extent of awareness and use of artificial intelligence (AI) tools by students in a private university environment as well as their impacts on academic performance. Data were collected from a standardized survey given to 70 undergraduate students. The analysis focused on four main dimensions: awareness of AI, self-perceived efficacy in the use of AI tools, integration into pedagogy, and academic performance. The descriptive statistical analysis showed high levels of familiarity and use, with the majority of the participants (over 88%) indicating active use of AI applications. Despite this, however, there is a gap in the provision of systematic training. Correlational analysis indicated high positive correlations among the variables, with integration as the strongest correlational factor associated with academic success. Stepwise regression also suggested that integration by itself was a significant predictor of performance in the students, explaining more than 30% of the variance. These study results underscore the saliency of environments infused by AI and the need for well-designed training programs. It concludes by specifying the steps by which schools may introduce AI in pedagogically appropriate steps.

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Awareness of Artificial Intelligence in Higher Education and Its Influence on Student Academic Outcomes: A Case Study at a Private University in Bahrain

  • Mahmood Saeed Mustafa Alalawi,
  • Merhan Mohsen Mohammed,
  • Shema Bukhari,
  • Adnan Faisal Hashem

摘要

This study examines the extent of awareness and use of artificial intelligence (AI) tools by students in a private university environment as well as their impacts on academic performance. Data were collected from a standardized survey given to 70 undergraduate students. The analysis focused on four main dimensions: awareness of AI, self-perceived efficacy in the use of AI tools, integration into pedagogy, and academic performance. The descriptive statistical analysis showed high levels of familiarity and use, with the majority of the participants (over 88%) indicating active use of AI applications. Despite this, however, there is a gap in the provision of systematic training. Correlational analysis indicated high positive correlations among the variables, with integration as the strongest correlational factor associated with academic success. Stepwise regression also suggested that integration by itself was a significant predictor of performance in the students, explaining more than 30% of the variance. These study results underscore the saliency of environments infused by AI and the need for well-designed training programs. It concludes by specifying the steps by which schools may introduce AI in pedagogically appropriate steps.