Integrating Mobile Gaming Behavior Analysis with AI-Driven Course Recommendation Systems: A Study on Student Cognitive Skills and Academic Performance

Abstract

The widespread use of mobile technology has transformed the way individuals interact, learn, and engage with digital platforms, raising new concerns about security awareness and academic implications. This study focuses on examining mobile usage patterns and their relevance to both security consciousness and educational practices. A structured survey-based methodology was adopted, emphasizing dimensions of mobile interaction, gaming involvement, and academic association. The analysis was conducted using descriptive statistical methods to provide a clear representation of observed trends. The study emphasizes the role of mobile security awareness as a crucial factor in shaping digital behavior and educational engagement. By addressing key aspects of mobile technology usage, the research establishes a foundation for integrating security awareness into academic learning environments. Furthermore, the insights gained from students’ mobile usage and gaming behaviors can be leveraged to design adaptive course recommendation systems that personalize learning pathways based on cognitive skills and engagement patterns. This work contributes to bridging the gap between mobile security research and educational technology applications, offering a new perspective for future academic and practical exploration.

Country : India

1 Kalokhe Anil Sopan2 Phadtare Anjali Dnyaneshwar3 Saste Payal Bhagwan4 Kumbhar Vijaykumar Sambhajirao

  1. Research Scholar, Department of Computer Science, Shivaji University, Kolhapur (MH), India
  2. Research Student, Department of BBA (CA), Vidya Pratishthan’s, Arts, Science and Commerce College, Baramati, (MH), India
  3. Research Student, Department of BBA (CA), Vidya Pratishthan’s, Arts, Science and Commerce College, Baramati, (MH), India
  4. Research Guide, Department of Computer Science, Shivaji University, Kolhapur (MH), India

IRJIET, Volume 9, Issue 11, November 2025 pp. 50-56

doi.org/10.47001/IRJIET/2025.911004

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