Student perspectives on designing generative AI-based learning companions for higher education in Oman - Saleem Raja Abdul Samad; Pradeepa Ganesan; Shanmuga Pria; Madhubala Radhakrishnan; Khadija Ahmed Al Isaei (Institute of Advanced Engineering and Science, 2026)
Artificial intelligence (AI) has rapidly permeated nearly every sector, from healthcare and finance to manufacturing, transportation, and communication. The emergence of generative AI (GenAI) applications, including intelligent assistants, recommendation engines, and predictive analytics, has further accelerated this transformation. Within education, these advances are reshaping teaching and learning, moving away from traditional instructor-centered models toward learner-centered ecosystems that emphasize adaptability, inclusivity, and self-directed growth. Despite the growing interest in AI-supported learning, existing literature reveals several important gaps that limit the effective integration of AI in educational contexts especially, students’ learning behaviors, and preferred learning resources, have received limited attention. This study explores student’s perceptions of AI-based educational tools to inform the design of an effective AI assistive learning companion for higher education. A structured survey was administered to 135 students across IT and business programs, examining demographics, language skills, learning habits, AI tool exposure, perceptions, concerns, and self-assessed learning confidence. The result of study highlights the need for AI learning companions that are adaptive, language-aware, discipline-specific, and ethically responsible, providing personalized scaffolding, practical skill reinforcement, and support for self-directed learning. These insights inform the design of AI tools that enhance learning confidence, inclusivity, and effectiveness in higher education.