ARTIFICIAL INTELLIGENCE AND DIGITAL INNOVATION IN EDUCATION

This research investigates and compares the effectiveness of three different digital innovation strategies in higher education: AI-driven personalized learning platforms, synchronous digital collaboration tools, and traditional technology-enhanced learning environments. It specifically examines how Artificial Intelligence (AI) algorithms can facilitate individualized learning pathways and how students perceive the ethical and functional integration of these tools into their academic workflow. A mixed-method approach was used, combining a quasi-experimental setup with an extensive questionnaire involving 82 university students aged 18–22. The participants were split into four distinct groups (three experimental groups each receiving a specific digital intervention, and one control group receiving standard pedagogical instruction). Over an eight-week period, students utilized these innovations for complex problem-solving and coursework. Pre-test and post-test results demonstrated that academic performance, engagement, and information retention improved across all technology-integrated groups. A significant statistical difference was found between AI-supported groups and the control group, suggesting that digital innovation acts as a catalyst for cognitive development. Students' perceptions remained overwhelmingly positive, with a strong emphasis on the desire for hybrid learning models. This study contributes to the global discourse on the digital transformation of higher education.