Assessment and feedback are foundational components of CDIO-based engineering education, and an expanding body of research has investigated the role of artificial intelligence (AI) in enhancing teaching and learning processes. As AI tools become increasingly embedded in academic and professional environments, it is necessary to examine how their use influences students’ learning experiences, particularly within engineering programs that emphasize problem-solving, active learning, and continuous improvement. This study investigates AI-supported learning through engineering students’ self-assessment of their learning experiences when using Google Gemini as a learning tool. Drawing on existing research on AI in education and technology acceptance, the study examines changes in students’ perceptions across twelve dimensions, including intrinsic motivation, learning readiness, self-efficacy, anxiety, interaction, perceived usefulness, and learning achievement. The study sample comprised 136 students from the University of Engineering and Technology, of whom 78 engineering students participated in AI-supported instruction, while the remaining 58 received traditional instruction without AI support. The analysis focuses on how AI influences students’ motivation, confidence, engagement, and perceived learning success, which are directly related to CDIO Standard 8 (Active Learning) and CDIO Standard 11 (Learning Assessment). The results indicate that students experience both benefits and challenges when using AI-based learning tools; however, strong patterns of positive engagement, high self-efficacy, and low anxiety were observed. The findings provide empirical insight into how AI can support professional competence development and learning effectiveness in CDIO-oriented engineering education based on self-assessment data from engineering students in Mongolia.
