Functionality and Efficiency of AI-Based Learning through Design Thinking in Engineering Disciplines: An Empirical Analysis

Abstract

This study examines the functionality and efficiency of AI-based learning implemented through the design thinking method within the context of engineering disciplines. In the wake of increasing digitalization and the integration of artificial intelligence in education, there is a growing need to evaluate the impact of such pedagogical models on the educational process and student development. The empirical study was conducted over two academic years among 64 engineering students, organized into teams and engaged in developing cyber-physical systems to solve real-world problems. The evaluation is based on four key areas: educational efficiency, creativity and design thinking, technological functionality, and educational experience and student impact. Data were collected through exploratory observation and analyzed using a system of indicators with a quantitative scale. The results of the study confirm that the integration of AI and design thinking creates an effective educational environment that supports the development of key engineering competencies and fosters active, engaged, and practice-oriented learning.