Transforming constructivist learning in engineering education through Comnet-Art: An AI-driven augmented reality learning environment

Abstract

The rapid integration of artificial intelligence (AI) and augmented reality (AR) in educational technology has opened new opportunities for enhancing constructivist learning, particularly in computer network education. This study aimed to design, develop, and evaluate Comnet-Art, an AI-based AR learning application, to improve students' understanding and constructivist skills in computer networks. The research involved 234 undergraduate students and employed the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) along with expert validation, practicality testing, and effectiveness assessment. Validation results indicated strong content and media validity, with average Aiken's V scores of 0.92 from media experts and 0.89 from material experts, categorized as very valid. Practicality assessments revealed high usability and engagement, with educators reporting an average practicality score of 91.85% and students 90.71%. Effectiveness evaluation using pre-test and post-test comparisons demonstrated substantial learning gains, with the mean score increasing from 68.21 to 86.47 and a relative improvement of 26.76%, confirming the application's effectiveness in fostering engagement, collaboration, problem-solving, and constructivist learning outcomes. These findings highlight that Comnet-Art successfully integrates AI-driven interactivity and AR visualization to support active learning, improve conceptual understanding, and enhance higher-order cognitive skills. This study provides strong evidence that emerging technologies such as AI and AR can be effectively leveraged to transform engineering education and promote constructivist learning.