Science Education in Capturing Industry-based Innovative Traits of Diverse Learners through AI and Teaching Strategies

Abstract

Higher education is facing increasing pressure to respond to rapid technological advancements, shifting labor market demands, and the growing need for graduates who are not only knowledgeable but also adaptable and innovative. This study explored the status of science education in one of the emerging regions in the Philippines, the Zamboanga Peninsula, focusing on how instructional practices align with the development of students’ skills and competencies needed in modern, technology-driven industries. Twenty college students enrolled in science-related courses were interviewed about their experiences. Narratives from one-on-one interviews were analyzed to extract themes and analyzed using reflexive thematic analysis. The findings revealed that students develop innovation-related competencies through continuous interaction with AI tools, instructors, and peers within structured learning environments. Learners exhibited improvement in creativity, problem-solving skills, decision-making abilities, and learner autonomy as they observed guidance from AI systems and instructional models. In this context, teachers and AI applications functioned as cognitive and procedural models by giving structured explanations, alternative solutions, and constructive feedback, which helped in facilitating the internalization of systematic thinking processes and the gradual development of independent problem-solving capabilities. Narratives highlighted that both AI-assisted learning and teacher-mediated instruction operate as social learning mechanisms that cultivate industry-relevant competencies through observation, imitation, feedback, and continuous cognitive engagement. Nevertheless, the study highlights the potential for integrating social learning processes into AI-assisted learning and classroom instruction to enhance the development of students’ higher-order cognitive skills, innovation-related competencies, and industry-relevant capabilities.