Fostering student competencies and perceptions through artificial intelligence of things educational platform

Abstract

The growing demand for artificial intelligence (AI) skills across various sectors has enhanced AI-focused careers and shaped academic exploration in educational institutions. These institutions have been actively developing teaching methods that enhance practical AI applications, particularly through integrating AI with the Internet of Things (IoT), leading to the emergence of the Artificial Intelligence of Things (AIoT). This convergence promises significant advancements in AI education, addressing gaps in structured learning methods for AIoT. This study explored AIoT's application in Smart Farming (SF) and its potential to enrich AI education and sectoral advancements. The AIoT platform was designed for SF simulations, integrating environmental sensing, AI processing, and user-friendly outputs. This platform was implemented with 40 first-year computer science university students in Thailand using a one-group pre-posttest design. This approach transformed theoretical AI concepts into experiential learning through interactive activities, demonstrating AIoT's capability to increase AI conceptual understanding, trigger AI competencies, and promote positive learning perceptions. Therefore, this study presented the results as indicative of the AIoT platform's potential benefits, emphasizing the need for further robust experimental research. This study contributes to educational technology discussions by suggesting improvements in AIoT platform effectiveness and highlighting areas for future investigation.