Important Things to Know Before Developing Artificial Intelligence-Based Drone Learning Systems: From the Experience of Educational Practice

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Publicado en:International Journal of Online Pedagogy and Course Design vol. 15, no. 1 (2025), p. 1-15
Autor principal: Huang, Ted Yuan-Yen
Otros Autores: Liu, Eric Zhi-Feng, Sang, Harry Hung-Yu
Publicado:
IGI Global
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Acceso en línea:Citation/Abstract
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Resumen:This study explored drone-based learning in educational contexts using a mixed-method design to identify key learning attributes. After completing researcher-developed drone tasks, 73 learners demonstrated a significantly improved understanding of drone concepts and proficiency in Blockly coding. However, learners perceived self-efficacy as significantly lower than other self-regulated strategies in drone activities. Task-based drone activities, facilitated by group settings, encouraged learners to develop metacognition through collective scaffolding methods, such as peer discussions and team testing. The identified learning attributes provide valuable insights for educators in designing assessments for collaborative drone problem-solving. Additionally, the interplay among effort regulation, problem-solving, and cooperativity observed in this study offers essential references for the future development of distributed expertise systems.
ISSN:2155-6873
2155-6881
DOI:10.4018/IJOPCD.376343
Fuente:Education Database