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

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Dades bibliogràfiques
Publicat a:	International Journal of Online Pedagogy and Course Design vol. 15, no. 1 (2025), p. 1-15
Autor principal:	Huang, Ted Yuan-Yen
Altres autors:	Liu, Eric Zhi-Feng, Sang, Harry Hung-Yu
Publicat:	IGI Global
Matèries:	Problem solving Pedagogy Predictive analytics Collaboration Curricula Scaffolding Unmanned aerial vehicles Core competencies Cognitive ability Cognition & reasoning Artificial intelligence Cooperation Education Learning analytics Drones Independent study Adaptive learning Guidelines Educational Practices Literature Reviews Competence Educational Resources Influence of Technology Group Instruction Learning Processes International Assessment Cooperative Learning Interpersonal Competence At Risk Students Agricultural Skills Communities of Practice Evaluative Thinking Educational Assessment Course Content Lifelong Learning Learner Engagement Learning Modules Educational Trends Algorithms
Accés en línia:	Citation/Abstract Full Text - PDF
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Descripció
Resum:	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
Font:	Education Database