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Climate change continues to widen the gap between farmers’ tacit knowledge and data-driven smart farming technologies, hindering scalable and culturally relevant agricultural education. This paper presents IoT4FarmEd (IoT for Farmer Education and Engagement), a framework that integrates IoT-based environmental sensing with a mobile application combining user-centered gamification and social engagement to enhance motivation and personalized learning in farming communities. Our framework is based on behavioral patterns, including Emotion-Aware Design, Manifest-Based Learning, Yield Challenges, Risk-Level Support, Social Awareness, and Best Practices Delivery, aimed at fostering engagement, promoting the adoption of smart farming practices, and supporting gradual behavioral change. The system leverages real-time environmental data and farmers’ learning experiences to deliver recommendations aligned with the current situation of their farms, thereby promoting climate-smart and sustainable decision-making. An interactive prototype demonstrates practical feasibility and was evaluated through user-centered design and usability testing, using the think-aloud method and input from a professional UX designer. The results indicate acceptance and reveal actionable insights for further refinement.

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Enhancing Farmers’ Learning Through IoT-Based Gamification and Social Awareness

  • 会议论文

  • 发表日期：

    2026年

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  • Abdelkader Ouared,
  • Ahmed Ala Eddine Benali,
  • Abdelhafid Chadli

摘要

Climate change continues to widen the gap between farmers’ tacit knowledge and data-driven smart farming technologies, hindering scalable and culturally relevant agricultural education. This paper presents IoT4FarmEd (IoT for Farmer Education and Engagement), a framework that integrates IoT-based environmental sensing with a mobile application combining user-centered gamification and social engagement to enhance motivation and personalized learning in farming communities. Our framework is based on behavioral patterns, including Emotion-Aware Design, Manifest-Based Learning, Yield Challenges, Risk-Level Support, Social Awareness, and Best Practices Delivery, aimed at fostering engagement, promoting the adoption of smart farming practices, and supporting gradual behavioral change. The system leverages real-time environmental data and farmers’ learning experiences to deliver recommendations aligned with the current situation of their farms, thereby promoting climate-smart and sustainable decision-making. An interactive prototype demonstrates practical feasibility and was evaluated through user-centered design and usability testing, using the think-aloud method and input from a professional UX designer. The results indicate acceptance and reveal actionable insights for further refinement.