Prototype Implementation of a Robotic Gamification Model for Climate Change Literacy for Green Innovation and Entrepreneurship with Social Robot Nao

  • Stephen Ochieng Oguta Information Technology Department, Durban University of Technology, Durban, South Africa
  • Sunday Ojo Information Technology Department, Durban University of Technology, Durban, South Africa
  • Benard Maake Computing Sciences Department Kisii University, Kisii, Kenya

Abstract

Purpose – This research introduces the Robotic Gamification Model for Climate Change Literacy for Green Innovation and Entrepreneurship (RGM-CCL4GIE) as an innovative educational solution for Sub-Saharan Africa (SSA), addressing the limitations of current gamification systems that fail to sustain long-term learner motivation and engagement.

Method – The study employs Design Science Methodology (DSM) to develop and validate the model, which integrates Self-Determination Theory, Mechanics-Dynamics-Aesthetics (MDA) framework, and Operant Conditioning Theory. The system is prototyped on the Moodle e-learning platform and Social Robot Nao, with empirical testing conducted among students.

Results – The findings demonstrate high learner motivation (mean score of 4.58) and significant positive correlations between random rewards and increased engagement (p-value < 0.001). The model successfully integrates robotic interaction, dynamic rewards, and gamification elements to enhance climate change literacy education.

Conclusion – The RGM-CCL4GIE effectively addresses the limitations of existing gamification systems by promoting sustained engagement and improved learning outcomes in climate change education, particularly within the SSA context.

Recommendations – Implementation of the model should focus on maintaining the balance between robotic interaction and gamification elements while ensuring accessibility and adaptability across different educational contexts.

Research Implications – This study advances the field of educational gamification by providing an innovative framework that combines robotics and advanced motivational theories, establishing a foundation for future research in sustainable, technology-driven learning models.

Practical Implications – The model offers educational institutions in SSA a practical solution for enhancing climate change literacy and green entrepreneurship education through integrated technological approaches.

Social Implications – The implementation of RGM-CCL4GIE contributes to broader climate change awareness and sustainable development goals in Sub-Saharan Africa, potentially influencing social attitudes toward environmental conservation and green innovation.

Author Biographies

Stephen Ochieng Oguta, Information Technology Department, Durban University of Technology, Durban, South Africa

Stephen Oguta is a PhD in Information Technology student at Durban University of Technology. He has a master's degree in Telecommunications Engineering from Jomo Kenyatta University of Technology in Kenya. His research interests are Gamification, Artificial intelligence, Social robots, Big data, Computer security, Cloud computing, and neural networks among others.

Sunday Ojo, Information Technology Department, Durban University of Technology, Durban, South Africa

Professor Sunday O. Ojo holds a PhD degree in Computing Science from the University of Glasgow in Scotland, UK. His research interest areas include ICT for Development, Computational Linguistics and Natural Language Processing,, Data Science and Machine Learning, Educational Gamification, Green Computing, and Climate Change Literacy for Green Innovation and Entrepreneurship. He is currently an Adjunct Professor (Research) at Durban University of Technology in South Africa.

Benard Maake, Computing Sciences Department Kisii University, Kisii, Kenya

Dr. Benard Maake is a lecturer in the Department of Computing Sciences at Kisii University, Kenya. He holds a PhD in Computer Systems Engineering from the Tshwane University of Technology in Pretoria, South Africa. His research interests include recommender systems, big data, machine learning, cloud computing, natural language processing, and artificial intelligence.

Published
2025-02-02
How to Cite
OGUTA, Stephen Ochieng; OJO, Sunday; MAAKE, Benard. Prototype Implementation of a Robotic Gamification Model for Climate Change Literacy for Green Innovation and Entrepreneurship with Social Robot Nao. International Journal of Computing Sciences Research, [S.l.], v. 9, p. 3491-3523, feb. 2025. ISSN 2546-115X. Available at: <//stepacademic.net/ijcsr/article/view/492>. Date accessed: 07 oct. 2025.
Citation Formats
Issue
Vol 9 (2025): Volume 9
Section
Articles

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