Empowering Digital Literacy through Computational Thinking, AI, and Renewable Energy in a Water-Scarce School

Medria Kusuma Dewi Hardhienata (Artificial Intelligence Study Program, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia Center for Transdisciplinary and Sustainability Sciences (CTSS), IPB University, Indonesia)
Wulandari Wulandari (Computer Science Study Program, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia)
Sheila Tobing (Department of Interdisciplinary Engineering, Faculty of Engineering, Universitas Indonesia, Indonesia)
Andrew Schauf (Center for Transdisciplinary and Sustainability Sciences (CTSS), IPB University, Indonesia)
Sita Rahmani (Energy Studies Institute, National University of Singapore (NUS), Singapore)
Gabriella Lumban Siantar (Department of Interdisciplinary Engineering, Faculty of Engineering, Universitas Indonesia, Indonesia)
Hafidlotul Fatimah Ahmad (Computer Science Study Program, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia)
Auzi Asfarian (Computer Science Study Program, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia Faculty of Engineering and Information Technology, The University of Melbourne, Australia)
Takhta Pandu Padmanagara (Commcap Indonesia, Indonesia)
Emir Raya Syuhada (Department of Mechanical Engineering, Universitas Indonesia, Indonesia)
Syaefudin Suminto (Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, Indonesia)
Iffa Mutmainah (Faculty of Medicine and Nutrition, IPB University, Indonesia)

Jurnal Pemberdayaan Masyarakat
Vol 5, No 2 (2026): Article in Press

Ongoing advances in digital technology require teachers to adapt and develop their technological competence continuously. However, a gap in technological understanding remains between teachers in rural and urban areas, particularly in Indonesia. SMA Negeri 1 Sukanagara, as the only public high school in its region, faces challenges related to water scarcity and limited access to energy, which affect both learning activities and the school community's basic needs. This community service program aims to enhance teachers' digital literacy through training in Computational Thinking (CT), Artificial Intelligence (AI), and Renewable Energy prior to the implementation of a smart rainwater-harvesting system at the school. The methods used included a survey, training sessions, and evaluation using a problem-based approach combined with pre-test and post-test assessments. A problem-based learning approach confirmed that the CT training had helped teachers to develop more structured problem-solving skills. Results of the test also show that AI and Renewable Energy training improved participants' understanding by an average of 17.08% and 14.28%, respectively, compared to their initial scores. These improvements demonstrate the potential of training programs like these to enhance teachers' understanding and better prepare them for implementing emerging technologies in schools.