This paper discusses the integration of AI into education, emphasizing a transdisciplinary approach that connects AI instruction to the broader curriculum and community needs. It delves into the AI program developed for Neom Community School in Saudi Arabia, where AI is taught as a subject and used to learn other subjects through the International Baccalaureate (IB) approach. The proposed method aims to make AI relevant throughout the curriculum by integrating it into Units of Inquiry.
This paper presents an experience report on teaching an AI course to business executives in the UAE. The course focuses on enabling students to understand how to incorporate AI into existing business processes, rather than focusing only on theoretical and technical aspects. The paper discusses the course overview, curriculum, teaching methods, and reflections on teaching adult learners in the UAE.
This research explores the use of generative AI, specifically ChatGPT, to create student assessments that align with academic accreditation standards, such as those of the National Center for Academic Accreditation in Saudi Arabia and ABET. The study introduces a method for mapping verbs used in questions to educational outcomes, enabling AI to produce and validate accreditation-compliant questions. A survey of faculty members in Saudi universities showed high acceptance rates for AI-generated exam questions and AI assistance in editing existing questions.
KAUST is developing AI-driven personalized learning and testing platforms to address STEM education resource gaps in Saudi Arabia. The project involves building an intelligent tutoring system in collaboration with Saudi high schools, the Ministry of Education, and SDAIA. The AI tutor, designed in a Socratic style, enhances learning through GenAI tutoring, including in Arabic, and supports teachers by generating test and homework problems. Why it matters: This initiative aims to prepare Saudi youth for future workforce demands and enhance educational outcomes, aligning with Saudi Vision 2030's goals for human capital development.
Ahmed Sultan Salem, a visiting associate professor of electrical engineering, received the 2017 KAUST Distinguished Teaching Award. Salem was one of six finalists nominated for the inaugural award and has been with KAUST since 2011. He teaches a range of EE and applied mathematics courses and his research interests include energy harvesting and cognitive radio technology. Why it matters: Recognizing teaching excellence can help incentivize high-quality education and mentorship in technical fields crucial for advancing Saudi Arabia's research and development goals.
The KAUST School (TKS) collaborated with the KAUST Red Sea Research Center (RSRC) to provide hands-on learning experiences for TKS students at the Ibn Sina Research Station. Students measured mangrove heights, crab abundances, and soil properties, guided by RSRC researchers Joanne Ellis, Marco Fusi, and Timothy Thomson. The collaboration aims to expose students to real-world research and foster a passion for science. Why it matters: This collaboration exemplifies how research institutions in the GCC can enrich local education by sharing expertise and resources, inspiring the next generation of scientists and environmental stewards.
KAUST researchers in the Image and Video Understanding Lab are applying machine learning to computer vision for automated navigation, including self-driving cars and UAVs. They tested their algorithms on KAUST roads, aiming to replicate the brain's efficiency in tasks like activity and object recognition. The team is also exploring the possibility of creative algorithms that can transfer skills without direct training. Why it matters: This research contributes to the advancement of autonomous systems and explores the fundamental questions of replicating human intelligence in machines within the GCC region.
Hisham Cholakkal has received MBZUAI’s inaugural Award for Teaching Excellence, launched by the University’s Center for Teaching and Learning. Cholakkal, an Assistant Professor of Computer Vision who joined MBZUAI in 2020, was recognized for his innovative teaching methods and positive impact on students. The award considers course evaluations and student feedback to recognize impactful, student-centered teaching. Why it matters: This award highlights MBZUAI's commitment to recognizing and promoting excellence in AI education within the region.