Leveraging Object Oriented Programming and Artificial Intelligence for Personalized Teaching and Learning in Developing Countries

educational landscape in many developing countries is evolving rapidly as students strive to keep pace with technological advancements and changes in learning demands. Recognizing that traditional “one‑size‑fits‑all” teaching approaches often fall short in meeting diverse learner needs and achieving desired learning outcomes, this study investigates how a hybrid use of artificial intelligence (AI) and object‑oriented programming (OOP) principles can support adaptive, scalable, and personalized teaching and learning systems. We employed an exploratory qualitative methodology, collecting data to understand perceptions and conceptual possibilities, and used thematic analysis to identify recurring themes and insights. Our findings indicated that the modular architecture enabled by OOP is particularly suitable for building robust, maintainable educational software, while AI components enable dynamic content adaptation and personalized tutoring. Together, these technologies hold strong potential to enhance engagement, accommodate individual learning paces, and improve academic performance. Based on these insights, we recommend the adoption of OOP based design practices in developing AI driven personalized learning systems that are contextually appropriate for resource constrained settings.