Artificial intelligence (AI) has demonstrated significant potential in addressing numerous challenges in the field of education. At the classroom level, AI applications have been crafted to support instruction by customizing learning materials, sequencing learning activities, and providing individualized feedback and scaffolding based on the unique profiles of learners. In this context, AI is utilized to identify resources and pedagogical approaches deemed suitable for learners' needs, predicting potential outcomes, and recommending the next steps in the learning process.
Moreover, at the school level, AI applications are tailored to support both school management and the overall system. Examples include reducing dropout rates through predictive analysis and offering timely assessments of new skillsets, such as higher cognitive skills. While the benefits are evident, the use of AI applications in education has faced criticism for various reasons, such as the lack of control over their behavior, the exclusion of practitioner expertise in their design, and the lack of interpretability.
Despite these concerns, AI methods are being integrated into public sector education systems through machine learning, natural language processing, image processing, and expert systems. Enhancing these systems to align with public sector values involves addressing major challenges, including those mentioned above.
AIED-TLU research group aims to bring together education and computer scientists with practitioners to collaboratively address the existing challenges and contribute to the advancement of educational technology