As technology continues to shape the landscape of education, the integration of Artificial Intelligence (AI) into TEL and EdTech holds immense promise. However, the opacity of AI systems poses challenges in understanding the decision-making processes behind personalized learning recommendations. Explainable AI (XAI) addresses this challenge by providing insights into how AI algorithms arrive at their predictions and allowing a more informed decision to be made based on these insights. This workshop aims to explore the intersection of XAI with TEL and EdTech to empower learners with the ability to make informed decisions regarding their learning pathways. In recent years, the TEL community has increasingly recognized the importance of personalized learning experiences, and the need for transparent and interpretable AI systems in education. Studies have highlighted the importance of explainability in fostering trust and acceptance of AI-driven recommendations among learners and educators. In the context of education, where learners' autonomy and agency are keys to accomplish a fair and learner-centered educational process, XAI becomes essential for ensuring that learners have meaningful insights into why certain learning recommendations are provided to them. Implementing XAI intel and EdTech requires a thorough and common understanding of its pedagogical foundations, technical realization, and assessment from the perspective of the educational-process stakeholders (the learners, educators, developers, and institutions). 

Therefore, we design this workshop to serves as a forum for interdisciplinary dialogue and collaboration, bringing together researchers, educators, and practitioners to explore the transformative potential of XAI in TEL and EdTech. The workshop will cover the standards and foundations of XAI in pedagogy and technology. It will dive into XAI methodologies in the current state of the art. With a common understanding of the foundations of XAI in TEL and EdTech, the participants will then have a hand-on experience with tools and frameworks designed to implements and evaluate XAI in educational technologies. Participants will also gain insights into explainability-design guidelines for continuous integration with TEL and EdTech. This workshop will utilize hands-on testing, presentations, group discussions, and reflection segments, to foster transparency, interpretability, and learner empowerment in the interdisciplinary scope of TEL and EdTech. This in turn is meant to enhance the ability of the learner to gain a better chance for an equal learning experience, and more inclusion in the decision making process of their learning path.