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Publications (5)
In the age of rapid technological advancements, the integration of artificial intelligence (AI), machine learning (ML), and large language models (LLMs) in science, technology, engineering, and mathematics (STEM) education has emerged as a transformative force, reshaping pedagogical approaches and assessment methodologies. This book, comprising twe...
In the context of inclusive education, Universal Design for Learning (UDL) is a framework used worldwide to create learning opportunities accessible to all learners. While much research focused on the design and students' perceptions of UDL-based learning settings, studies on stu-dents' usage patterns in UDL-guided elements, particularly in digital...
Dropout prediction is an essential task in educational Web platforms to identify at-risk learners, enable individualized support, and eventually prevent students from quitting a course. Most existing studies on dropout prediction focus on improving machine learning methods based on a limited set of features to model students. In this paper, we cont...
An experimental study investigated the effects of applying principles of the Universal Design for Learning (UDL). Focusing on epistemic beliefs (EBs) in inclusive science classes, we compared four groups who worked with learning environments based more or less on UDL principles and filled out an original version of a widely used EBs questionnaire o...
