One of the essential goals of science learning is to lead students to master scientific concepts or ideas and apply them to explain relevant everyday phenomena. Such mastery should help students to work with various representations. The objective of this study was to determine the effectiveness of the Learning Cycle Multiple Representation (LCMR)…

We address the problem of predicting the correctness of the student's response on the next exam question based on their previous interactions in the course of their learning and evaluation process. We model the student performance as a dynamic problem and compare the two major classes of dynamic neural architectures for its solution, namely the…

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…

The aim of this paper is two-fold. The first aim is to review the core representational and processing aspects of influential accounts of single-document and multiple-document comprehension with a particular emphasis on how readers negotiate conflicting information during reading. This review provides the groundwork for the second aim--to expand…

The aim of this paper is two-fold. The first aim is to review the core representational and processing aspects of influential accounts of single-document and multiple-document comprehension with a particular emphasis on how readers negotiate conflicting information during reading. This review provides the groundwork for the second aim--to expand…