The aim of this study was to determine the cognitive structures of high school students related to the atmosphere and climate. The study group consists of 70 students in the 10th grade of a state high school affiliated to Konya Provincial Ministry of National Education. In this study, a survey model, which allowed us to determine the current…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…

A deep understanding of the learning level of online learners is a critical factor in promoting the success of online learning. Using knowledge structures as a way to understand learning can help analyze online students' learning levels. The study used concept maps and clustering analysis to investigate online learners' knowledge structures in a…

This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…

The Repertory Grid Technique (RGT) is a qualitative method, based on the Personal Construct Psychology (PCP) theory, which provides a powerful tool to elicit tacit personal construction systems, with minimal intervention and interpretation. Although the contributory potential of the RGT as a cognitive research tool in science education has been…

A poorly elaborated learner's understanding of models has been reported to be one of the major sources for learning difficulties in the quantum domain. To be able to provide physics education in schools with evidence as to how this problem can be tackled, a deeper theoretical understanding of the structure of learners' mental models in quantum…

Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…