A mathematical formulation of learner cognition for personalised learning experiences

Abstract

The paper focuses on the assessment of cognitive skills within Virtual Learning Environments (VLEs). In response to the global shift to remote learning amid the COVID-19 pandemic, VLEs, which include learning management systems (LMS) and online collaboration platforms, gained prominence. The proposed work leverages an established Cattell–Horn–Carroll (CHC) theory to propose eight metrics, which collectively form a part of Cognitive Evaluation Metrics (CEM). The proposed metrics introduce a novel computational approach for multimode evaluation of learners’ cognitive abilities for each learning task within a learning environment. The paper details the formalism for the evaluation of the metrics and makes a contribution towards the potential of the proposed methodology to evaluate cognitive abilities. Additionally, the work implements CEM integration into the learner module of a Game-Based Learning (GBL) environment. Analysis of simulations in the GBL environment, along with statistical analysis, provides insights into the normal distribution of cognitive metrics. This reveals diverse ranges in various abilities such as long or short term memory, working memory, reasoning, attention, and processing speed. The paper also explores the impact of virtual assistants, which highlights their limited relevance to enhance cognitive abilities but serve as valuable on-demand support resources.