An approach to modelling learner cognition for Technology Enhanced Learning

Abstract

Adaptive Technology Enhanced Learning (TEL) combines pedagogical and psychological theory with technological approaches in order to support the learner as an individual. TEL environments have already begun to demonstrate significant positive results for the learner – knowledge gain, skill acquisition, and cognitive and metacognitive abilities can be improved through the introduction of these systems. However, the modelling of key cognitive skills such as metacognition and self-regulated learning, which are antecedent of positive lifelong learning, needs to be further addressed. Current systems address these skills as a by-product of the learning environment and those that explicitly address these skills do so in a way that is that is tightly coupled with a learning environment. There is no agreed mechanism with which to model, trace, and subsequently foster cognitive strategies that are complementary to learning in a manner that is logically separated from the learning environment. The original contribution to knowledge in this thesis is a model of learner cognition that can explicitly model metacognition, can be used to reason over how to provide metacognitive supports, and is implemented as a separate web service which works alongside a TEL environment. This thesis addresses the issue of modelling cognition by describing cognitive constructs in a manner that is measurable and implementable. The resulting system is logically separated from the learning environment, but works in symbiosis to deliver support that is complementary and aligned with its goals. The formulation and validation of this model and approach have been carried out through an analysis of related literature, an examination of typical metacognitive abilities in the target learner population, and through implementation and experimentation of a test-bed system to assess the perceived benefits for the learner, modelling precision, behaviour changes, cognitive gain, and knowledge gain. The result is a mechanism with which to explicitly describe learner metacognition in a measurable manner and which can be implemented as separate service that works in collaboration with a web-based TEL environment.