Towards an Adaptive Intelligent Assessment Framework for Collaborative Learning

Assessing in an online collaborative learning environment is a complex task due to the variety of elements and factors that intervene in how a group of learners collaborates to achieve an assessment task. This paper aims to improve both learners' and group performance at a given activity or a set of activities by adapting the assessment process to the learner level. To that end, we propose a general framework to illustrate our adaptive approach for assessment in an online collaborative learning environment. To do so, we take the concept of adaptation, generally based on three models: the learner model, the domain model, and the adaptive model, as a point of departure and extend it by designing two other new models that are an assessment model and a group learner model. To present our assessment model, we are based on IMS/QTI standard and ontology for the formalization of the question. We aim to combine collaborative learning, assessment, and adaptation to provide an adaptive assessment, an adaptive group composition, and an adaptive collaboration.