Multi-level computer aided learner assessment in massive open online courses

Assessment is at the heart of massive open online courses (MOOC) challenges. It is also a core component for any effective learning. In this paper, we provide a general survey of the various forms of assessment in MOOCs. Then, we propose gradual automated learners assessment based on ontology driven for auto-evaluation learning approach (ODALA) approach. Our proposition focuses on an assessment pyramid with four levels: Closed-ended questions, Half-open questions, Open-ended questions and problem solving (PS). This pyramid is the backbone of the learning process since it needs a gradual progression with an adequate methodology. Various computer aided or completely automated assessment activities are proposed. The transition from a level to another is a conditional one since there are minimal threshold of disciplinary knowledge acquisition. An evaluation prototype was tested with the Algorithmic discipline and was developed to access the feasibility of our proposition.