Extending Cognitive Skill Classification of Common Verbs in the Domain of Computer Science for Algorithms Knowledge Units

To provide an adaptive guidance to the instructors through designing an effective curriculum and associated learning objective, an automatic system needs to have a solid idea of the prerequisite cognitive skills that students have before commencing a new knowledge before enhancing those skills which will enable students to steadily acquire new skills. Obtaining the learning objectives in knowledge units based on cognitive skills is a tedious and time-consuming task. This paper presents subtasks of an automatic meta-learning recommended model that enables the extraction of learning objectives from knowledge units, which are teaching materials. Knowing the cognitive skills will help mentors to connect the knowledge gaps between learning materials and their aims. The model applies Natural Language Processing (NLP) techniques to identify relevant knowledge units and their verbs, which assist in the identification of extracting the learning objectives and classifying the verbs based on cognitive skill levels. This work focuses on the computer science knowledge domain. We share the result that evaluates and validates the model using three textbooks. The performance analysis shows the importance and the strength of the automatic extraction and classification of the verbs among knowledge units based on cognitive skills.