Enforcing STEM-Driven CS Education Through Personalisation

This chapter discusses a generic structure of personalised learning content identified as Learning Objects (LOs) in three categories: component-based LO, generative LO, and smart LO. The latter is a combination of the first two. The generic structure integrates those entities with the assessment modules and specifies the distributed interface for connecting them with digital libraries. The other contribution is the learner’s knowledge assessment tool implementing the model that integrates attributes defined by the revised BLOOM taxonomy and computational thinking skills with adequate questionnaires or solving the exam tasks, we have developed. Both (the generic structure and assessment module) predefine a variety of personalised learning paths. The personalised smart LO is a mini scenario to form personalised learning paths by the learner and drive the personalised learning process. The basis of our methodology is the recognition, extraction, and explicit representation and then implementation of the STEM-driven learning variability in four dimensions, i.e., social, pedagogical, technological, and content. All these enforce integrative aspects of STEM-driven CS education and contribute to the evolution of pedagogical aspects we discuss in Part I of this book. The personalisation of STEM-driven CS education represents a new way for developing computational thinking and other skills in the process of gaining interdisciplinary knowledge; it contributes to achieving faster and deeper knowledge for decision-making skills and measuring progress through multiple assessments.