Understanding the Effects of Lecturer Intervention on Computer Science Student Behaviour

Abstract

Providing effective support and feedback to students is critical to ensure engagement and retention within Computer Science courses. Individual student learning experiences and challenges vary from student to student, and effective intervention is further hampered in a large scale context. In addition, there are a plethora of possible interventions for any given learning challenge, and it is difficult for an educator to establish which intervention is the most effective or quickest to implement. To this, we report on the outcomes of a systematic literature review focused on interventions in Computer Science classrooms. To provide an understanding of the types of interventions possible in a Computer Science course, we propose a taxonomy of intervention types with low mutual information and classify the 129 selected papers based on it. We identify the most effective interventions as presented in their respective studies and discuss gaps in the study of several intervention types. We then present an overview of two of the most popular types of interventions in the published literature: those focused on introducing technical cooperations within courses, and those focused on changing the way the course content is presented to students. To understand how interventions have evolved over time, we present the evolution of sub-classes of interventions over the years.