Instructional Scaffolding and Students’ Cognitive Engagement in Programming MOOCs

Programming skills are in extreme demand in the modern labor market, and Massive Open Online Courses (MOOCs) are the prevailing and almost the only way to learn programming. However, programming MOOCs, as well as courses in other fields, are prone to low students’ retention of students. This paper aims at filling the gap in the existing literature on students’ support with instructional scaffolding in programming MOOCs. The current study investigates relationships between the most widespread forms of instructional scaffolding, such as worked examples, hints from the instructor, code snippets, and cognitive engagement. Proposed measurements of engagement are based on students’ overt behavior that allows making inferences without direct interventions. Beginning from the factors of students’ dropout from MOOCs, it is argued that ordinary measurements of course participation, for instance, the number of completed tasks or lecture views, do not reflect the amount of mental effort invested by learners in gaining new knowledge. Instead, cognitive engagement as a dependent variable is proposed. The study was based on data obtained from the Russian MOOC constructor platform “Stepik” and included a sample of 519 coding tasks from 10 introductory programming courses. Results indicate that higher cognitive engagement was observed in tasks with worked examples, while hints are associated with the increase of constructive engagement. These findings provide insights into students’ patterns of engagement and benefits from implementation of instructional scaffolding in form of worked examples and hints for learners and course designers as well.