Massive Open Online Courses (MOOCs) open up new opportunities to learn a wide variety of skills online and are thus well suited forindividual education, especially where proficient teachers are not available locally. At the same time, modern society isundergoing a digital transformation, requiring the training of large numbers of current and future employees. Abstract thinking,logical reasoning, and the need to formulate instructions for computers are becoming increasingly relevant. A holistic way to train these skills is to learn how to program. Programming, in addition to being a mental discipline, is also considered a craft, and practicaltraining is required to achieve mastery. ln order to effectively convey programming skills in MOOCs, practical exercises areincorporated into the course curriculum to offer students the necessary hands-on experience to reach an in-depth understanding of the programming concepts presented. Our preliminary analysis showed that while being an integral and rewarding part of courses,practical exercises bear the risk of overburdening students who are struggling with conceptual misunderstandings and unknown syntax. In this thesis, we develop, implement, and evaluate different interventions with the aim to improve the learning experience, sustainability, and success of online programming courses. Data from four programming MOOCs, with a total of over 60,000participants, are employed to determine criteria for practical programming exercises best suited for a given audience.
Based on over five million executions and scoring runs from students' task submissions, we deduce exercise difficulties, students'patterns in approaching the exercises, and potential flaws in exercise descriptions as well as preparatory videos. The primary issue in online learning is that students face a social gap caused by their isolated physical situation. Each individual student usually learns alone in front of a computer and suffers from the absence of a pre-determined time structure as provided in traditional school classes.Furthermore, online learning usually presses students into a one-size-fits-all curriculum, which presents the same content to all students, regardless of their individual needs and learning styles. Any means of a personalization of content or individual feedback regarding problems they encounter are mostly ruled out by the discrepancy between the number of learners and the number of instructors. This results in a high demand for self-motivation and determination of MOOC participants. Social distance exists between individual students as well as between students and course instructors. It decreases engagement and poses a threat to learning success. Within this research, we approach the identified issues within MOOCs and suggest scalable technical solutions, improving socialinteraction and balancing content difficulty.
Our contributions include situational interventions, approaches for personalizing educational content as well as concepts for fostering collaborative problem-solving. With these approaches, we reduce counterproductive struggles and create a universal improvement for future programming MOOCs. We evaluate our approaches and methods in detail to improve programming courses for students as well as instructors and to advance the state of knowledge in online education.
Data gathered from our experiments show that receiving peer feedback on one's programming problems improves overall course scores by up to 17%. Merely the act of phrasing a question about one's problem improved overall scores by about 14%. The rate of students reaching out for help was significantly improved by situational just-in-time interventions. Request for Commentinterventions increased the share of students asking for help by up to 158%. Data from our four MOOCs further provide detailedinsight into the learning behavior of students. We outline additional significant findings with regard to student behavior anddemographic factors. Our approaches, the technical infrastructure, the numerous educational resources developed, and the datacollected provide a solid foundation for future research.
