Supporting Learning of Programming with Tutoring Systems

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In many institutions, programming classes are now endorsed for all students (not just computer science majors) at pre- and post-secondary levels. However, programming classes have notoriously high failure and drop-out rates. This may be because programming, while sharing some overlap with other problem-solving activities, additionally requires a novel way to think and problem solve in order to master the skills needed to program. Since these skills are unique to programming, supporting them requires innovative pedagogical approaches. My research program will advance educational technologies, called tutoring systems, that help students learn to program by encouraging constructive processing of examples. Examples play a key role in cognitive skill acquisition but to date relatively little work exists on leveraging them to support learning of programming via tutoring systems. To address this gap, the proposed work has three main research streams: (1) interventions focused on example design (including gaps in example solutions, prompts to encourage self-explanation, and erroneous examples), (2) instructional sequencing of examples vs. problems, and (3) promotion of programming as a creative activity through multiple examples. In the short term, the focus will be on the design of tutoring system functionalities, including studies to identify interface features that promote student learning through constructive reasoning. The long-term goal is to add to the tutoring systems adaptation capabilities that tailor instruction, accomplished by extending the tutors with student models. A student model stores information about individual students (e.g., their knowledge and affect) and updates that information in real time based on students' interactions with a tutoring system; this information is used by the tutoring system to tailor instruction to a given student's needs. The proposed research has intellectual merit. The tutoring systems developed by my research program will serve as testbeds for answering research questions related to effective tutoring-system design, as well the utility of novel cognitive and affective interventions focused on core programming skills. Thus, the results will contribute to artificial intelligence & education, cognitive science, and human-computer-interaction fields. On the broad impact side, my research program will produce a series of online tutors designed for a diverse audience that provide personalized help to all students, including ones coming from non-traditional CS backgrounds. By making programming accessible, this has potential to motivate interest in this domain and thus broaden participation in the field.