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Peer Instruction (PI) is an instructional approach that engages students in constructing their own understanding of concepts. Students individually respond to a question, discuss with peers, and respond to the same question again. In general, the peer discussion portion of PI leads to an increase in the number of students answering a question correctly. But(More)
Peer Instruction (PI) has a significant following in physics, biology, and chemistry education. Although many CS educators are aware of PI as a pedagogy, the adoption rate in CS is low. This paper reports on four instructors with varying motivations and course contexts and the value they found in adopting PI. Although there are many documented benefits of(More)
Recent research suggests that the first weeks of a CS1 course have a strong influence on end-of-course student performance. The present work aims to refine the understanding of this phenomenon by using in-class clicker questions as a source of student performance. Clicker questions generate per-lecture and per-question data with which to assess student(More)
While the independent contributions of synchronous and asynchronous interaction in online learning are clear, comparatively less is known about the pedagogical consequences of using both modes in the same environment. In this study, we examine relationships between students' use of asynchronous discussion forums and synchronous private messages (PM). We(More)
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We examine student difficulties with CS1 concepts by analyzing a dataset containing 266,852 student responses to weekly code-writing problems. We find that conditionals and loops prove particularly problematic, even when considering 'second chance' data; and that, while we observe some evidence of improvement, certain straightforward applications of loops(More)
Computer Science 1 (CS1), the first course taken by college-level computer science (CS) majors, has traditionally suffered from high failure rates. Efforts to understand this phenomenon have considered a wide range of predictors of CS success, such as prior programming experience, math ability, learning style, and gender, with findings that are suggestive(More)