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- W2806182380 abstract "In a massive open online course (MOOC), a single pro-gramming or digital hardware design exercise may yield thousands of student solutions that vary in many ways, some superficial and some fundamental. Understanding large-scale variation in student solutions is a hard but important problem. For teachers, this variation can be a source of pedagogically valuable examples and expose corner cases not yet covered by autograding. For students, the variation in a large class means that other students may have struggled along a similar solution path, hit the same bugs, and can offer hints based on that earned expertise. We developed three systems to take advantage of the solu-tion variation in large classes, using program analysis and learnersourcing. All three systems have been evaluated using data or live deployments in on-campus or edX courses with thousands of students." @default.
- W2806182380 created "2018-06-13" @default.
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- W2806182380 date "2016-02-01" @default.
- W2806182380 modified "2023-09-25" @default.
- W2806182380 title "Leveraging Learners for Teaching Programming and Hardware Design at Scale" @default.
- W2806182380 hasPublicationYear "2016" @default.
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