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The call for alternative grading practices has been made both inside and outside the computing education community. Various practices exist to provide assessment and feedback to students that do not rely strictly on points out of one hundred percent, weighted averages, high stakes assignments, and grading for behaviors instead of learning. However, modern classrooms, especially computer science classrooms, rely on a myriad of digital tools to organize and maintain the course structure. Tools like learning management systems, automatic grading systems, submission systems, and practice systems all exist for computing students and faculty to use to help support the learning of programming concepts. By and large, these systems all rely on an underlying mechanism of points and aggregating points for scoring. In the face of such technological choices, adopting alternative grading practices can prove challenging for instructors and confusing for students. In this position paper, we advocate addressing key research problems to make these systems easier to use with alternative grading practices. These include comprehensive support for categorical grading, comprehensive support for rework and resubmission, and improved protocols for communication of scores and feedback. We propose an extension to LTI to support the needs of alternative grading practices, and we provide an initial design for this LTI extension. We discuss current problems and potential solutions and challenge the community to work on these problems and consider the design of future systems to embrace grading approaches that go beyond just points-based scoring.
Decker et al. (Fri,) studied this question.