Grades are complex information delivery vehicles: in a single letter we summarize something about a student’s effort, content knowledge, behavior, and their performance relative to their peers. Did you know the topic incredibly well but turned the paper in late? Not an A. Did you only get a 60% on the final exam…but that was the top mark in the class? A! Did you skip class but ace the assessments? Maybe an A. We then use these markers to make all sorts of decisions about students. Should you be admitted to the major you wanted? What about graduate school? Do you qualify for a scholarship to support your studies? Can you take the next course in a sequence? And what about that job? All instances where grades are consulted to provide a sketch of who a student is and some indication of their likely success, but the ability for a grade to be descriptive is inherently limited.
In gameful design, we look to well-designed games for inspiration on how we can improve the design of learning environments, including ways to describe a learner’s current standing. For instance it’s common in games to break apart assessment of a player’s effort (experience points, or XP) from their ability (skill points, or SP). In order for the game to feel engaging, there needs to be different challenges and feedback provided in response to each state. As we begin to address what it means to tailor learning experiences to students more directly, we’re going to need more information about a student’s experience and skillset than can be garnered from a single grade or even a whole transcript.
We have found competency-based learning to be an ideal way to address this need to create personalized rigor: rather than simply earning raw points, students must demonstrate mastery of specific learning objectives in order to level up–whether that means being awarded the next grade, earning new privileges, or facing new content content challenges. This allows us to design challenging courses where students can engage in a way that best fits their skill level, but prevents them from earning a high grade simply by producing mediocre work in bulk quantity. By incorporating learning objectives as explicit micro-credentials that students earn separately from their course grade, these can easily be communicated to a broader network, or even to the next instructor. Do you teach a class that is second in a sequence? What do your incoming learners really know? Grades don’t contain enough information to answer this question. But a description of their competencies met connected to learning analytics tools might help you tailor instruction to students’ actual needs and strengths.
The next phase of GradeCraft will be dedicated to understanding the needs of different approaches to competency-based learning and assessment practices and integrating support for them into the platform. We anticipate supporting this type of learning at a variety of scales, starting within courses, but building to support whole programs, colleges, and even across the co-curricular ecosystem. Are you currently using a competency-based approach, or considering doing so? We would love for you to join us in this conversation by emailing Rachel (rkniemer@umich.edu) so that we can design the most efficient and engaging solution possible.