There are two fundamentally different types of learning outcomes. It is important to be clear that some learning follows a fairly linear pathway where there are clear right and wrong answers. The former, which is referred to as “ladder” learning or as a technical problem, can be mastered and typically can be assessed using software. This technical learning tends to be oriented around knowledge acquisition. As an example, successfully completing two-digit multiplication is preceded by competence with one-digit multiplication. In this mode of learning, the outcomes can be binary (mastered/not yet mastered or competent/not yet competent). These binary determinations are used to inform advancement and to certify competency.
Other learning is much more adaptive and contextual with multiple possible “solutions” to open-ended challenges. This type of learning, which is referred to as “knot” learning, typically cannot be mastered and competency progressions are nonlinear. Habits such as curiosity or creativity, for example, are deeply contextualized and dynamic. Inputs to inform progress are also more complex, requiring self-reflection, peer observation, educator observation, and even external “expert” observation. As an example, a challenge tied to one of the United Nations Sustainable Development Goals (such as “no poverty”) is unlikely to result in a binary outcome and the valuable outcomes are more directional than determinative. In this case, feedback is designed to inform ongoing growth in the learners’ knowledge, habits, and skills.
When I engaged in a research project to determine which other forms of input may be helpful, I solicited input from students, teachers, administrators, families, and researchers. In addition to academic assessments, we can see that self-reflection, peer feedback, educator observations and feedback from non-classroom based “experts” are all valuable perspectives to inform the learner.
What follows are examples of learner-centered metrics that reflect whole-learner outcomes in each of these areas.
Agency
Measuring learner agency requires us to think about expertise as well as ensuring that learners are developing belief in their power to act purposefully toward meaningful goals.
