ASSESSMENT AND EVALUATION BEYOND HUMAN CENTERED MODELS

Abstract

Literature deconstructs traditional psychometric, individualized, and representational evaluation paradigms that reduce learning to static human outputs. It critiques algorithmic surveillance, predictive analytics, and automated proctoring that reinforce cartesian dualisms and panoptic datafication. In response, it proposes ecological assessment assemblages, posthuman evaluative judgment, and non-representational feedback models that account for distributed agency, socio-material environments, and machine-mediated cognition. This chapter argues for an ethical, relational, and non-anthropocentric re-configuration of pedagogy, demonstrating that learning, imagining, and evaluating are fundamentally more than human practices.