Recognition of Prior Learning (RPL) from Posthumanist Perspective: A Higher Education Reconceptualization

Abstract

This study explores Recognition of Prior Learning (RPL) through a posthumanist perspective, highlighting its potential to reshape higher education by challenging traditional humanist paradigms of knowledge validation. RPL acknowledges non-linear, experiential, and technologically mediated learning, disrupting institutional authority and fostering decentralized accreditation systems. Using a Systematic Literature Review (SLR), the study examines the integration of AI-driven assessments, blockchain credentialing, and decentralized verification networks in RPL frameworks. Findings indicate that while these innovations enhance educational accessibility and legitimacy, institutional resistance remains due to concerns over quality assurance, regulatory alignment, and epistemic authority. The study advocates for a hybrid validation model that integrates posthumanist methodologies, human oversight, and emerging technologies to ensure equitable and inclusive learning recognition. Future research should explore the ethical, operational, and policy implications of AI-driven assessments and decentralized educational frameworks.