Abstract

REGGIARDO ROMERO, Rosmery Ruth et al. Conventional AI agents and Blockchain in higher education: A framework for dynamic learning personalization and immutable micro-credential certification. e-Rev. Multidiscip. Saber [online]. 2025, vol.3, e-RMS05102025.  Epub Nov 30, 2025. ISSN 2960-2467.  https://doi.org/10.61286/e-rms.v3i.284.

This study addresses the need for an integrated architectural framework that combines the adaptive capabilities of Artificial Intelligence agents with the assurance of trust provided by Blockchain technology within the context of higher education. The objective of this research was to design a conceptual solution that would simultaneously respond to the pedagogical imperative of dynamic learning personalization and the challenge of academic integrity resulting from the use of generative artificial intelligence. The methodology employed was based on the rigor of Conceptual Design, establishing the functional and non-functional requirements necessary for the convergence of both technologies. The first outcome is the formulation of a three-layered architecture: the personalization layer, the validation engine, and the immutable certification layer. A key finding is the design of the Competence Validation Engine, which acts as an ethical and integrity control point by defining certification triggers that consider non-pedagogical variables, such as low risk of Artificial Intelligence-based plagiarism, before activating the process. Finally, the framework concludes with the conceptualization of the adaptive micro-credential, whose individualized achievement is permanently recorded via a smart contract. This research contributes to the field by offering academic institutions a viable model for certifying the achievements of personalized learning with academic rigor and global verifiability.

Keywords : artificial intelligence; Blockchain; higher education; dynamic personalization; micro-credentials.

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