Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-05-157-20
DOI: https://dx.doi.org/10.15863/TAS.2026.05.157.20
Language: English
Citation: Al Souleiman, I., & Al Souleiman, H. (2026). From automation to augmentation: a human-centered framework for responsible generative AI in education. ISJ Theoretical & Applied Science, 05 (157), 332-339. Soi: https://s-o-i.org/1.1/TAS-05-157-20 Doi: https://dx.doi.org/10.15863/TAS.2026.05.157.20 |
Pages: 332-339
Published: 30.05.2026
Abstract: Generative artificial intelligence is changing how learners seek explanations, draft ideas, receive feedback, revise texts and complete academic tasks. Institutional responses tend to fall between two limited positions: viewing the technology mainly as a tool for automation and productivity, or mainly as a risk to academic integrity and independent learning. This article argues both views are incomplete, as the key educational question is whether generative AI helps or hurts human learning. The research employs a qualitative conceptual approach to differentiate between automation and augmentation, and to develop a human-centered model for responsible use in education, based on Self-Determination Theory. The discussion produces five key observations: that the responsible use of technology is a pedagogical matter, not a matter of tool presence; that augmentation has value when it supports autonomy, competence, and relatedness; that cognitive effort must be protected; that academic integrity involves process-sensitive assessment; and that institutional governance must link policy, pedagogy, professional development, and learner literacy. This article proposes a Human-Centered Augmentation Framework, which is oriented around six dimensions: pedagogical alignment, learner agency, cognitive effort, transparent process, relational teaching presence, and institutional accountability. This framework offers a practical way for educators and institutions to distinguish between learning-supportive and learning-substitutive use.
Key words: generative AI; human-centered education; learner agency; academic integrity; assessment design; self-determination theory.
|
