Proposal of a framework to enhance the adoption of artificial intelligence in higher education considering sustainable development: a hybrid Lawshe-TOPSIS approach

Purpose The main objective of this study was to propose a framework to enhance the adoption of artificial intelligence (AI) in higher education, considering sustainable development in the context of an emerging economy country. Design/methodology/approach The method adopted was a literature review and a survey conducted with higher education faculty members from Brazilian universities. Through an electronic questionnaire, 71 responses were collected. The data were analyzed using a hybrid Lawshe-TOPSIS approach. Findings As a result, the validated framework highlights six challenges related to the adoption of AI in higher education and nine ordered benefits of AI adoption, with the most significant for the analyzed context being the ability to process large amounts of data; sustainable solutions for industry, commerce and the economy; adaptive teaching strategies and greater scientific assistance for students and faculty. Research limitations/implications The article contributes to the literature by filling a research gap and provides insights for higher education institution managers regarding AI adoption in this mode of education. Originality/value The research underscores the importance of aligning technological initiatives with sustainable development goals, providing a structured guide.

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Publication Details

Journal
International Journal of Educational Management
Published
2025-12-04
DOI
https://doi.org/10.1108/ijem-08-2024-0441
Primary Topic
E-Learning and Knowledge Management
Type
article
Field-Weighted Citation Impact
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article

Proposal of a framework to enhance the adoption of artificial intelligence in higher education considering sustainable development: a hybrid Lawshe-TOPSIS approach

Lucas Veiga Ávila, Izabela Simon Rampasso, Verônica de Menezes Nascimento Nagata, Rosley Anholon et al.
International Journal of Educational Management
E-Learning and Knowledge Management
article

Proposal of a framework to enhance the adoption of artificial intelligence in higher education considering sustainable development: a hybrid Lawshe-TOPSIS approach

Lucas Veiga Ávila, Izabela Simon Rampasso, Verônica de Menezes Nascimento Nagata, Rosley Anholon, Vitor William Batista Martins, Walter Leal Filho, Reimison Moreira Fernandes, Jonhatan Magno Norte da Silva
article en

Abstract

Purpose The main objective of this study was to propose a framework to enhance the adoption of artificial intelligence (AI) in higher education, considering sustainable development in the context of an emerging economy country. Design/methodology/approach The method adopted was a literature review and a survey conducted with higher education faculty members from Brazilian universities. Through an electronic questionnaire, 71 responses were collected. The data were analyzed using a hybrid Lawshe-TOPSIS approach. Findings As a result, the validated framework highlights six challenges related to the adoption of AI in higher education and nine ordered benefits of AI adoption, with the most significant for the analyzed context being the ability to process large amounts of data; sustainable solutions for industry, commerce and the economy; adaptive teaching strategies and greater scientific assistance for students and faculty. Research limitations/implications The article contributes to the literature by filling a research gap and provides insights for higher education institution managers regarding AI adoption in this mode of education. Originality/value The research underscores the importance of aligning technological initiatives with sustainable development goals, providing a structured guide.

International Journal of Educational Management
Universität Hamburg (DE), Universidade Estadual de Campinas (UNICAMP) (BR), Universidade do Estado do Pará (BR), Universidad Católica del Norte (CL), Universidade Federal de Santa Maria (BR), HAW Hamburg (DE), Universidade Federal de Alagoas (BR)
Openalex Percentile: Top 60%
E-Learning and Knowledge Management
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