Ranking the challenges of AI adoption in elementary education using fuzzy best-worst method approach
Year: 2026
Type: article
Abstract: AI-based technologies have successfully proliferated across various levels of education, from higher to elementary education. The most apparent implementation of AI in education can be traced directly to higher education, which has a number of potential application areas. Despite its popularity at the higher education level, its application in the context of elementary education remains scarce in the literature. Investigating the challenges associated with implementing AI-based technologies in elementary education is equally important as that of the widely tackled field in higher education. Along this line, this paper intends to explore the challenges brought about by AI in elementary education using the fuzzy best-worst method. A case study in a cluster of elementary education institutions in Cebu City, Philippines, is conducted, and interesting results reveal that stakeholders prioritize addressing the generalizability of the data mining model prior to the actual adoption of AI in elementary education.
Source: Frontiers in Education
Author: Catherine Gabia
Institution: Cebu Technological University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7154040730