@article{ART003375004},
author={Taewan Kim},
title={Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2026},
volume={12},
number={4},
pages={23}
TY - JOUR
AU - Taewan Kim
TI - Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator
JO - Journal of Internet of Things and Convergence
PY - 2026
VL - 12
IS - 4
PB - The Korea Internet of Things Society
SP - 23
EP -
SN - 2466-0078
AB - Global university rankings assess research, reputation, educational conditions, and internationalization, but they do not independently measure how broadly substantive artificial intelligence (AI) learning is distributed among students across an institution. Recent research has begun evaluating AI and digital readiness at the student, program, and institutional levels, yet limited work has connected such readiness with global university ranking structures. This study develops a concise AI Readiness Indicator (AI-RI) through a design-oriented comparison of major global, regional, and subject-ranking methodologies and scholarship on AI literacy and convergence education. AI-RI consists of Subject-Level AI Competitiveness (30%), Graduate AI Learning Coverage (45%), and Non-Major AI Learning Diffusion (25%). Publications and citations are not calculated separately because they are already incorporated into the relevant subject rankings. Qualifying student learning must include substantive AI content, assessment, and a responsible-use component. IoT, sensing, robotics, edge computing, and cyber-physical systems remain significant convergence applications but are not required in every qualifying course. For integration, the baseline ranking score and AI-RI are converted to a shared 0–100 scale. A 1% pilot weight and a 2% formal weight are proposed, subject to evaluation of data completeness, classification reliability, redundancy, equity effects, and rank sensitivity. The indicator is intended to function as a limited and auditable signal of readiness rather than a comprehensive assessment of university quality. Research on AI literacy similarly emphasizes multidimensional assessment involving knowledge, application, evaluation, and ethics.
KW - World University Rankings;AI Readiness;AI Literacy;AI Assessment;AI Education;IoT Convergence;QS Rankings;THE Rankings
DO -
UR -
ER -
Taewan Kim. (2026). Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator. Journal of Internet of Things and Convergence, 12(4), 23.
Taewan Kim. 2026, "Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator", Journal of Internet of Things and Convergence, vol.12, no.4 23.
Taewan Kim "Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator" Journal of Internet of Things and Convergence 12.4 23 (2026) : 23.
Taewan Kim. Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator. 2026; 12(4), 23.
Taewan Kim. "Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator" Journal of Internet of Things and Convergence 12, no.4 (2026) : 23.
Taewan Kim. Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator. Journal of Internet of Things and Convergence, 12(4), 23.
Taewan Kim. Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator. Journal of Internet of Things and Convergence. 2026; 12(4) 23.
Taewan Kim. Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator. 2026; 12(4), 23.
Taewan Kim. "Rethinking World University Rankings in the Age of AI: Introducing an AI Readiness Indicator" Journal of Internet of Things and Convergence 12, no.4 (2026) : 23.
