Navigating AI Integration Into Higher Education: A Study of the Dynamics Influencing Early-Career University Teachers’ Readiness to Integrate AI in Education

Despite growing interest in AI in higher education, little is known about how early-career university teachers perceive and engage with it. This study addresses this gap by examining their perspectives and readiness to integrate AI into academic work. Fifty-seven teachers with less than one year of experience participated in semi-structured interviews and were classified into four readiness groups: Ready, Preparing, Not Ready, and Neutral/Indifferent . Epistemic Network Analysis was used to uncover the cognitive and relational dynamics shaping their strategies. Teachers in the Ready group demonstrated a balanced understanding of AI and regarded its adoption as both necessary and inevitable. The Preparing group recognized its complexities and actively considered technical and ethical implications. The Not Ready group lacked experience and expressed skepticism, often shaped by ethical concerns. The Neutral/Indifferent group showed uncertainty, heavy reliance on external support, and a limited sense of AI’s relevance. By highlighting these differentiated perspectives, this study reveals how early-career teachers navigate AI integration, pointing to diverse needs across readiness levels. Given AI’s transformative role in higher education, the findings stress the urgency of tailored support and professional development to help new educators develop the confidence, literacy, and ethical awareness needed for effective AI use.

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Publication Details

Journal
Journal of Educational Computing Research
Published
2026-05-29
DOI
https://doi.org/10.1177/07356331261456128
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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article

Navigating AI Integration Into Higher Education: A Study of the Dynamics Influencing Early-Career University Teachers’ Readiness to Integrate AI in Education

Daner Sun, Xinyu Jiang, Z D Zhang, Wei Wei et al.
Journal of Educational Computing Research
Online Learning and Analytics
article

Navigating AI Integration Into Higher Education: A Study of the Dynamics Influencing Early-Career University Teachers’ Readiness to Integrate AI in Education

Daner Sun, Xinyu Jiang, Z D Zhang, Wei Wei, Seng Chee Tan, Xinghua Wang
article en

Abstract

Despite growing interest in AI in higher education, little is known about how early-career university teachers perceive and engage with it. This study addresses this gap by examining their perspectives and readiness to integrate AI into academic work. Fifty-seven teachers with less than one year of experience participated in semi-structured interviews and were classified into four readiness groups: Ready, Preparing, Not Ready, and Neutral/Indifferent . Epistemic Network Analysis was used to uncover the cognitive and relational dynamics shaping their strategies. Teachers in the Ready group demonstrated a balanced understanding of AI and regarded its adoption as both necessary and inevitable. The Preparing group recognized its complexities and actively considered technical and ethical implications. The Not Ready group lacked experience and expressed skepticism, often shaped by ethical concerns. The Neutral/Indifferent group showed uncertainty, heavy reliance on external support, and a limited sense of AI’s relevance. By highlighting these differentiated perspectives, this study reveals how early-career teachers navigate AI integration, pointing to diverse needs across readiness levels. Given AI’s transformative role in higher education, the findings stress the urgency of tailored support and professional development to help new educators develop the confidence, literacy, and ethical awareness needed for effective AI use.

Journal of Educational Computing Research
Qingdao University (CN), Qingdao University of Science and Technology (CN), Nanyang Technological University (SG), Education University of Hong Kong (HK), Macao Polytechnic University (MO)
Natural Science Foundation of Shandong Province
Quality Education
Openalex Percentile: Top 3%
Online Learning and Analytics
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