Higher Education Transformation through AI-Based Learning Innovation: Faculty Members’ Perception, Challenges, and Adoption in Teaching and Assessment

Year 2025, Volume: 12 Issue: 6, 280 - 299, 01.11.2025

Sarlota Singerin , Evania Yafie , Ade Nugroho , Ajeng Putri Pratiwi , Andrianus Krobo , Nancy Marhadi

https://doi.org/10.17275/per.25.90.12.6

Abstract

The purpose of this study is to determine the AI-based learning tools used the most by lecturers in higher education and examine the factors affecting the acceptance of AI-based learning innovations in teaching and assessment through the Technology Acceptance Model (TAM). The present study utilized a correlational quantitative cross-sectional design. Data were collected from 300 lecturers using a structured questionnaire through Google Forms. Data was analysed using the Structural Equation Modeling (SEM) technique with a Partial Least Squares (PLS) approach. Key findings of the research indicate that NLP-based technologies such as ChatGPT, Grammarly and QuillBot, are the most adopted AI tools. Furthermore, the research indicates that Attitude Toward Using and Behavioral Intention to Use contribute significantly to the adoption of AI technologies. A positive attitude towards AI has a strong positive effect on the lecturers' intention-to-use these technologies, which remains an important direct predictor of actual teaching with such tools. Key factors affecting attitudes and perceived usefulness of AI from lecturers' perspectives include Perceived Ease of Use and availability of adequate support. Such integration of AI into teaching emphasizes the necessity of providing proper support for higher education staff to assist them in using the technology effectively, which in turn can lead to improved teaching practices and learning outcomes. More concretely, the implications of this work include higher education institutions emphasizing solutions to the challenges of AI adoption and spending time developing policies that will allow for efficient AI use in academic contexts.

Keywords

higher education , artificial intelligence , AI , learning innovation , teaching and assesment

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