Validating an Instrument for Teachers' Acceptance of Artificial Intelligence in Education
Project Overview
The document explores the role of generative AI in education, focusing on teachers' acceptance and perceptions of AI technologies. It emphasizes the significance of understanding educators' attitudes toward AI, as their acceptance is vital for effective integration into learning environments. A newly developed instrument, the Teachers' Acceptance of Artificial Intelligence (TAAI), was created and validated to measure this acceptance. The study identifies key dimensions influencing TAAI, including perceived usefulness, ease of use, behavioral intention, self-efficacy, and anxiety, supporting the instrument's validity and reliability through extensive psychometric evidence. The findings suggest that fostering positive perceptions and addressing concerns related to AI can enhance its adoption in educational settings, ultimately leading to improved teaching and learning outcomes.
Key Applications
Teachers’ Acceptance of AI Instrument (TAAI)
Context: Pre-service teachers in various disciplines at a university
Implementation: The instrument was developed based on literature review and expert feedback, then validated through surveys and factor analysis with 274 pre-service teachers.
Outcomes: The instrument showed robust validity and reliability, with reported dimensions capturing key aspects of teachers’ acceptance of AI.
Challenges: Limited awareness and understanding of AI among teachers, potential biases in responses, and lack of existing validated instruments.
Implementation Barriers
Awareness Barrier
Many teachers have limited knowledge and understanding of AI and its applications in education, which can lead to inaccurate responses when measuring acceptance.
Proposed Solutions: Providing stimuli such as reading materials or videos about AI before measuring acceptance can help improve understanding and lead to more accurate responses.
Instrument Quality Barrier
Existing instruments measuring TAAI lack robust psychometric evidence, undermining the validity of findings.
Proposed Solutions: Developing new instruments with comprehensive validation processes, including expert reviews and factor analysis, to ensure reliability and validity.
Project Team
Shuchen Guo
Researcher
Lehong Shi
Researcher
Xiaoming Zhai
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Shuchen Guo, Lehong Shi, Xiaoming Zhai
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai