Teachers’ Readiness and Perception of AI Integration in Science Teaching: Implications for Innovation and Curriculum Reform in Anambra State

Abstract

The study investigated secondary school teachers’ readiness and perception of AI integration in
teaching of science subjects in Anambra State. Three research questions and two hypotheses guided
the study. A descriptive survey research design was employed to collect data from a sample of 80
secondary school science teachers. The instrument for data collection was adopted by the researchers,
from the standard methods of “Technological Pedagogical Content Knowledge Framework”;
developed by Mishra and Koehler (2006); “Teachers’ Acceptance of AI Instrument”; developed by
Guo, Shi and Zhai (2024); and “Unified Theory of Acceptance and Use of Technology Model” by
Venkatesh, Thong and Xu (2012). The instruments have strong validation and reliability rating;
making them credible instrument to use for this study. Data collected were analyzed using descriptive
statistics (mean and standard deviation) to answer the research question, and inferential statistics
(paired t test) for the research hypotheses. The study's findings provided insights into teachers'
attitudes, knowledge, and skills in integrating AI in Science education, highlighting areas of strength
and weakness. The results informed policymakers, educators, and stakeholders on how to support
teachers in embracing AI-driven innovations and reforming the curriculum to meet the demands of a
rapidly changing technological landscape. The study recommended among others that educational
authorities should organize training programs to enhance teachers' knowledge and skills in integrating
AI in Science. It was also recommended that the science curriculum should be restructured to give
room for the incorporation of AI-driven innovations, ensuring that it aligns with the demands of a
rapidly changing technological landscape and prepares students for future challenges.