The Realistic Dilemmas and Possible Paths of Artificial Intelligence Enabling Teacher Education
Published Online: Aug 05, 2024
Received: Mar 25, 2024
Accepted: Jun 23, 2024
DOI: https://doi.org/10.2478/amns-2024-2163
Keywords
© 2024 Qin Zhou, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
This paper explains the dilemma of artificial intelligence in relation to the development of teacher education based on the functional structure of artificial intelligence and the activity characteristics of teacher education. Then, after designing a survey questionnaire on the factors affecting the development of teacher education empowered by artificial intelligence and completing the reliability test, the paper collects initial data in the form of distributing questionnaires and analyzes in detail the least squares estimation of mean, variance, standard deviation, correlation coefficient, and regression coefficient needed in the process of analyzing the data to carry out the analysis of instances. The correlation coefficients of teacher training, professional development, policy support, resource allocation, teacher literacy, educational information technology behaviors, and AI-enabled teacher education development are 0.674 (0.003), 0.496 (0.001), 0.259 (0.009), 0.371 (0.008), 0.639 (0.004), and 0.325 (0.007). Their corresponding regression coefficients were 0.616 (t=59.852, P=0.003), 0.021 (t=0.018, P=0.007), 0.078 (t=5.668, P=0.005), 0.032 (t=3.282, P=0.009), 0.239 (t=29.734, P=0.008), 0.137 (t=5.406, P=0.001), indicating that these factors have a significant impact relationship on AI-enabled teacher education.
