This study investigates the potential of Artificial Intelligence (AI) assistants in reducing administrative burdens on public school teachers in the United States, where approximately $1.04 billion annually is allocated for teachers to perform non-teaching tasks. As AI technologies advance, their integration into educational settings presents an opportunity to automate 20-40% of administrative activities, reallocating up to 13 hours per week toward more impactful educational engagements. This shift could significantly mitigate teacher burnout, a significant factor in the profession’s high turnover rates. The introduction of the AI chatbot, “EL” (Education and Learning in Inclusive Environments), is posited as a transformative tool designed to assist with routine administrative tasks, potentially enhancing educational efficiency and allowing teachers to focus more on direct student interaction and pedagogical innovation. The quasi-experimental research design employed a T-test, Chi-Squared, and Cohen’s d to analyze the effects of AI assistant usage among pre-service teachers at the University of Central Florida. Through a pretest and post-test approach, the study assessed the effectiveness of EL in creating lesson plans that included accommodations and modifications. Additionally, the research examined the correlation between the frequency of AI assistant usage and the likelihood of pre-service teachers allowing their future students to use AI tools and pre-service teachers use of AI over four weeks. Preliminary results indicate a significant change in the attitudes and practices of pre-service teachers regarding AI, with notable improvements in their familiarity and ethical considerations of AI use in educational settings. The findings suggest that integrating AI assistants like “EL” can effectively support teachers and enhance student learning experiences, highlighting the necessity of including AI literacy in teacher education programs.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1346 |
| Date | 01 January 2024 |
| Creators | Zaugg, Tiffanie J |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
| Rights | In copyright |
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