Date of Award

Summer 8-22-2026

Document Type

Dissertation

Degree Name

Ph.D. in Educational Leadership and Policy Studies

Organizational Unit

Morgridge College of Education, Educational Leadership and Policy Studies

First Advisor

Rashida Banerjee

Second Advisor

Erin Anderson

Third Advisor

Starla Sieveke-Pearson

Copyright Statement / License for Reuse

All Rights Reserved
All Rights Reserved.

Keywords

Artificial intelligence (AI), AI tool in SPED, Special education (SPED), SPED teachers, Teacher retention, Teacher shortages

Abstract

In the United States, special education (SPED) teachers face complex workloads, high caseloads, and extensive documentation responsibilities, contributing significantly to burnout and retention issues. The recent integration of artificial intelligence (AI) into educational settings presents promising opportunities to alleviate teachers' instructional and administrative demands. To better understand the impact of AI on SPED teachers, this phenomenological qualitative study explored the lived experiences of licensed K–12 SPED teachers in Colorado who use AI tools in their professional practice. This study also examined how AI tools supported workload management, as well as their perceived impacts on burnout and intentions to remain in the field. Data were collected using semi-structured interviews and voice memos. Findings provide detailed insight into how licensed K–12 SPED teachers utilize AI tools to manage workload demands, including instructional planning, communication, and required documentation, and how the use of these tools influences retention and SPED teacher shortages in the state of Colorado. Findings from this study can inform professional development and leadership recommendations for responsible AI use among special educators as well as reduction of workload demands. Although findings are limited to a sample of six SPED teachers from one geographic region, these findings have important implications for future research on AI use across diverse special education settings and teacher experience levels, workload reduction, and teacher retention.

Copyright Date

8-2026

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Rawa Suhail Abu Alsamah

Provenance

Received from ProQuest

File Format

application/pdf

Language

English (eng)

Extent

208 pgs

File Size

1.5 MB

Download



Share

COinS