In 2010, the North Carolina General Assembly amended state laws that required all community colleges to adopt a religious observance policy that would provide students with a minimum of two excused absences for religious activities “required by the faith of the student.” Drawing on Felix and Nienhusser’s Equity-Centered Policy Implementation Framework, this qualitative, critical policy analysis examined the language used in publicly available religious accommodation policies and procedures adopted by various North Carolina community colleges to gain a deeper understanding of how these policies are foregrounded and constructed, and to what extent the organizational behaviors directed in the policies may or may not foster religious pluralism. Findings revealed how the colleges framed these policies in legal and non-discrimination compliance language and logic, while obscuring the distinction between excused absences specifically and religious accommodations broadly. Discussions of key findings focus on the role of individual institutions responding to state legislative mandates, along with recommendations for future research and institutional practice.
This study examines how school leaders use artificial intelligence (AI) in their professional practice. Through semi-structured interviews with 15 school leaders from a Midwestern state, the study found that participants used AI primarily to streamline administrative work, support data analysis, assist with communication, and generate instructional resources. Across roles, participants described their ability to deepen instructional support, mentoring, and collaboration with teachers, practices that align with core dimensions of distributed leadership such as collaboration, capacity building, and shared instructional leadership. The findings suggest that participants viewed AI as a tool that supported aspects of their leadership work, particularly instructional support and efficiency. The study contributes to emerging scholarship on AI in educational leadership by offering an exploratory qualitative case study of how school leaders are currently integrating AI into their work and conceptually by illustrating how these emerging practices are situated within a distributed leadership framework.
Across U.S. higher education, adoption of generative artificial intelligence (GenAI) is expanding faster than many campus governance systems can guide, monitor, or audit. This paper offers an equity-first, risk-calibrated policy playbook for higher education leaders by integrating equity-centered leadership perspectives with the National Institute of Standards and Technology Artificial Intelligence Risk Management Framework. It specifies governance mechanisms, including risk-tiered use-case portfolios, clear decision rights, procurement and vendor-assurance standards, and auditable documentation such as impact assessments. These mechanisms are anchored in U.S. accountability concerns, including privacy, accessibility, nondiscrimination, and due process. Drawing on a policy-design analysis of federal guidance, institutional policy syntheses, and illustrative state/system levers, the paper identifies recurring governance failure modes, including shadow AI use and decision-support tools that become determinative in practice. It specifies proportionate controls campuses can implement without building a parallel bureaucracy. It concludes with a concise measurement approach for internal improvement and public-facing accountability.
Alternative certification (AC) programs are adopted to address teacher shortages, yet high turnover undermines workforce stability and educational equity. Using a national sample, this study examined how dimensions of in-service support relate to turnover intentions. Regression results revealed that a preparation gap in leaving intentions emerged among teachers with limited support. Crucially, regular (monthly or weekly) mentoring or coaching was associated with a reduction in this disparity. Additionally, higher perceived professional development quality was uniformly associated with reduced moving and leaving intentions for all teachers. Targeted professional support is a vital policy lever to promote a more sustainable teacher workforce.
