Restorative and community circles foster cross-generational relationships that strengthen well-being, communication, and problem-solving skills. Research highlights increased student voice, stronger relationships, and enhanced respect, empathy, and accountability among members. Findings reinforce the need to reimagine teacher preparation to emphasize relational, community-building practices that promote belonging and acceptance in today’s classrooms.
Teachers’ roles are continuously evolving, reflecting shifts in educational paradigms and societal expectations. While teachers remain central to student learning outcomes and curriculum delivery, they increasingly face challenges, such as teacher burnout. Could artificial intelligence (AI) alleviate teacher burnout? The presentation will discuss research that investigated the possibilities of innovative and inclusive education by exploring how free AI tools can support special education teachers. Findings will offer valuable insights into effective instructional strategies using emerging technologies, helping to inform teacher training and professional development initiatives.
Generative AI has fundamentally disrupted traditional approaches to writing assessment in higher education, rendering text-based AI detectors inadequate and ethically problematic tools for evaluating student authorship. This presentation introduces the Write–Present–Defend (WPD) model as a multimodal, theoretically grounded assessment framework that addresses AI-related academic integrity concerns while simultaneously advancing oracy, metacognition, and disciplinary communication. Drawing on behavior-analytic theory and authentic assessment pedagogy, WPD repositions integrity as an assessment design problem rather than a surveillance challenge. The model's five stages increase the effort cost of AI substitution, provide contingent feedback, and develop skills valued across generations of learners and professionals. Attendees will examine implementation tools including dual rubrics, defense question banks, behavioral indicators of authorship, and a student AI-disclosure framework. Implications for teacher preparation programs, faculty professional learning, and institutional AI governance are discussed.
