Intersectional Realities
Is There a Teacher in This Class? : Revisiting What it Means to Teach
Paper Presentation in a Themed Session Kelly Van Andel
Using Stanley Fish’s book "Is There a Text in This Class?" and reader response theory as a touchstone, this paper examines what it means to be a teacher today. In particular, it explores how the growing emphases on AI, technology, best practice frameworks, and testing on the one hand, and the diversity, inclusion, and equity of the learner on the other, have created an ethos of mechanized individuation that has changed the roles of teachers and redefined what it means to teach. It then considers Park Palmer’s argument about the “I” and “Self” who teaches in relation to such. Finally, it ponders if the real presence of a self who teaches is a romantic fantasy or an obtainable reality that can provide hope and meaning for the hearts of teachers, if not education itself.
Integrating Artificial Intelligence in Teacher Education en la Frontera: Enhancing Literacy Instruction and Ethical Frameworks for Culturally Diverse Teacher Candidates View Digital Media
Paper Presentation in a Themed Session Heriberto Godina
This study introduces the concept of AITED (Artificial Intelligence in Teacher Education) to describe the integration of AI technology in teacher preparation programs. Using an action research methodology, the study aims to enhance teaching and learning outcomes for teacher candidates of Mexican descent in the Southwestern United States. The instructional intervention, grounded in an active learning approach, adjusted teaching strategies to adapt AITED to this culturally diverse population. These aspiring teachers are being prepared to serve as literacy educators in underserved, low-income communities facing declining literacy rates. The focus of the intervention is on participants' mastery of the Science of Teaching Reading (STR). Data collection is ongoing and follows a reiterative and continuous cycle of analysis, application, and reflection. Collected data includes reflective narratives, class discussions, and various assignment artifacts. Initial findings show mixed attitudes toward AITED; while many participants were initially unaware of its potential, they grew to recognize its creative and practical utility. Participants also raised ethical concerns, particularly regarding academic integrity. In response, contrapuntal exercises were introduced, blending AI-generated content with personal demonstrations of mastery to promote balanced and ethical AI usage. The collaborative nature of the action research where participants also became stakeholders increased participants' confidence in using AI. This study offers valuable insights for educators interested in integrating AI into teacher preparation programs, underscoring the need for ethical frameworks that ensure content mastery, uphold teacher autonomy, and maintain a culturally-responsive approach, particularly for future educators preparing for certification exams.
The Road Less Taken: A Multiple Case Study of Alternative Learning Program Educators in Minnesota View Digital Media
Paper Presentation in a Themed Session Ann Elizabeth Thole
This qualitative, multiple case study explored educators’ perceptions and measurements of success and approaches utilized in maximizing learner potential at three different Minnesota alternative learning program sites. Sites included Greater Minnesota, suburban, and urban settings. Methods involved eight one-on-one participant interviews, one focus group, and three observations of classroom physical space across the three programs. Participants had at least three years working in alternative learning and held tenure status according to the Minnesota Department of Education. Within-case-analysis produced 12 themes across the cases with three themes corresponding to each site and the focus group. Cross-case analysis disclosed three overarching themes: personalization, transition, and relationships. First, the personalization of learning contributed to learner success. Second, students’ ability to transition from one step to another, whether a small benchmark or after high school equated learner success. Third, relationships rendered a significant approach towards maximizing learning potential, particularly the impact of building and sustaining relationships in a positive manner. Path-Goal Theory, Bio-ecological Model of Development Theory, and the Theory of Academic Optimism and Student Achievement served as pillars to examine cross-case findings. Based on the findings, alternative learning program educators constructed asset-based pathways for their students. Recommendations to and implications for key stakeholders serve as vehicles to transform the perception of alternative learning programs.
Transforming Assessment Paradigms: The Role of Generative AI as a Disruptive Force in Higher Education View Digital Media
Paper Presentation in a Themed Session Matthew Montebello
The advent of Generative AI technologies has heralded a transformative era across various sectors, with higher education experiencing a profound upheaval particularly within the domain of assessment. This paper explores the disruptive potential of Generative AI in reshaping traditional evaluation paradigms, challenging long-standing practices of essays, examination, grading, and feedback. By critically examining emerging AI-enabled assessment tools and methodologies, the study highlights opportunities for more cognitive-intensive, effective, and educative evaluation processes. However, it also addresses pressing concerns surrounding academic integrity, equity, and the ethical implications of AI-generated content. Through a comprehensive analysis of current trends, case studies, and future outlooks, this research aims to provide educators, administrators, and policymakers with a nuanced understanding of how Generative AI is redefining assessment in higher education calling for innovative frameworks that harness its potential while safeguarding academic standards and integrity. Ultimately, this paper advocates for a paradigm shift that embraces AI as a catalyst for more meaningful and equitable assessment practices in the digital age.
