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The Lead, Mid-Fall 2025
Get PDFThe Lead is an electronic newsletter produced by the Lindenwood College of Education & Human Services
From Prohibition to Preparation: Reframing Academic Integrity in the Age of AI
Get PDFThis study analyzes how U.S. universities reconfigure academic integrity during the 2024–2025 cycle in response to widespread generative AI adoption. The analysis foregrounds three loci: student ignorance and metacognitive blind spots; the expanded remit of Academic Integrity Officers prioritizing education over punishment; and deliberate AI-enabled misconduct that exposes the evidentiary limits of detection technologies. A mixed-methods design integrates a multi-site review at Arizona State University, Montclair State University, and Cornell University with synthesis of surveys, policies, and faculty development guidance. Findings show that detector outputs function as conversational prompts rather than adjudicative proof, necessitating dialogic resolution standards, process evidence, and due-process safeguards to reduce false positives and bias. Institutions that center syllabus clarity, assignment-level AI permissions, and transparent attribution norms report fewer gray-area violations and higher student comprehension of expectations. Pedagogical redesign—personalized, context-bound prompts; scaffolded drafting with reflections; in-class writing and oral defenses; and structured ―AI-in-the-open‖ tasks that demand critique and verification—reduces incentives to outsource cognition while strengthening targeted learning outcomes. The study maps integrity work to labor-market demands for AI fluency, arguing for frameworks that cultivate ethical AI competence rather than prohibitions that suppress skill formation. Attention to accessibility and neurodiversity remains pivotal; integrity regimes that ignore assistive use cases risk exacerbating inequities and chilling legitimate accommodations. The article proposes a sustainable governance model coupling principled authorization and attribution with evidence-based adjudication, faculty training aligned to curricular cycles, and continuous assessment improvement. Collectively, these strategies reposition academic integrity as a design problem aligned with AI literacy and graduate employability
Composition Pedagogy as AI‑Native Coding: From Design Kit to Scholarly Framework
Get PDFThis article advances a field-ready framework that reconceives first-year composition as AI-native coding, translating a complete “design kit” into scholarly method, evaluative protocol, and curriculum architecture. Background: Contemporary composition pedagogy emphasizes process, genre awareness, and collaborative revision; meanwhile, modern software practice operationalizes iteration through version control, test-driven development, and continuous integration. The uploaded kit demonstrates that these cultures are isomorphic: writing stages align with SDLC phases, and automated pipelines can lint prose, execute argument “tests,” and publish artifacts with auditable histories. Approach: The study systematizes that kit into (1) a conceptual map that recasts authorship as orchestration and verification, (2) a pipeline specification that integrates rhetorical linters, claim-evidence checks, retrieval-grounded fact audits, and CI dashboards, and (3) an assessment regime that grades specification quality, revision discipline, and process transparency alongside argument strength and source integration. Significance of results: The framework yields inspectable process evidence that reduces adjudication ambiguity, raises floor quality on conventions through automation, and reallocates instructor attention to higher-order reasoning; it further proposes a mixed-methods research program that couples CI telemetry with blinded ratings to estimate effects on argument adequacy, equity for multilingual writers via audit trails, and transfer across disciplines. By treating “voice” as measurable style alignment under constraints and “authorship” as documented governance over generative systems, the model offers a reproducible answer to integrity, workload, and scalability in an AI-saturated academy. The contribution is a discipline-legible, automation-forward blueprint that programs can adopt in enhanced, driven, or autonomous variants without requiring coding prerequisites, supported by ready-to-deploy rubrics, YAML exemplars, and policy templates
Identity and Representation in Contemporary Art: An Inclusive 400/500-Level Art History Seminar Course
Get PDFThis project is an upper-level art history seminar addressing identity and representation – specifically related to race, ethnicity, gender, and sexuality – in contemporary art. Primarily a discussion-based course, the course is focused on inclusivity and is highly structured, with weekly low-stakes assignments that provide students with ample opportunities to practice engaging with academic texts. Designed for students with varying levels of academic skills, it is built around current non-academic articles that students select via an online survey. Students then “unpack” the “big ideas” in each of the four chosen non-academic articles via a cluster of academic readings and videos with varying levels of difficulty (from a comedian’s TedX video on gender and sexuality, to a 4-page excerpt of Michel Foucault’s “Domain” in The History of Sexuality).
The final project deliverable consists of a syllabus, a list of sources for each of the non-academic articles, examples of guided reading tasks and questions, and notes (in this report) on how the content and assignments are crafted to promote student agency and academic inclusivity