Publications & Presentations
A record of peer-reviewed scholarship, conference presentations, and institutional publications focused on human-centered, ethical AI integration in higher education. Full publication record available on Google Scholar and ResearchGate.
This paper introduces the Team Dynamics and Conflict Resolution (TDCR) module — a structured curriculum for helping students form effective project teams, navigate conflict, and collaborate productively. The paper proposes integrating generative AI through the deployment of the Project Pal GPT, trained on the TDCR module. It also introduces the Foundational Framework for GenAI Literacy and Deployment — a five-stage model — and the 210-point Human-AI Collaboration Rubric, marking the origin of key frameworks and tools that have since been extended across multiple publications and deployed agents.
A practitioner-focused paper and workshop guiding engineering educators through the process of building and implementing custom AI assistants for their courses using the PCTII cycle — without requiring any coding knowledge. Demonstrates how educator-designed AI agents can support student learning while maintaining ethical accountability through the EITL governance architecture.
Presents a novel framework for the ethical assessment of AI applications in industry, grounded in the seven pillars of trustworthy AI established by the European Union. Moves beyond technical compliance toward an ethically driven approach organized around five thematic areas: Ethical Governance and Accountability, Operational Procedures and Security, Human-AI Interaction, Data Management and Governance, and Stakeholder Engagement and Environmental Impact.
Examines how the advent of generative AI requires a fundamental rethinking of what constitutes ethical assessment in higher education — moving beyond detection and enforcement toward assessment designs that are purposeful, transparent, and aligned with student learning rather than merely surveillant.
This paper presents the Fact-O-Fictionist GPT — a story-driven engineering problem generator that contextualizes technical content through narrative. Introduces 14 storytelling characteristics (10 primary, 4 secondary) as a framework for designing and evaluating AI-generated instructional content, and presents the EITL two-layer governance architecture for maintaining pedagogical oversight in AI agent deployment.
Educational AI agent design must treat usability, pedagogy, and metacognition as three co-equal design requirements. The PCTII cycle already embeds all five Nielsen usability attributes — this paper names and formalizes what was always there, providing a theoretically grounded framework for practitioners designing custom AI agents for educational contexts.
Ethical behavior in higher education does not emerge in isolation from the environments in which students learn — it is shaped by task design, expectations, pressure, perceived fairness, and the tools available. This chapter introduces the Safe Ethical Zone (SEZ) and the LTTR framework, arguing for a shift from compliance-based responses to ethics-by-design: intentionally building learning environments that support ethical action before misconduct occurs. Includes an Ethical Recovery Framework for growth-oriented responses when students do cross ethical boundaries.
This paper proposes a sociotechnical usability typology of educational AI agent failure — examining not just what goes wrong when AI agents fail in higher education contexts, but why, and what structural, pedagogical, and design conditions make failure more likely. Situated within a special issue that challenges the field's bias toward success narratives, this work contributes an honest, diagnostic framework for understanding and moving beyond AI agent failure.
Proposes a two-stage AI literacy framework for higher education that addresses the dual responsibility faculty carry as both AI learners and AI literacy educators. Stage 1 covers faculty AI literacy through the PIDEU cycle (Prepare, Introduce, Deploy, Evaluate, Update). Stage 2 provides faculty with tools and strategies to embed AI literacy into curriculum design, instructional practice, and assessment through the PSS model. Repositions AI literacy as a core faculty competency rather than an optional professional development topic.
A Quick Hit design case presenting the Management Portfolio as a scaffolded learning intervention designed for working adult professionals. The portfolio functions simultaneously as a learning tool and a workplace performance artifact — bridging the gap between academic assessment and professional practice in management and technology settings.
This paper formalizes the theoretical and pedagogical foundations of a course-integrated AI prompt library designed to give students a structured, ethical pathway to AI use. Six distinct prompt types address different cognitive moves, positioning AI as a sparring partner rather than an answer key. Central to the framework is the principle of educator agency — the library returns design authority to the instructor, who determines how, when, and to what end AI enters the learning experience. The paper situates the framework within self-regulated learning theory, Socratic method, and Knowles' andragogy, and contributes a replicable design model for educators across disciplines. .
Facilitated a hands-on workshop introducing a structured, educator-designed AI prompt library as a tool for ethical and pedagogically sound AI integration in higher education courses. Participants engaged directly with the three design principles and six prompt types, and left with a starter plan for building a course-specific prompt library — positioning student thinking, not AI output, as the center of the learning experience.
Presented the dual-layer AI literacy framework — PIDEU for faculty and PSS for students — to an international audience of higher education researchers and practitioners, situating it within the global landscape of AI literacy frameworks and institutional gaps.
Presented trauma-informed pedagogy and care ethics for faculty developers, accompanied by the Trauma-Informed & Care Pedagogy Assistant GPT — demonstrating how AI tools can serve the full humanity of educators, not just their instructional efficiency.
Keynote address on ethical AI use for K-12 educators — a population that rarely receives research-grounded guidance on responsible AI. Focused on practical integration strategies and how to support students in developing healthy, critical relationships with AI tools.
Full workshop guiding engineering educators through the PCTII cycle to build and deploy custom AI assistants — no coding required. Demonstrated classroom-tested agents and provided hands-on guidance for ethical AI agent design.