See the Teaching and Learning Center’s schedule below for upcoming workshops, webinars, and open labs related to Artificial Intelligence.<\/p>\n

\n \n

AI in Higher Ed, ACUE Quick Study Course Accordion Closed<\/span><\/h4>\n <\/span>\n <\/div>\n <\/a>\n
\n \n\n
Available through ACUE Commons, the AI for Higher Ed Endorsement will empower you to integrate AI into your teaching strategy while maintaining academic rigor and integrity. From the ACUE Commons home page go to Quick Studies. All NAU faculty have access to the ACUE Commons.<\/p>\n
To register and sign in,<\/b> follow these instructions:<\/p>\n
Establish your account with the ACUE Commons by registering here.<\/a> Use your NAU email address. You will receive a confirmation email from Support@Acue.org<\/a>. (Learn more on this webpage: TLC\/ACUE Commons<\/a>)<\/p>\n<\/body><\/html>\n\n <\/div>\n<\/div>\n\n
\n \n
\n
AI 201 \u2013 \u00a0AI Intermediate Series Accordion Closed<\/span><\/h4>\n <\/span>\n <\/div>\n <\/a>\n
\n \n\n
This intermediate AI Learning series takes faculty beyond “good prompts” into repeatable AI workflows for teaching, research, and administrative productivity that is grounded in prompt\/context engineering and disciplined iteration. Participants will design an AI-enhanced assignment sequence with a grading approach that differentiates AI-assisted and AI-independent work in that assignment, as well as develop a responsible-use implementation plan that can be used in their courses to help align integrity, bias awareness, and privacy constraints. Each day is hands-on and artifact-driven, emphasizing verification, transparency, and practical adoption in real coursework and faculty need contexts. Facilitator: John Gartin<\/a><\/p>\n
Fridays | April 3, 10, 17 | 12:00 – 1:00 pm | Zoom<\/a><\/p>\n<\/body><\/html>\n\n <\/div>\n<\/div>\n\n
\n \n
\n
The AI Educational Double Bind: When to Lean In \u2013 and When to Refuse Accordion Closed<\/span><\/h4>\n <\/span>\n <\/div>\n <\/a>\n
\n \n\n
The Teaching and Learning Center will host a OneHE Live Webinar viewing of “The AI Educational Double Bind: When to Lean In – and When to Refuse” followed by a short discussion facilitated by Amy Rushall and our Student Academic Partners joining us. This webinar will focus on practical strategies, such as how to craft AI-resilient assessments or methods of convincing students that AI shortcuts will endanger their future careers.<\/p>\n
Wednesday, April 15 | 1:00 – 2:00 pm | Cline Library AI Hub<\/a><\/p>\n<\/body><\/html>\n\n <\/div>\n<\/div>\n<\/p>\n
AI Week | March 23 – 27, 2026<\/strong><\/h2>\n
Over the past year, faculty engaged in Transformation through Artificial Intelligence in Learning (TRAIL) projects, incorporated AI into their courses and\/or studied the use of GenAI tools in research, and are now showcasing what they learned through AI Week’s annual TRAIL Blazer Showcase.<\/p>\n
AI Week has concluded for 2026! Each presentation is described below and was recorded separately during AI Week. Recordings will be available on this webpage in mid-April.<\/p>\n\n
\n \n
\n
2025-2026 TRAIL Blazer Showcase Presentations Accordion Closed<\/span><\/h4>\n <\/span>\n <\/div>\n <\/a>\n
\n \n\n
\n
\n
Reflecting Upon Design Trade-offs in Software Engineering using LLM-Generated Feedback<\/strong>
\nPresented by Marco A. Gerosa, School of Informatics, Computing, and Cyber Systems
\nWe explored how to integrate AI-generated feedback into software engineering education to enhance students’ critical thinking about design trade-offs and software quality attributes. Assignments in CS386 and CS440 prompted students to analyze AI suggestions, reflect on their applicability, and justify acceptance or rejection. The approach fosters analytical skills, promotes AI literacy, and prepares students for AI-assisted development.<\/p>\n
From Python to Copilot: Scaling an AI Chatbot to Support Critical Thinking in Research Methods<\/strong>
\nPresented by Sara Kien, Department of Psychological Sciences
\nThis presentation showcases the migration of Reese Erch, an AI chatbot designed to support critical thinking in research methods, from a standalone Python application to Microsoft Copilot. The move enables 24\/7 access across a broad range of research methods courses and disciplines, dramatically expanding scalability and student reach. The session will highlight design decisions, instructional use cases, and a proposed plan for collecting data on student interaction, engagement, and perceived learning benefits.<\/p>\n
AI is Not Very Good at Tax: Accounting Students’ Validation of AI and the Internal Revenue Code<\/strong>
\nPresented by Landi Morris, Department of Economics, Finance, and Accounting
\nStudents are required to engage with AI throughout the semester to develop an understanding of its capabilities and limitations. They are asked to prompt AI to prepare a tax memorandum related to tax law introduced in the One Big Beautiful Bill Act. Students then validate AI’s work using independent tax research software. Over the course of the semester, students report an increased use of AI and improved understanding of its application and limitations.<\/p>\n<\/div>\n<\/div>\n
FACTBot: Faculty Assistant for Critical Thinking<\/strong>
\nPresented by Michelle Miller, Department of Psychological Sciences
\nCritical thinking is a particularly difficult skill to address in college courses. This project tests a custom GPT that helps suggest and build activities to reinforce critical and higher-order thinking aligned with a specific discipline or field, based on a specific set of resources provided by the creator of the GPT.<\/p>\n
Using GAI in Lesson Planning<\/strong>
\nPresented by Marti Canipe, Department of Teaching and Learning
\nI will share the results of an intervention that helped elementary education majors learn to use GAI as part of their lesson planning process. These results include how students used or did not use GAI and their perceptions about the use of GAI.<\/p>\n
From Perils to Pedagogy: Generative Artificial Intelligence as Forms of Visual and Verbal Communication in the Introductory Communication Analysis Course<\/strong>
\nPresented by Jermaine Martinez, School of Communication
\nGenerative A.I. hallucinations and algorithmic bias pose risks for higher education, yet within COM101’s focus on applying communication theory to public messages, these same features become pedagogical opportunities. They reveal Anton’s (2023) notion of “superabundance,” showing how GenAI draws from sprawling histories of human symbolism. This project demonstrates how we can shift from peril to pedagogy by introducing students to receiver-oriented, critical, and media-ecological frameworks to identify and analyze algorithmic bias and describe how GenAI hallucinations often feel “truthful.”<\/p>\n
Learning with Large Language Models through a Distributed Cognition Lens: Findings from an Exploratory Study<\/strong>
\nPresented by Priyanka Parekh, Center for Science Teaching and Learning
\nThis exploratory study found that undergraduates engaged GenAI as a dynamic partner within a distributed learning system across disciplines. Learning emerged through iterative exchanges where reasoning, problem-solving, and trust were co-constructed. These interactions were shaped by disciplinary norms, individual ability and willingness to interact with GenAI, and personal and professional goals. Agency and identity were negotiated when students actively decide when to lead, critique, or delegate tasks, and position themselves as certain kinds of learners.<\/p>\n
Can AI generate qualitative data for software engineering research?<\/strong>
\nPresented by Marco Gerosa, School of Informatics, Computing, and Cyber Systems
\nQualitative research is extensively used to understand human factors in software engineering, but it faces significant challenges in recruiting participants. Large language models (LLMs) have demonstrated strong capabilities in generating human-like text, raising questions about whether they can augment or serve as surrogates for human participants in certain qualitative research contexts. In this talk, we discuss situations where AI can and cannot mimic human behavior.<\/p>\n
Conversations with Conservationists: Using AI to Aid Conservation Education<\/strong>
\nPresented by Derek Uhey, School of Forestry
\nAI can allow students to go beyond readings to engage with famous conservationists, asking them questions about modern day issues. In this presentation I’ll explore how successful these AI lessons were and student attitudes towards using AI in conservation. Overall, students valued learning AI tools and having conversations with AI generated conservationists but had ethical concerns about using AI in conservation and education. As a class we formed a code of conduct to guide use of AI in the classroom and the field of conservation.<\/p>\n
See, Touch, Learn: Enhancing DPT Students’ Palpation Skills and Anatomical Knowledge with AI Musculoskeletal Ultrasound<\/strong>
\nPresented by Michael Morgan, Department of Physical Therapy and Athletic Training
\nThis presentation highlights a TRAIL-funded pilot integrating AI-enhanced musculoskeletal ultrasound into a first-year DPT anatomy course to help students see, touch, and learn more effectively. After introducing the technology in accessible terms for a cross-disciplinary audience, the session presents detailed results across cognitive, psychomotor, and affective learning domains. Data demonstrate meaningful improvements in anatomical understanding, palpation accuracy, and learner confidence. The project offers a scalable model for transforming anatomy education with AI-supported imaging.<\/p>\n
From Classroom to Clinic: Workshop Series Integrating AI into Healthcare Education Training<\/strong>
\nPresented by Sarah Bolander, Department of Physician Assistant Studies; Zac Baker, College of Health and Human Services; and Carrlene Donald, Department of PA Studies
\nThis session highlights a three-part workshop series that equips graduate healthcare students with essential AI skills. Covering ethical foundations, practical applications in didactic training, and integration into clinical practice. Attendees will gain insights into how AI can support learners, with examples from healthcare training. This session will also leverage AI tools to create personalized, high-quality study resources aligned with adult learning theory.<\/p>\n
Using the Socrates Learning Tool to Promote Interactive Learning in a Large Class<\/strong>
\nPresented by Nick McKay, School of Earth and Sustainability
\nThis project integrated Socrates, an AI-powered teaching tool, into ENV 115 (Climate Change), a large-enrollment course serving 130-200 students. Socrates uses Socratic questioning to recreate small-class learning experiences at scale, guiding students through personalized inquiry-based discussions. The tool enhances critical thinking while automating quiz generation and identifying student misconceptions. Building on successful pilots at Cornell in similar courses, this implementation demonstrates how AI can effectively scale personalized learning in large lectures while optimizing faculty effort and improving accessibility.<\/p>\n
Enhancing CS136 Lab Learning with an AI-driven Conversational Agent<\/strong>
\nPresented by Ana Paula Chaves, School of Informatics, Computing, and Cyber Systems
\nIn this presentation, we will present the results of using an AI-driven Conversational Agent to tutor CS 136L students when developing programming skills. The agent was developed by an NAU lab and embedded into a coding platform that students use to write code. The outcomes show positive results when students use it for problem-solving tutoring, but over-reliance on the agent results in a lack of independence when writing code.<\/p>\n
Empowering Business Students to Thrive in the AI Era: A Practical and Research-Driven Approach<\/strong>
\nPresented by Yichuan Wang, Department of Management, Marketing, and Information Systems Management
\nThe presentation, Empowering Business Students to Thrive in the AI Era: A Practical and Research-Driven Approach, showcased real-world applications of artificial intelligence across industries. Guest speakers from DriveTime, Circle K, and Intel introduced how AI had been applied to supply chain management, pricing strategies, and marketing practices. I also presented my research on text mining of ESG reports, illustrating how students connected academic methods with practical business challenges to prepare for future success.<\/p>\n
Enhancing Research Proficiency in Higher Education: Analyzing the Impact of Afforai on Student Literature Review and Information Synthesis<\/strong>
\nPresented by Delaney La Rosa, Beth McManis, & Jennifer Rossetti, College of Nursing
\nThis presentation explores emerging research on how students are using AI-supported research tools to transform the literature review process. In this early-stage study, NAU students reflect on their experiences using a selected AI platform to locate credible sources, evaluate evidence, and synthesize complex information more effectively. We share the key takeaways, the questions it raised, and what this may mean for teaching research in an AI-enabled academic landscape. Attendees will leave with practical insights for thoughtfully integrating AI into research instruction while strengthening, not replacing, critical thinking and scholarly rigor.<\/p>\n
Peacebuilding and AI: Designing VR Experiences for Israeli-Palestinian Understanding<\/strong>
\nPresented by Emily Schneider, Criminology and Criminal Justice
\nIn this presentation, I will discuss my research on MEJDI, an Israeli-Palestinian peacebuilding organization that uses tourism to foster tolerance and understanding in Israel\/Palestine, and our exploration of AI and virtual reality as tools to expand its impact. I will focus on the design of a VR program that will allow participants to safely engage with communities and sites typically inaccessible due to political, legal, or safety barriers. The presentation will focus on the ethical, ideological, and political questions these immersive technologies raise in conflict settings.<\/p>\n
AI as a Creative Partner: Teaching Scalable Content Production in Strategic Communication<\/strong>
\nPresented by Amy Dryden, School of Communication
\nThis project introduced Strategic Communication students to real-world AI workflows used in modern advertising. Students created original content and used generative AI to repurpose it into full, multi-platform campaigns. The experience strengthened their strategic thinking, ethical AI use, and professional portfolios, preparing them for internships and jobs that increasingly rely on AI-assisted content creation.<\/p>\n
The Future of Learning: Integrating AI into Teaching Cognition and Psychology of Creativity Courses<\/strong>
\nPresented by Viktoria Tidikis, PhD, Department of Psychological Sciences
\nIn this presentation, I will showcase how AI tools were integrated into two psychology courses to enhance creative and cognitive learning. Students engaged with generative AI as a brainstorming partner, a study tutor, and a cognitive-bias analyzer, allowing them to compare human and AI idea generation, practice critical evaluation, and explore creativity. These assignments demonstrated AI’s potential as both a creativity catalyst and a critical-thinking tool.<\/p>\n
Integrating AI-Enhanced Creative Workflows in Animation and Visual Communication Education<\/strong>
\nPresented by Chris Johnson, School of Communication
\nThis presentation explores how generative AI tools can be integrated into creative research and production workflows in animation and visual communication education. Drawing on classroom pilots and studio-based experiments, I will share strategies for using AI as a sketching, ideation, and prototyping partner rather than a replacement for creative labor. The talk will address pedagogical design, ethical use, and assessment, and demonstrate how AI-enhanced workflows can support iteration, visual thinking, and research-driven making across multiple creative courses.<\/p>\n<\/body><\/html>\n\n <\/div>\n<\/div>\n\n
\n \n
\n
2024-2025 TRAIL Blazer Showcase Presentations Accordion Closed<\/span><\/h4>\n <\/span>\n <\/div>\n <\/a>\n
\n \n\n
Learn more about the innovative work our TRAIL-supported faculty did to incorporate AI into their courses. Each presentation is described below and was recorded separately during AI Week: March 24-28, 2025. Click on this link to access the ten TRAIL Blazer Showcase Video Presentations<\/a>.<\/p>\n
Lessons Learned while Integrating GenAI in ENV 360: Enhancing Fieldwork, Classwork, and Technical Writing<\/strong>
\nPresented by Nicholas McKay, Associate Professor, School of Earth and Sustainability<\/p>\n
I integrated generative AI (GenAI) into multiple aspects of an upper-division Environmental Sciences course, supporting field and classwork, and technical writing. Students used GenAI for multiple components of the class, including transcribing field and lecture notes, studying for exams and refining technical reports. Some applications were more successful than others, with feedback on writing and exam preparation being the most successful. Despite some hiccups, students appreciated the opportunity to learn to work with emerging tools.<\/p>\n
The Perils and Possibilities of Using Generative AI in Indigenous Literary Studies<\/strong>
\nPresented by Jeff Berglund, Professor, Department of English<\/p>\n
Students from Fall 2024 classes on post-Civil War American Literature and U.S. Multi-Ethnic Literature will join me to share their experiences using AI, specifically Co-Pilot, in units featuring Indigenous writers. Our discussion will focus on the best uses of AI we discovered as well as the limits and dangers of relying on AI-generated information with limited access to culturally sanctioned knowledge. Contributors: Jeff Berglund with Daniela Alfaro Alas, Andi Casten, Sydney Freeland, Kayla Garcia, Skye Kind, Lincoln Lambert, Taryn Toombs, and Paige Yaklin.<\/p>\n
Tackling AI Anxiety with Art Students<\/strong>
\nPresented by David Politzer, Director, School of Art + Design<\/p>\n
During the Fall 2024 semester, Politzer integrated AI tools into ART 499: Interdisciplinary Critique, a course focused on analyzing and discussing student artwork. The goals were to ease AI anxiety and enhance students’ preparation for critique. Students used ChatGPT to role-play critiques and attempted to recreate their art projects using Midjourney. In his presentation, Politzer will share insights and outcomes, and demonstrate sample assignments.<\/p>\n
Educational Leaders and AI: Exploring the Emotional Side of AI Adoption<\/strong>
\nPresented by Blue Brazelton, Associate Professor, Department of Educational Leadership<\/p>\n
Technology and unfounded enthusiasm or fearful avoidance, pick your favorite trope. Across 3 graduate courses covering the intersection of education and technology, my work examined the ways emotion affected students studying educational leadership. Using the Technology Acceptance Model as a framework, the AI experiences and emotions of over 50 graduate students are contextualized as part of an on-going conversation about disruptive technology and schooling.<\/p>\n
Dialogues with Generative AI: Exploring Human-AI Adversarial Collaborations<\/strong>
\nPresented by Jonna Vance, Associate Professor, Philosophy Department<\/p>\n
This talk discusses an ongoing project to help students improve their reasoning and communication through adversarial-collaborative dialogues with large language models. The talk describes a series of pedagogical challenges professors independently face and how the project has helped meet them. The challenges include: helping students understand the costs\/benefits of offloading work to AI; helping students effectively reason with others; providing real-time non-threatening critical feedback to students; and improving students’ ability to accurately identify and explain patterns of excellence\/deficiency in their own work.<\/p>\n
Improving Student Learning Outcomes with a Generative AI Peer Review Partner<\/span><\/strong>
\nPresented by Kiley Huntington, Assistant Clinical Professor, Department of Social Work<\/p>\n
The presentation will discuss the use of generative AI as a peer review partner in an online asynchronous undergraduate writing intensive course. The goal of the project was to improve student writing outcomes by providing students with access to a supportive “peer reviewer” throughout the course. The presentation will also discuss the challenges and opportunities of using generative AI in the classroom.<\/span><\/p>\n
Fostering Solution Diversity: Teaching Software Engineering through LLM-Generated Alternatives<\/strong>
\nPresented by Marco A. Gerosa, Professor, School of Informatics, Computing, and Cyber Systems<\/p>\n
Numerous LLMs are available, giving access to diverse solutions for the same problem. Students need to develop skills in analyzing and selecting context-appropriate approaches. To address this, we tasked Software Engineering and Software Architecture students with generating and comparing multiple solutions and reflecting on the process. In this presentation, we will discuss student perceptions and benefits of this approach and how this initiative fits in the overall research conducted in our group.<\/p>\n
An AI Literacy Module for Students Across the Disciplines<\/strong>
\nPresented by Alana Kuhlman, Associate Teaching Professor, English<\/p>\n
As a relatively new and constantly emerging technology, students tend to have varying levels of knowledge about generative AI and its ethical and appropriate use inside and outside of the classroom. Likewise, faculty may exhibit similar discrepancies in generative AI knowledge, usage, and classroom instruction\/integration. This TRAIL project aimed to fill these gaps by developing a generative AI literacy module for students that was piloted in ENG 100 and ENG 405–writing support courses offered by the Lumberjack Writing Center–and by sharing this module for possible use with faculty across the disciplines. This presentation will provide an overview of the module and the results of an IRB-approved study that explored students’ and Writing Assistants (tutors) experiences with the AI module and any perceived benefits.<\/p>\n
Harnessing AI in the Strategic Communication Classroom and Workplace<\/strong>
\nPresented by Janice Sweeter, Associate Professor, School of Communication<\/p>\n
My research explores the rapid adoption of generative artificial intelligence (AI) interventions in the classroom and exposure to AI in the strategic communication workplace, culminating in a collaborative study assessing student awareness and understanding of AI, AI contribution toward career readiness, and other factors.<\/p>\n
Chatbot activities in the Spanish classroom: challenges and possibilities<\/strong>
\nPresented by Yuly Asención-Delaney, Professor, Department of Global Languages and Cultures<\/p>\n
This session addresses the benefits and challenges of using chatbots in Spanish classes at NAU as tools that can simulate real-life interactions in the target language. The presenter will describe some chatbot activities implemented in Spanish classes and discuss students and instructors’ perceived usefulness of this AI-powered language practice.<\/p>\n<\/body><\/html>\n\n <\/div>\n<\/div>\n<\/p>\n\n
\n \n
\n \nOffice of the Provost Initiatives on AI\n\n\n<\/a>\n <\/div>\n<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"
Learning Opportunities on AI Topics\u00a0 See the Teaching and Learning Center’s schedule below for upcoming workshops, webinars, and open labs related to Artificial Intelligence. AI Week | March 23 – 27, 2026 Over the past year, faculty engaged in Transformation through Artificial Intelligence in Learning (TRAIL) projects, incorporated AI into their courses and\/or studied the […]<\/p>\n","protected":false},"author":2612,"featured_media":1855,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","ring_central_script_selection":"","footnotes":""},"class_list":["post-4737","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/pages\/4737","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/users\/2612"}],"replies":[{"embeddable":true,"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/comments?post=4737"}],"version-history":[{"count":100,"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/pages\/4737\/revisions"}],"predecessor-version":[{"id":6218,"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/pages\/4737\/revisions\/6218"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/media\/1855"}],"wp:attachment":[{"href":"https:\/\/in.nau.edu\/teaching-learning-center\/wp-json\/wp\/v2\/media?parent=4737"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}