Upper Peninsula Teaching & Learning Conference - 2026

Any student can have a bad day.   But giving students multiple attempts on exams is fraught with issues of fairness, exam integrity, and student preparation.   In this session, we'll discuss a "mulligan" system used in a very large class (300+)  that tries to balance these issues using online exams with large "pools" of questions.   We'll explore how to determine who shoud be eligible for a "second shot" as well as making sure students are prepared to make the most of it.

Using a custom, web‑based tool—SwiftFlock (swiftflock.app)—you can create well‑matched groups that respect competencies, gender identities, existing friendships, physical location, or any other rule you define; once the groups are formed you can instantly assign discussion prompts, capture real‑time conversations, and post a follow‑up survey to see if the activity improved targeted competencies, and in this session we’ll walk through a quick live demo of the tool, showing how to set up matching criteria, launch an activity, and collect analytics while also exploring what makes a truly well‑matched group.

This session explores the potential of generative AI to dramatically accelerate the development of Open Educational Resources (OER). OER are teaching materials that can be retained, reused, revised, remixed, and redistributed due to their license. During the 2021-2022 academic year, college students spent up to $1,240 per year on books; this cost led 63 percent of students to decide not to purchase a textbook. OER may help reduce this financial barrier by providing access to free or low-cost instructional materials. Additionally, the use of OER allows instructors to customize course materials, better aligning them with learning objectives.


OER are in the public domain; therefore, instructors can use tools like generative AI to assist in many tasks relating to their creation. This presentation will introduce and demonstrate the "AI Sandwich" framework for OER creation using AI. The “AI Sandwich” framework has the instructor provide the initial outline, the AI generates a draft, followed by the instructor reviewing and editing the content.


I will showcase the successful application of this technique at Northern Michigan University in the creation of multiple OER textbooks, including Personal Wellbeing, Health Information Literacy, and ECG Interpretation. This practical demonstration will illustrate how the "AI Sandwich" framework can streamline the process, enabling instructors to produce high-quality, customized course materials that are better aligned with specific learning objectives, ultimately improving equitable access and student outcomes.

Generative AI tools are increasingly used in teaching and learning, yet many classroom implementations rely on familiar formats such as quizzes, summaries, and short responses. While useful, these approaches can overlook opportunities for deeper engagement, reflection, and skill development.


This interactive session introduces ten practice-based learning activities that instructors can use with large language models (LLMs) to support higher-order thinking and meaningful student interaction. Drawing on recent work in instructional design and AI-supported learning, participants will explore activities such as Rapid Fire questioning, AI-facilitated post-mortems, adaptive case studies, devil’s advocate debate, decision-based simulations, and assumption-testing exercises. These approaches position AI as a facilitator, challenger, and reflective partner rather than a replacement for human judgment.


Participants will experience several of the activities in real time and discuss how they can be adapted across disciplines, modalities, and course levels. The session will also introduce practical strategies for helping students engage with AI responsibly by distinguishing between ethical guidelines for AI use and integrity-driven behaviors such as verification, transparency, and critical questioning.


Attendees will leave with adaptable activity templates, starter prompts, and practical ideas for incorporating AI-supported practice into their own courses while maintaining human-centered learning design.

The applied improvement project implemented professional development training to boost faculty readiness for ethical AI integration in the classroom. Guided by Magana’s T3F Framework, it addressed questions on how an online AI module would support ethical strategies, confidence, implementation across disciplines, understanding of benefits, and training effectiveness. Faculty from varied disciplines and roles participated, with data gathered via semistructured interviews and an AIP Implementation Journal, analyzed through Braun and Clarke’s thematic approach. Key themes from interviews included transparency, ethical AI use, academic integrity, AI literacy, classroom integration, workload, hesitancy, and training efficiency, while the journal tracked challenges and successes, showing the training's value in advancing AI integration literature. Recommendations focus on expanding training, creating AI policies, and offering ongoing support to reduce resistance and build confidence

Generative AI is rapidly working its way into the classroom. How do we use these technologies? What are AI’s strengths and limitations? What even is Generative AI? As educators, we must understand emerging technologies as they evolve to support our students’ learning needs!


This talk will touch on findings from a semester-long, student-driven research study regarding the benefits of Generative AI in math education. Presenters will dive into how prompt engineering can be used to create lesson plans and classroom activities. There will be a short demonstration showing how educators can incorporate AI tools into their lesson-planning process.

Many instructors are curious about AI but hesitant to try it—concerned about academic integrity, accuracy, and “opening the floodgates.” This 20-minute mini-session is designed to break the AICE: the awkward first step where AI feels intimidating or risky. Using a familiar, low-stakes starting point—simple AI tools built into Blackboard Ultra—we’ll help faculty experience AI as a practical helper: C-3PO (clarifies, organizes, translates expectations) rather than Terminator (takes over, threatens learning).
Participants will see two quick, high-impact workflows:

1. Rubric drafting to clarify expectations and speed up feedback
2. Question generation for low-stakes practice/self-check quizzes that improve engagement and success

We’ll emphasize one guiding rule—AI drafts, humans decide—and provide quick “safety checks” for accuracy, alignment, and tone. Attendees will leave with a one-page AICE Starter Kit and a simple way to model responsible AI use.

The current generation of college students are accustomed to apps, internet searching and AI to answer questions. With the push towards Artificial Intelligence fluency in the classroom and workplace, how do we develop critical thinking skills related to data analysis?
 
Recent news articles in the Wall Street Journal highlight this environment with a WSJ article on UC – San Diego noting that 1 in 12 incoming freshmen can’t do middle school math. According to another article “AI will get better and better, but the most important skill in the white-collar field now is critical thinking” How do we get junior employees to learn without AI so that they have the cognitive skills to do more complex jobs 1-5 years into the workforce?
 
60% of my current students self-reported little or no Excel experience before starting my introduction to decision science class. Follow-on courses focus on business analytics and higher level critical thinking skills, will they have the skills necessary to succeed? Using Excel allows students to see the data and mathematical relationships clearly without being obscured by complex code. The challenges of working in Excel to teach critical mathematical and thinking skills will be presented with a structured discussion of what needs to be done in the future.