Dr. C. Edward Watson to Present at UW-Green Bay: Teaching with Artificial Intelligence (Aug 29, 2:00 p.m)

Preparing Students for Life Beyond College: Embracing AI as Essential Learning

UW-Green Bay is excited to welcome Dr. C. Edward Watson, Vice President for Digital Innovation at the American Association of Colleges and Universities and co-author of “Teaching with AI: A practical guide to a new area of human learning.” Mark your calendars as we kick off a new fall semester together with Dr. Watson’s presentation and read on to learn more about the presentation topic! This event is for UWGB faculty and staff. If you did not receive an Outlook invitation for this presentation, please send an email to CATL, and we will get you added to the event!

  • When: Thursday, August 29, 2024, at 2:00 p.m.
  • Where: Virtual presentation hosted in Zoom

Preparing Students for Life Beyond College: Embracing AI as Essential Learning

Generative AI tools have had an astonishingly quick impact on the ways we learn, work, think, and create. While higher education’s initial response was to develop strategies to diminish AI’s influence in the classroom, many would now argue that AI competencies and literacies must be embraced as essential learning for most colleges and universities. These responses and realities create a challenging tension that higher education must work to resolve. Drawing from the presenter’s new book, Teaching with AI: A Practical Guide to a New Era of Human Learning (Johns Hopkins University Press, 2024), this presentation and discussion will detail the challenges and opportunities that have emerged for higher education. The core focus of this keynote will be on concrete approaches and strategies higher education can adopt, both within the classroom and across larger curricular structures, to best prepare students for the life that awaits them after graduation.

Presenter Bio

Photo of Eddie Watson

C. Edward Watson, Ph.D., is the Vice President for Digital Innovation at the American Association of Colleges and Universities (AAC&U). He is also the founding director of AAC&U’s Institute on AI, Pedagogy, and the Curriculum. Prior to joining AAC&U, Dr. Watson was the Director of the Center for Teaching and Learning at the University of Georgia (UGA) where he led university efforts associated with faculty development, TA development, learning technologies, and the Scholarship of Teaching and Learning. He continues to serve as a Fellow in the Louise McBee Institute of Higher Education at UGA and recently stepped down after more than a decade as the Executive Editor of the International Journal of Teaching and Learning in Higher Education. His most recent book is Teaching with AI: A Practical Guide to a New Era of Human Learning (Johns Hopkins University Press, 2024). Dr. Watson has been quoted in the New York Times, Chronicle of Higher Education, Inside Higher Ed, Campus Technology, EdSurge, EdTech, Consumer Reports, UK Financial Times, and University Business Magazine and by the AP, CNN and NPR regarding current teaching and learning issues and trends in higher education.

UWGB Free Access to Teaching with AI

UWGB faculty and staff can get free unlimited access to the text Teaching with AI through the UWGB library!

Communication Methods & Recommendations

A communication challenge you might face whether you’re teaching in an in-person class, a hybrid one, or one that’s completely online, will be to try to communicate the same information to students who are not able to attend the in-person class, or to communicate with students who may have fallen behind. Remember, you should strive to provide equitable communication to all students, and opportunities for students to communicate with you and with each other, regardless of how they’re engaging with the course. Not only will some instructors have to consider how to communicate important information to students in different physical locations, but also across modalities and time.

The expandable sections below offer some additional information when considering how to communicate instructor to student, student to student, and student to instructor.

✅ Might work because

  • Efficient, but remember that your communication and that of your students will be limited by who attends in-person.
  • You can use the classroom environment to support your goals for the session: whiteboards, projectors, screens, and other equipment in a physical classroom.
  • Hand gestures and body language can help you get your point across.

❌ Might not work because

  • One group of students will get the information first.
  • We have limited interaction time with students, and may not be able to communicate everything we desire to in the time we have.
  • Potential classroom distractions may limit the intake of the communication for some individuals.

✅ Might work because

  • Personable and efficient.
  • Effective for one-to-one communication.

❌ Might not work because

  • Time intensive if you have to do this with every student.
  • Students don't necessarily talk on the phone—they may feel more comfortable communicating through email.
  • Ephemeral (unless you record it!)

✅ Might work because

  • A "distribution list" will allow you to send a message to your entire class at once.
  • Familiar to you and to students.

❌ Might not work because

  • One-on-one communication can get "noisy" and relies on the class list in SIS or Canvas (not Outlook).
  • Media limited.

 

✅ Might work because

  • Engage the whole class or specific groups of students.
  • Keep related things together.
  • Familiar in principle to students.
  • Less formal.

❌ Might not work because

  • Requires regular/frequent interaction for best results.
  • Small learning curve in Canvas initially.
  • Task needs clarification.
  • Less formal.

✅ Might work because

  • Intuitive and in Canvas.
  • Alert the whole class or sections of students all at once.
  • Allows for rich media (video messages, images, etc.).
  • Students get notified.
  • Allows for student comments (optional).

❌ Might not work because

  • Students can disable email notifications—but still see announcements when in Canvas.
  • Can get noisy with frequent use.

 

✅ Might work because

  • Feels more like being in the classroom.
  • Sessions can be recorded for review (or for those who miss).
  • Varying levels of interactive options (whiteboard, breakout groups, chat, polls, etc.).

❌ Might not work because

  • Steeper learning curve the first time.
  • Relies on a good connection and technology.
  • Logistically, some students cannot make it to synchronous sessions.

✅ Might work because

  • Allows instructors to create channels for specific people, or a whole class
  • Can @ people to notify them; and use emojis to respond to chats
  • Could be useful for communicating expectations for group work.

❌ Might not work because

  • Students may be more familiar with it as a synchronous meeting tool rather than as a communication tool
  • Easy to get lost in threads if users don't tag each other for communicating
  • Steep learning curve to utilize full functionality

✅ Might work because

  • Intuitive and familiar to students.
  • Easy to use.
  • Synchronous.
  • A "history" of the chat is available to the entire class making it good for Q&A-type sessions.

❌ Might not work because

  • Synchronous.
  • Media limited.
  • Whole-class only. Cannot be limited to specific students.

✅ Might work because

  • Displays course due dates automatically.
  • Can add other items (like reminders).

❌ Might not work because

  • Requires "due dates."
  • Only the names of events appear directly on the calendar.

✅ Might work because

  • Create blocks of time for students to sign up to meet one-on-one (e.g. office hours).
  • Can use a "feed" to add these blocks to Outlook.

❌ Might not work because

  • Required additional communication so students know how and to use them.

Learning Outcomes that Lead to Student Success 

What are learning outcomes and why do you need them?

There’s a famous misquote from Lewis Carroll, “If you don’t know where you’re going, any road will get you there.” The same is true in our courses: if you don’t know what you want your students to learn, it doesn’t really matter how or what you teach them. Every instructor wants to ensure student success, but if we as instructors don’t have accurate and well-thought-out learning outcomes, what does success mean in our classes? Creating learning outcomes should be a collaborative process where instructors responsible for teaching a course come together to craft these statements based on the most important learning in a course, taking care to maintain a balance between critical thinking and base knowledge while keeping an eye toward what makes a learning outcome an achievable learning goal.

Learning outcome creation

Before you create course learning outcomes

  • If your course is part of a program, you should ensure that the learning outcomes mesh with the rest of the program to meet all program learning outcomes.
  • Plan collaboratively with colleagues teaching the same course. All learning outcomes for sections taught of the same course should have the same learning outcomes according to the HLC (Higher Learning Commission) criteria 3a.
  • With colleagues, determine and list the most important learning or skills that will take place in this course.
  • Whittle down the list if it is too large. Consider what you and your colleagues can reasonably accomplish during the semester.
  • Pay attention to the conversation around Generative AI. What your students need to know and do may change because of the rapid development of AI.

Considerations as you create your learning outcomes

  1. Keep assessment and, therefore, your verb choices in the forefront of your mind. As you write learning outcomes, you want to ensure that the learning outcomes contain actions that can be demonstrated. When you ask students to “understand” something, this is difficult to demonstrate. If they “explain” it instead, that is an action that can be done and measured in various ways.
  2. Keep Bloom’s Taxonomy next to you as you create. It makes sense to use a taxonomy when writing outcomes. In Bloom’s model, skills and verbs on the bottom of the pyramid are less complex or intellectually demanding than those at the top of the pyramid; keep in mind they may still be totally appropriate, especially for lower-level courses. More critical thinking skills are required for those skills at the top of the pyramid, but it is useful and acceptable to use verbs and abilities from all levels of the pyramid. If you are teaching an upper-level course, you don’t want to draw all your verbs and skills from Bloom’s Taxonomy’s knowledge level. You should be using some higher levels in Bloom’s system.  The chart below can be a guide as you create those learning outcomes and note that generative AI developments may make the original chart problematic in different ways. There are alternatives to Blooms, as well.

    Alternatives to Blooms Taxonomy levels and verbs.
    Newtonsneurosci, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0>, v Wikimedia Commons
  3. Use SMART Goals also. In addition to including Bloom’s Taxonomy as part of your learning outcomes, we encourage you to make sure that your learning outcomes are created using the SMART goals model.   SMART goals were developed in 1981 by George Duran, who noticed that most business goals were not created in a way that could be implemented effectively.

SMART is an acronym we can use to describe the attributes of effective learning outcomes for your students. Please note that you will find different versions of the acronyms in the SMART goal model, but these are the ones CATL uses to discuss learning outcomes:

    • Specific – target a specific area, skill, or knowledge
    • Measurable – progress is quantifiable
    • Attainable – able to be achieved or realistic
    • Relevant – applicable to the students in the class
    • Time-based – achieved in a specific timeframe, such as a semester

Example: By the end of the semester (T), students will be able to diagram (M) the process of photosynthesis (S, A) in this biology class (R).

Learning outcomes are more likely to be meaningful if they can meet all of the qualifiers in the SMART acronym. Think specifics as you create your learning outcome. If you can’t tell if your learning outcome meets one of the qualifiers, you should rework it until it does.

Review your learning outcomes

Your next step as a team should be to review your learning outcomes. Compare them to the SMART model and Bloom’s Taxonomy or any other relevant model you might be using. If it helps, consider these examples. First, “Students will improve their understanding of passive voice.” On the surface, it might look like a reasonable goal, but then as you ask, “What does it mean to improve? Where did the student start from? When does this need to be done by?” This goal offers no answers to those questions.

How about this one? “By the end of the semester, all students will receive a 100% score on their math notation quiz.” For context, this is a Writing Foundations course. That begs the question, is this outcome relevant to this group of students? Is 100% a reasonable and attainable goal?

Consider these questions as a guide when creating SMART goals. A more reasonable goal for this group of writing students is that by the end of the semester, students will be able to identify and accurately and effectively use scholarly research in their writing projects 80% of the time. One part of the review process is ensuring your outcomes are SMART, but there are additional elements to consider, including the questions below.

  • Can you identify the verb in your learning outcome?
  • If your students master the skills in your learning outcomes, will they be satisfactorily prepared to go to another course that teaches the next level of this material?
  • If this is a course in a series, have you checked to be sure that your outcomes make sense with the previous and next courses?
  • Has your unit done curriculum mapping for its goals, and do your course outcomes align with that mapping?

Put it all together

Creating learning outcomes that reflect the learning necessary to achieve mastery in a course can be an arduous process. It should be a collaborative process as well. We encourage you to reach out to the CATL team if you would like guidance or help walking through Bloom’s Taxonomy and the SMART goal model. We are always available to help!

Resources on creating learning outcomes

Using the Lightboard (eGlass) to Create Engaging Videos

photo of the lightboard studio 505B doorway.

What is the Lightboard Recording Studio?

Kaltura Video Tutorial: eGlass (Lightboard) Basics

UWGB instructors and students can reserve and use the Lightboard (eGlass) studio located on the 5th floor of the Cofrin Library (CL 505 B). The lightboard functions like a transparent whiteboard. You write on one side of it, and a camera records you from the other side.

Potential Use Cases

The lightboard can be a valuable tool for presenting complex materials, such as mathematical formulas or diagrams. By allowing presenters to write or draw while explaining content, it provides helpful visuals that enhance understanding, making it ideal for engaging students and simplifying complex topics.

It can also be used to facilitate ‘flipped learning.’ In this case, students receive scaffolded instruction outside of the classroom and class time is then reserved for discussion or activities in which students apply concepts to further engage with the subject matter.

Tips for Before You Record

Before you record your video using the lightboard, consider the following planning tips:

  • Keep it short. Lightboard videos should be a single topic that can fit easily on a single board. If your video requires constant erasing, it is likely too long.
  • Organize your content. Develop a structured outline or script and rehearse your video beforehand to ensure preparedness and to streamline the recording process.
  • Practice writing before you record. Spacing can be an issue on the lightboard so it is a good idea to practice laying out any complex drawings or text that you want to use in your video ahead of time. You could practice on a whiteboard or on the lightboard itself before recording.
  • Clothing choice. Dark, solid colors (grey, navy, deep reds, etc.) are best. The markers you use for the board are neon colors and tend to blend in with light shades, becoming hard to read. Avoid wearing black so you don’t blend in with the background and don’t wear clothing with large logos or lettering (the writing/logo of your shirt will be flipped and might be a potential distraction in the video).

Tips for Recording Your Video

During the recording process, keep the following tips in mind to enhance the quality and effectiveness of your video.

  • Do a quick mic-check. Consider recording a quick 10-30 second video to ensure that the microphone, camera, lightboard brightness and settings are functioning properly.
  • Stay close to the eGlass lightboard. Stepping away from the board will reduce the amount of light that hits your face and may also affect the camera focus, making you appear blurry.
  • Try to leave room for yourself as you write on the glass. Be mindful of space as you draw and write on the board. Move to the side as you write and try to not cover your face with text.
  • Point and emphasize content. When you are speaking about something specific on the board, point to it, circle it, or underline it to draw attention to that specific item.
  • Look at the camera when recording. When you are not drawing or writing, address the camera as it represents your audience.
  • Have fun with it and enjoy the process! Having fun while making these videos will make for more engaging content.

Reserving the Room

Reserve and check out the room through the UWGB library reservation system.

  • Note: Please contact the UWGB IT Service Desk if you encounter technical difficulties with the studio computer or lightboard hardware.

Related Resources & Alternative Recording Methods

My Resistance (and Maybe Yours): Help Me Explore Generative AI

Article by Tara DaPra, CATL Instructional Development Consultant & Associate Teaching Professor of English & Writing Foundations

I went to the OPID conference in April to learn from colleagues across the Universities of Wisconsin who know much more than I do about Generative AI. I was looking for answers, for insight, and maybe for a sense that it’s all going to be okay.

I picked up a few small ideas. One group of presenters disclosed that AI had revised their PowerPoint slides for concision, something that, let’s be honest, most presentations could benefit from. Bryan Kopp, an English professor at UW-La Crosse, opened his presentation “AI & Social Inequity” by plainly stating that discussions of AI are discussions of power. He went on to describe his senior seminar that explored these social dynamics and offered the reassurance that we can figure this thing out with our students.

I also heard a lot of noise: AI is changing everything! Students are already using it! Other students are scared, so you have to give them permission. But don’t make them use it, which means after learning how to teach it, and teaching them how to use it, you must also create an alternate assessment. And you have to use it, too! But you can’t use it to grade or write LORs or in any way compromise FERPA. Most of all, don’t wait! You’re already sooo behind!

In sum: AI is everywhere. It’s in your car, inside the house, in your pocket. And (I think?) it’s coming for your refrigerator and your grocery shopping.

I left the conference with a familiar ache behind my right shoulder blade. This is the place where stress lives in my body, the place of “you really must” and “have to.” And my body is resisting.

I am not an early adopter. I let the first gen of any new tech tool come and go, waiting for the bugs to be worked out, to see if it will survive the Hype Cycle. This year, my syllabus policy on AI essentially read, “I don’t know how to use this thing, so please just don’t.” Though, in my defense, the fact that I even had a policy on Generative AI might actually make me an early adopter, since a recent national survey of provosts found only 20% were at the helm of institutions with formal, published policy on the use of AI.

So I still don’t have very many answers, but I am remembering to breathe through my resistance, which has helped me develop a few questions: How can I break down this big scary thing into smaller pieces? How might I approach these tools with a sense of play? How can I experiment in the classroom with students? How can I help them understand the limitations of AI and the essential nature of their human brains, their human voices?

To those ends, I’d like to hear from you. Send me your anxieties, your moral outrage, your wildest hopes and dreams. What have you been puzzling over this year? Have you found small ways to use Generative AI in your teaching or writing? Have your ethical questions shifted or deepened? And should I worry that maybe, in about two hundred years, AI is going to destroy us all?

This summer and next year, CATL will publish additional materials and blog posts exploring Generative AI. CATL has already covered some of the “whats,” and will continue to do so, as AI changes rapidly. But, just as we understand that to motivate students, we must also talk about “the why,” we must make space for these questions ourselves. In the meantime, as I explore these questions, I’m leaning into human companionship, as members of my unit (Applied Writing & English) will read Co-Intelligence: Living and Working with AI by Ethan Mollick. We’re off contract this summer, so it’s not required, but, you know, we have to figure this out. So if we must, let’s at least do it over dinner.