Josh Brake shares metaphors and other ethical considerations regarding AI on Episode 607 of the Teaching in Higher Ed podcast.

“When you’re moving fast, it’s really easy to do things unreflectively and to make a poor decision without even realizing it.”

“The special thing about bicycles, at least in their non-electronic versions, is that they’re totally human-powered. So it’s all based on the energy that you put in, and it’s just transforming that energy, to make you more efficient and be able to move faster.”

“When you have something like an E bike, that augmentation can be used in a variety of different ways, so it can be used to actually extend your capacity.”

“It’s really this question about what’s the intention that you’re bringing to the technology when you come to the tool, what are the questions that you’re asking? And fundamentally, it’s a question of purpose and intention. Why are you using this?”

Karen Costa shares about An Educator’s Guide to ADHD on Episode 606 of the Teaching in Higher Ed podcast.

Curiosity is just this sort of force of nature. So tap in to your students creativity, your students passions and interests as a way to support them in reaching and achieving those challenges that you also hold for them.

That’s a heavy thing for folks with ADHD to carry, that we are a burden on the other students in the classroom, that we are a burden on our teachers. And that is simply not true.

What we know now is that many times those are what are called stims in neurodivergent and ADHD and autistic communities. And those are actually a way that a lot of folks help themselves to stay present and regulated in their bodies so that they can direct their attention to the teacher or to the task at hand.

The best thing we can do to make the course real is as an instructor to be present in that online course.

José Bowen shares about the second edition of Teaching with AI on episode 605 of the Teaching in Higher Ed podcast.

I do think that we are going to have to figure out how to focus on student learning in an era where students have this new technology that will short-circuit the learning we want.

My advice to people is that I know we’re overwhelmed, so don’t ask AI to do something you love. Ask AI to do something that you hate.

The real problem with AI privacy is that now we have a tool that can mine all that, right?  I’m more worried about AI as a tool for analysis and observation, and how that’s going to change the world in which we live.

I think the potential is, you’re probably going to get more bias because people are going to use AI poorly. And so bias and privacy are two categories of ugly that are pretty big.

Bryan Alexander shares about Peak Higher Ed on episode 604 of the Teaching in Higher Ed podcast

“It’s another form of thinking, it’s another form of organizing information and that we have to treat it seriously as such. The computer scientist actually recommends that we think about generative AI as children. These are AIs that have some degree of autonomy and they’re also not very wise in the world yet, and we have to train and rear them up.”

“So if AI is bubble, if it turns out to be a bubble and it pops, this might be bad news for the entire economy.”

“The problem of how do we actually figure out what people are doing with AI within post secondary education? That’s a really great challenge because if you polled people, they have all kinds of great incentives to not respond accurately.”

Matthew Mahavongtrakul shares about active learning that engages all learners on episode 603 of the Teaching in Higher Ed podcast.

You don’t need to change your entire course tomorrow. What is one simple thing that you can do that will push you on the path?

“The number one kind of piece of pushback that I get from faculty is I just simply cannot cover everything.”

“I think at the crux of it, it is the shift in mentality between us as being, as we say, the sage on the stage to being a facilitator in the classroom.”

C. Edward Watson shares about navigating AI’s rapid transformation in higher ed on episode 602 of the Teaching in Higher Ed podcast.

I never include AI in the beginning of my processes.

There’s a lot of incremental shifts, but the increments are quite large.

I would argue that maybe this is the first time in the history of higher education that we have learning outcomes that are at war with one another.

We’ve never built a curriculum for something that’s changing so quickly. We’re being asked to keep up with this rate of change in a meaningful way that actually serves our students well.

Christopher Ostro discusses the AI grief cycle on episode 601 of the Teaching in Higher Ed podcast.

The fact is there are things we’re grieving. Our job has profoundly changed in huge ways in a very short period of time.

Our traditional assessments suddenly are not working effectively like we used to think that they did.

I want my students to view me as a resource and as someone that they can trust.

When something makes me uncomfortable, I want to lean in and understand it better.

Dave Stachowiak joins Bonni to explore 6 pedagogical practices from 600 episodes on episode 600 of the Teaching in Higher Ed podcast.

When we stop aiming for perfection, we allow ourselves to then be fully present for others.

Practice 1: Start and end small.

David Gooblar shares how better teaching can make college more equitable on episode 599 of the Teaching in Higher Ed podcast.

Most of our scars are hidden. I think most of the time people don’t see the scars that we carry.

We get such a small window into our students lives.

The imaginary idea of the college student in America is of a privileged student. And that’s just not the case when we talk about American college students today.

We need to work to earn their trust, to convince our students that we’re working for them, that our job is to help them develop, learn, and grow.

Jeff Young shares clips from his Learning Curve Podcast regarding AI in higher education on episode 598 of the Teaching in Higher Ed podcast.

It is crazy to think of how much we’ve all learned about generative AI just in the last couple years.

I’ve been really interested in how students are thinking through AI and where their perspectives are. There is not one student view. You can find students that think all kinds of things.

Students are very aware of AI and they’re also very aware of how it’s changing the job market that they might enter.

One danger of these tools is that they give you such instant gratification. There’s a hit of dopamine.

Students are using AI tools, not just for academics. They’re experimenting with AI.