[00:00:00] Bonni Stachowiak: On today’s episode of Teaching in Higher Ed number 461, How to Not Fight Artificial Intelligence and Lose with Dara Ryder.

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Welcome to this episode of Teaching in Higher Ed. I’m Bonni Stachowiak, and this is the space where we explore the art and science of being more effective at facilitating learning. We also share ways to improve our productivity approaches so we can have more peace in our lives and be even more present for our students.

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Today’s guest, Dara Ryder, is chief executive officer of AHEAD, an Irish NGO established in 1988, which is dedicated to creating inclusive environments for people with disabilities in education and employment. Dara became CEO in 2020, having previously managed AHEAD’s digital presence and developed a suite of online CPD programs related to universal design for learning and inclusive practice in his role as digital media and e-learning manager there. His research interests include monitoring the participation of students with disabilities in higher education, exploring the learning experiences and desires of students with disabilities, and examining the implementation of UDL in policy and practice.

After graduating from Queens University in 2005, Dara joined Dun (LEERY) College of Further Education as a lecturer, where he became interested in inclusive education when working firsthand with students with disabilities in his classroom. When the opportunity arose in 2008, he joined AHEAD, where he’s been working ever since on creating inclusive environments in education and employment for people with disabilities. Dara Ryder, welcome to Teaching in Higher Ed.

[00:02:14] Dara Ryder: God, Thanks, Bonni. It’s lovely to be with you today.

[00:02:16] Bonni: I’ve been looking forward to this conversation ever since you agreed to come on the show. Would you start by giving us a layperson’s definition of artificial intelligence?

[00:02:26] Dara: Yes, sure. I suppose it’s important to say, look, I’m not an AI expert, just a very, very interested observer. I come actually from the background of the inclusion of people with disabilities in higher education. Really just understanding how we need to reshape our approach to higher education in response to the increased human diversity that we see in our classrooms. What I’m finding is there’s actually a lot of overlap in the conversations around AI and the conversations around inclusion, and that’s why I’ve been pulled into it, but I’m really, I suppose, every day finding myself coming down a new AI rabbit hole. It’s lovely to externalize some of these tasks with you today.

In terms of AI, a layperson’s definition, I suppose, really it’s about the development of systems that can perform tasks that we would typically associate with requiring human intelligence. That’s AI in its simplest form. When we think about those tasks, what are we talking about? Things like understanding natural language, understanding visual perception, looking at speech recognition, how we understand the sounds that we make as human beings from our voice.

Also, things like physical skills that require dexterity, so if we think about things like robotics and how AI is used within that. Another process is decision-making. It’s really about all the cognitive and physical skills that relate to those tasks that we might typically link with human intelligence. Ultimately, the goal of AI, I suppose, is to create machines or software that can learn and reason and adapt like humans do, and perform those tasks that maybe previously might have been taught of as requiring a human level of intelligence. It’s a catch-all term for the algorithms and the statistical models that power those machines, really.

[00:04:05] Bonni: I’m feeling so much of that catch-all lately as we’re having conversations. Just last week, we did a panel with some of our students, and I started to feel like in those moments, that everything feels like artificial intelligence at some point. That was a fascinating conversation. I was so grateful to the students to come and be vulnerable to share about ways that they’re seeing it being used and using it themselves. Talk to us a little bit about some of the main categories involved in artificial intelligence.

[00:04:35] Dara: Look, there’s a lot of different ways of categorizing AI, different subsets of categories and different fields that move across these categories within AI, so you probably won’t get a straight answer. I know you’ve been doing a lot of podcasts on this, Bonni, so I’m sure you’re getting different types of answers on this, but I suppose if I’m trying to boil it down very simply, most of the forms of AI fall into two main big categories, as I see it, as I said, as an AI enthusiast. The ones that really stand out for me in terms of explaining AI in simplest terms is machine learning, and the second one is called natural language processing.

What’s machine learning? Well, basically, it involves training algorithms to recognize various patterns and make decisions based on data that sits in front of it. I suppose the process of machine learning involves feeding data to the task that you’re trying to train the machine on into a machine to allowing it to learn from lots and lots of samples of that type of data, that type of process.

Essentially, once a sufficient number of examples have been gone through, the machine then has the capability and can begin to process new and unseen examples and return accurate results. It’s able to adapt and learn from what’s happened before and what’s been fed into it before, and it’s able then to encounter new situations, new encounters, and produce the accurate results similar to what a human would do. I suppose if we think about that from a teaching and learning perspective, we might think about this as the machine engaging in active learning. It’s learning by doing, and now it’s able to respond to new situations based on that previous activity.

The second form is natural language processing, and we might think about ChatGPT, which is causing a big stir right now across academia. That would largely fall into the category of a natural language processing AI. I suppose in simple terms, natural language processing makes it possible for humans to talk to machines. In ChatGPT, for example, how that works, it’s … on a massive amount of text-based data to learn patterns and relationships in language.

It uses that knowledge then to generate natural language responses in return. Essentially, it does that by predicting the next word or sequence of words in a given text. By doing that repeatedly over and over and over, the model learns to generate natural language that seems to us to be coherent and contextually relevant to whatever text input that we’ve given it as a human interacting with it.

I suppose, when you ask ChatGPT a question, what it’s essentially doing is predicting a coherent response based on everything that’s been fed into it before. It’s putting one word in front of the other, almost like learning to walk until it eventually learns to run. It seems really super intelligent, but essentially, it’s just a very smart prediction engine. It’s probably a little bit more similar to maybe the rote learning approach, where somebody is learning what sounds right from the previous instances and repeating that back one word at a time.

[00:07:33] Bonni: Oh, I love how you’ve brought in those comparisons to how some of us approach teaching. That’s really helpful for me to wrap my heads around these broad definitions. What’s even also helpful for me to understand a little bit better about artificial intelligence is to hear about it in our daily lives. Would you share a little bit about where people, in general, might start to see artificial intelligence? Then I’d love to hear specifically in your life where you’re seeing it show up.

[00:08:01] Dara: Sure. I suppose, it’s really important to say that there’s a lot of talk about AI now, but it’s not at all new. AI has been around for decades to varying levels of success. Way back in the mid-1990s, IBM’s Deep Blue computer, which is an AI machine, defeated the world chess champion, Garry Kasparov, for the first time. That shows you how advanced already it was at that stage of the game.

In terms of our daily lives, look, people are interacting with AI every day, have been for a very long time. If you’re a user of Netflix, you might think about how you’re being recommended different types of shows. Equally, when you go on Amazon, you might be recommended different types of products based on your usage of the internet or … what your device is listening to you and what you’re saying in conversations. All of that information is being taken into an AI engine and it’s being used to hopefully recommend useful products, useful shows.

Things like your satnav is powered by AI, things like your voice assistant, so Alexa or Siri is using that kind of speech recognition to, first of all, understand what you’re saying and it’s then using natural language processing to understand what you want from that and spit back at you something that’s meaningful. All of these things in your daily lives. If you ever played a computer game, that’s, generally speaking, going to involve some form of AI in the background.

Even then, when we think about the big stir that’s been caused in academia at the moment about writing, we’ve been using AI to assist us in writing for a long, long time. All our spelling and grammar checkers … form of AI sitting in the background to varying degrees of complexity.

More increasingly, as we move through 365 and Microsoft getting more and more advanced, we see things like Microsoft Editor, for example, which is getting more complicated in terms of the types of suggestions it’s making for us in terms of how we phrase particular sentences, the conciseness of our language. It’s even giving us scores from our spelling and grammar and how we write and how clearly we write. We’ve been using these things for a very, very long time, so that’s quite important to say.

In terms of how I’ve been using it, I suppose the most recent wave of AI that’s been taking us over, so things like ChatGPT, we also have image creation tools like DALL-E, which is another open AI tool. ChatGPT is also an open AI tool.

My own usage, I’m using it now. I’m finding it really useful. I’m actually using it pretty much on a daily basis now in some form or another. I’m using it for meeting preparation. I’m a very busy person generally, so I often have long preparation … for meetings. If I see a topic on the agenda but I’m not sure about, maybe it’s a new policy directive or something like that, I’m asking ChatGPT to summarize that policy document for me, and it’s giving me a nice meaningful summary. It’s not making me an expert on this policy, but it’s giving me enough to have a meaningful input at the meeting where otherwise I might not have had that opportunity.

I’m using it in my writing now to help me to reframe. For example, if I’m writing a paragraph, we all have that feeling where sometimes we’re just stuck and it feels like a word soup in front of you. I’m asking ChatGPT to help me out to simplify it for me. Then I’m not just taking that and pasting it in, but I’m using that as a reframing and a starting point in my writing as well.

Then increasingly, I’m using the image creation tools within my PowerPoint presentation. I’ll give you an example. Recently, I was doing a session on Universal Design for Learning and I was trying to get this analogy of not really being able to get to the pedagogical parts of Universal Design for Learning without addressing the baseline foundational or digital accessibility. In other words, making your Word documents or PowerPoint document accessible.

I wanted to give the analogy of it’s like having a really fancy living room furniture put out in the snow. You haven’t got the foundations, you haven’t built the walls, you’ve just got the decoration. I couldn’t find an image in my stock imagery, so I asked Dall-E to create one for me. I created this beautiful imagery of a living room sitting out in a very snowy, serene field. That is an example of really cool ways that you can use AI to help you with your efficiency and your productivity. I see this is only the beginning for me with these types of tools. I can just say that we’re going to explore all sorts of new and interesting ways to use them.

[00:12:23] Bonni: Oh, you’re making me so much want to go try that out. I got really interested in and I actually recommended an Instagram account where the entire account is made up in someone’s imagination of toys that don’t exist. They look really creepy. I can’t remember the name of it, but it’ll be in a show that’s either coming or already happened. I was showing it to my son last night, he was really interested.

I think for them, this is just– The fact that you could have something in your imagination and then have it appear before you is not as maybe miraculous as it feels to me right now because I just think that that’s incredible. I love that you had that image in your mind and then were able to have that come through in your PowerPoint slides. I’m fascinated always by all that I’ve read and learned about the importance of having our visuals match with what we’re trying to say and think of all the freedom that is before us right now to be able to live up to this …

[00:13:23] Dara: Totally. How long have we all spent trialing these stock image sites are trialing it for our royalty-free images, even probably more relevant for folks in the academics fair, where we’re just trying to find an image that lands? Now we have that really creative potential to use these tools. For me, I just find it immensely exciting as a phase that we’re in with AI, that who knows, both ourselves as academics and our students as well, what ways they might use AI within their own working? The potential seems to be almost limitless.

[00:13:57] Bonni: You’ve talked a little bit about how you’re seeing it show up as useful in your daily life. Would you talk about some of the reasons that students might turn to artificial intelligence?

[00:14:07] Dara: Yes. We’ve alluded to some of them already that, first of all, the creative potential there is amazing. I see a kind of AI as having potential in lots of different ways, some of which are maybe negative and something to be concerned about or something to at least think through what the implications are, and some of which are immensely positive.

If I touch on the positives because, to be honest, I think there’s enough people engaging in what I would consider almost a moral panic about what’s happening in higher education with regards to ChatGPT and academic integrity, I’m going to maybe lean more towards the positives there because I think there’s enough voices talking about that debate. I see it as a great leveler. I see it as almost like the ability to have a level of a personal assistant there, someone you can check in when you don’t understand the concept, and you can ask a very meaningful, specific query about the content that you’re engaging and that you just don’t get, and you can get an additional layer of advice on that.

Yes, it’s not always going to be perfect. Yes, we have to be careful about how students use it because, as we know, the responses can contain information that isn’t correct, but I think that’s, I suppose, part of the onus on educators, is to actually engage with students on this to teach them how to use it really effectively, because one of the things, for example with ChatGPT that we’ve learned is how you actually construct the prompts is really, really heavily linked with the quality of response that you get.

I think there’s actually an onus on us to help our students to understand that, to get the most from it. I suppose, students can use it in a whole variety of ways, things, like as I mentioned, just checking in on particular types of content, it could be summarizing big, big chunks of content into smaller chunks. I mentioned that I’m a very busy person and I come to meetings and maybe I haven’t had the preparation time that I’d like.

We all know that students are incredibly busy at the moment. They have increasingly compact lives. They’re often traveling huge distances because of issues with housing. Certainly, here in Ireland, were in the midst of a housing crisis. Obviously, the diversity of our colleges is massively exploding. We have a lot of socioeconomic diversity within our colleges, which means that people often have to work long hours outside of their college life.

Equally, we have a whole range of diversity in terms of access and disability, which means that maybe people may need more time to internalize data. All of those things mean we need to be realistic about where we are as educators and I suppose plan our pedagogy to the real world. I think AI can really help our students maybe to chunk some of that information down and act as a real guide through that information.

I suppose in terms of the more nastier side of things, where we see a lot of the talk and … focused is around how students might use it to produce essays and to cheat in that regard. I suppose the reason students might do that, for me, this is actually an essential part of this conversation, is about the environment that we put our students in and the purpose of our educational institutions and our programs. I think for me, the primacy of grades within our system is something that really, really has to change.

We have moved, generally speaking, to more standards-based accreditation, especially when we think about things like engagement with our professional bodies or professional programs to generally standards-based, and yet we haven’t moved away from grades. For me, grades actually don’t have a place in a standards-based accreditation system at all. The research is very clear that they have real no assistance to learning. Grades do not actually aid learning in any real capacity. I think bringing in these unnecessarily competitive systems is actually harm to our students and harm to the process of learning. Really, they end up driving desperate students to do often desperate things.

I think over-assessment is a major major problem that we have. Often there’s not a lot of time and energy spent in a cross-programmatic approach to assessing our learning outcomes, or often assessing learning outcomes multiple times, very, very unnecessarily, to the point where students often end up maybe having three, four, or five assessments to do in a very short window. Sometimes those assessments are engaging in multiple learning outcome or the same learning outcome multiple times.

I think a lack of authentic assessment is another really big issue in terms of do students actually see the value in the assessment itself for the purpose of learning? We know we have assessment for us learning as well. I think actually all assessments should be for learning, even if they are assessment of learning. Do actually students see the value in the assessment, as something that’s meaningful for them to engage and that will be useful for them in their professional lives or aspects of their life?

I think a big one from my perspective, coming from the disability and inclusion perspective, is the whole aspect of the integrity of their traditional modes of assessments in the first place. Often the academic integrity debate is very heavily weighted towards the student’s responsibility to ensure fairness within the process, but actually, I believe that some of the traditional modes have been very, very heavily disadvantaging for students with disabilities… in AHEAD suggest that.

I’ll give you an example that always sticks in my mind, of a student I interviewed as part of the research project during COVID, who told me that prior to COVID, they were failing their exams, scraping passes and others. As soon as they moved into COVID, into the alternative assessment modes, they actually moved from failing and scraping passes to the top 5 to 10 in their class. Just the change of instrument had an enormous effect.

Really, the reasonable accommodations that this student would have been getting for extra 10 minutes an hour in exam was a … class. It wasn’t a meaningful intervention for them.

Really, I think what that tells me actually is that the integrity of the debate needs to be widened out and it needs to be looked at in a much more holistic way, because I would see that almost as a form of institutional cheating, if I want to use very provocative language, but that we’re not addressing these issues, that we’re mostly doing the examination because it’s practical, because it’s something we’ve always done, because it’s something from an economic perspective that we can achieve in a practical way.

I think those are some of the reasons why I think students turn to maybe the more negative aspects of AI because they need a way out, they’re desperate. We really need to think about that in a very holistic sense and think how can we create an environment, first of all, where students are motivated to learn for the purpose of learning itself, where they feel entrusted enough, I suppose, that they can share what’s going on in their lives and that they’ll get the flex that they need to engage meaningfully to demonstrate their learning.

[00:20:55] Bonni: Wouldn’t that be a wonderful place to both begin and end? [laughs] That could be presumed. This is such a challenge and an opportunity because we can do this as individuals and yet our individual work is limited by the number of people that can do this in solidarity.

We’d love to have you share a little bit about an alternative to our response to artificial intelligence, being to fear it, lock it down, try to prevent people from using it, when is the new Turnitin or whatever, the plagiarism. When are they going to come out with their latest iteration that will rid us all from this thing that we fear or makes us angry or roots around at our sense of identity and what it means to be an educator? Talk a little bit about a culture of trust.

[00:21:49] Dara: That’s a million-dollar question. I suppose, one thing is that culture does take time to build. It’s not something you can switch on overnight. I think it’s important to almost talk a little bit, first, about the response that you are talking about, Bonni, about this move to lock things down. First of all, it’s just a fool’s errand, isn’t it? I think, if we’re honest about it, this is not something that is going to be a successful strategy. [laughs] It’s just not possible.

While you might increase the numbers of people who are caught under these surveillance systems, really all you’re doing is enriching a bunch of grifter companies, in my view, that will have very largely mixed results. Really, people who are smart and want to do this will do it anyway. Most students, for example, aren’t taking ChatGPT, asking it to write an essay and turning the essay in without doing anything with it. We know already that the tools that are available so far are very poor at detecting any kind of alterations to initially AI-produced text. That’s the first thing. It’s fool’s errand.

I almost bring it … to back when the record industry tried to respond to Napster originally. Rather than trying to create a holistic solution that brought streaming to the internet in a productive way for them as industries, they instead went to try and lock it down, bring Napster to court, draw that out. Really, over time, that resulted in the music industry dramatically losing revenue at a record pace.

I think that’s been, overall, very harmful for the industry, in that it’s taken a long time for it to respond. The responses that they have in place now are definitely not necessarily the most productive ways both for the industry and for artists as well. I think that’s a good analogy, is that it’s this fool’s errand to actually try and fight this in a major way. I’m not trying to say that it’s easy for educators, it’s very, very difficult, and educators are largely very, very overworked themselves. I have real empathy for the conversations that are going on.

What I would say is, first of all, to have conversations with your students about this technology, “This is what it is, this is what it’s doing.” Even from the point of view, what it– ChatGPT, for example, is largely a predictive model. It’s largely going to give you mixed results in terms of the efficacy of what’s coming out of it, flagging with them that it’s often going to make up references, with prompts, of course. You can improve you can approve that dramatically in terms of the quality of that.

Still, having those initial conversations, really pointing out what this is all about, that they’re actually losing by using ChatGPT in those kinds of ways, but actually that there is really constructive ways to use it, and allowing them to use it, but also to maybe reflect as part of their assessment process on their engagement with ChatGPT, how did they use it? What did they find critically as the things that ChatGPT was good at or bad at? Including that as part of the thing and being open about that. I always find that, being open in those relationships with your students, allowing them to show their vulnerabilities and showing your own is a really good way to create a culture of trust.

Also, bringing in maybe more examples of peer engagement, where, for example, if you’re doing a peer review of work before submission, where maybe there’s a point that they talk to each other about how these tools were used as part of the creation and they also get feedback in each other’s work so that you’re creating a culture of dialogue within the classroom, more generally, all these things can help, I think, to create a culture of trust.

Then from an academic integrity point of view, I think just having conversations about that is really important, because often students don’t understand the term whatsoever, what it means, why it’s important. Understanding that being in academia is partly about creating truthful process, truthful dialogue, truthful output, and why that contributes to our society in the whole, and how they can be part of that conversation by engaging in the process meaningfully and authentically. I think that’s really the way to go.

[00:25:54] Bonni: I wanted to try a premise out on you. I just want to play with it for a bit. We might presume that you’re here to learn as a student, and if you’re not here to learn, that’s not your fault, or perhaps I have to soften it a bit and say, that’s not entirely your fault. [laughs] What would education look like if we were to start with that premise? Is that a good premise to start with, that people are there to learn, or do we need to replace it with something else?

[00:26:21] Dara: First of all, I think we need to be realistic about students’ motivations and the culture that we’re placing them in. We can’t pretend they’re here to learn fully, that that’s their sole purpose in an environment where they’ve been culturally taught that grading is important, that competition is important, that we live in a market economy that’s going to value that in some way. A lot of people will come into university settings because they want jobs that will give them meaningful, authentic, rich lives. I think it’s important to have those conversations at the beginning. How can learning assist them in their goals really is what it’s about.

It’s about linking the goals of the course and the goals of you as an educator to how that can help them in their real lives, and help them to understand that if they’re using these tools to take shortcuts, that that may seem like a good approach in the short run, but really, in their longer-term goals of being the best that they can be in their job, and if that is what their goal is, that really it’s not going to help them, that they’re only starring up problems for themselves later in life.

They may get a B grade instead of a C grade this time around, but actually, they’re starring up problems for themselves later in life because they’ll be exposed very quickly in a workplace setting, where there’s potentially much closer between a boss and an employee than there would be in maybe a classroom of 400 students and an educator. The time-to-ratios there just don’t match up. I think that’s really what it’s about, it’s about helping them understand how your goals and their goals align, really.

[00:27:50] Bonni: It does circle back to what you said earlier about authentic assessment, because if we were doing that more effectively, collectively in higher education, that potential for that kind of thing to happen would be a lot less because the assessments would resemble the expectations, both in the workplace, but also, I think many of us would say, in society to be engaged in civic life in ways that are for the betterment of our society.

[00:28:16] Dara: Yes, totally. I think when we look at the graduate outcomes that we want for our students, often the universities and colleges will have specific stated outcomes that they want to… their graduates with.

Increasingly, often things like our critical thinking skills, our reflective skills, we’re increasingly moving away from the hard skills of maybe writing, or it’s increasingly more about our engagement with information and how we analyze it and interpret it. I think that’s also a way in for us to have those dialogues with our students, is to show us this is actually what employers want from you as a graduate. This is what we want to give you the opportunity to develop as a university. Part of that is actually that meaningful critical engagement with the content.

ChatGPT can help you fake that, but that’s only going to help you fake it till you get out the door. Maybe not even until you get that far. I think having those kind of conversations with students just to show them the value of the assessment for the purposes of how it can help them in their lives and how it can help them to develop as human beings.

[00:29:26] Bonni: Yes. I think if we are experimenting with it ourselves, then we’re going to be probably in a better position to speak with credibility because we’ve seen what it’s capable of doing. That’s why I don’t know what makes it an interesting thing to consider how our own engagement with these new technologies and, as you said, some that’s been around a while, but maybe we haven’t had a chance to play with as much can be helpful in this endeavor.

[00:29:49] Dara: Yes, totally. I think even engaging with that with your students, and I think it’s useful if you can have that … with your students, “How are you using it in your life?” “This is how I’m using it,” and you can show that you have some kind of understanding of what it’s all about. I think serves a dual purpose, I suppose. One is that it shows your own vulnerability in a way, or that you’re willing to explore and use these tools to support you in your own work. It shows that you have an understanding of them, so that you won’t have the wool pulled over your eyes about how students are using them.

It also gives you a point of being able to draw lines about asking your students, “Look, what do you think is reasonable for me as an educator to accept? In terms of you using these tools, what’s actually useful to you to use these tools that doesn’t prevent us from actually addressing the learning outcomes and moving forward and developing as students?” Having that kind of honest conversation with students I think is useful.

[00:30:45] Bonni: This is the time in the show where we each get to share our recommendations, and I wanted to recommend the article that was the impetus for me inviting you to today’s conversation, and that is one that you wrote called AI is here – if we fight it, we’ll lose, and so will our students. This is from the AHEAD journal. I’m going to link to that in the show notes and hope that people will take a read. A lot of our conversation is based around that article, but I felt like I just really appreciated the ways in which you expanded my imagination beyond the fear-based and the resistance base and into something more nuanced and, I believe, helpful.

I mentioned, oh, gosh, maybe a couple of months ago about our family deciding to invest in YouTube. I forget what the paid service is, but we don’t have to watch commercials anymore. It’s lovely. [laughter] It’s absolutely lovely. Man, does that algorithm really get dialed in with me because it presents me with a lot of videos from what I would best describe as tech bros, talking about all their tech bro stuff. One of the things [laughs] that I like to watch about is how artificial intelligence is showing up in our daily lives. There’s a guy who runs a channel called Daily Tekk, and that’s T-E-K-K. There’s a video I wanted to recommend called AI apps for the iPad. I just think it’s interesting.

I own an iPad, and when we own these devices, I find it fascinating just to think about ways that go beyond my current usage, of how it could help me either get some things done. It’s actually back to what you said, Dara, about the broad two types of artificial intelligence. To see that show up on such a simple device that I mostly use for consumption, it’s an intriguing idea. I will warn you that when I link to these videos, it’s a little tech bro, but we can handle a little tech bro as we learn a little bit how to get more out of our devices. That’s what I want to recommend, and I’ll pass it over to you for whatever you’d like to recommend.

[00:32:55] Dara: Yes, if it’s okay, I’m going to recommend a couple of resources around the Universal Design for Learning approach. I would be an advocate of that approach partly because it touches on so many of the topics that we’ve discussed today. The first principle of UDL is all about really providing multiple means of engagement. That’s really about understanding why our students are in the room in the first place. We talked about that motivation and how our teaching and our pedagogy connects with that motivation. That’s one part of it.

The first one is a book called Reach Everyone and Teach Everyone. It’s an introduction to Universal Design for Learning. In terms of creating that culture of trust that we talked about, I think it’s an absolutely brilliant book. It goes through the full gamut of UDL as a concept, but for me, the strength of it is all about that engagement with the students and creating a community of learning that is very authentic and gives students, hopefully motivates students for the purpose of learning itself. That’s a book by Thomas J. Tobin and Kirsten Behling. I know Tom Tobin’s through my work, and he’s just a brilliant communicator around these type of topics. I’d highly recommend engaging in anything that Tom produces.

The other piece is actually an AHEAD piece, from the organization that I work for, AHEAD. We’re an NGO focused on creating inclusive environments in education and employment for people with disabilities. We actually have a whole series of short courses that we’ve released this year, which are two-hour free, self-directed short courses on a range of topics that are all about inclusion in education, including actually there’s an intro to UDL there.

They’re all housed in a little subset of our website called ARK, which stands for Accessibility Resources and Knowhow, so ahead.ie/ark and you’ll get five free short courses there that any educators right across the world can engage in.

[00:34:44] Bonni: Oh, that sounds amazing. I did spend quite a bit of time exploring your website when I was preparing for today but missed that. I can’t wait to go back and explore that and, of course, suggest that listeners do just the same. Dara, thank you so much for joining me for today’s conversation and for responding to my invitation to come on the show.

[00:35:03] Dara: It was really wonderful, and I hope your listeners get something from it.

[00:35:07] Bonni: I’m sure they will. Thanks again for being on Teaching in Higher Ed. Today’s episode was produced by me, Bonnie Stachowiak. It was edited by the ever-talented Andrew Kroger. Podcast production support was provided by Sierra Smith, who will only be Sierra Smith for a short number of months before she has a different last name and I get to say a different last name during this conclusion. Thanks to each one of you for listening to today’s episode and being a part of the Teaching in Higher Ed community.

If you’ve yet to sign up for the weekly update, head over to teachinginhighered.com/subscribe and you can receive the show notes from the most recent episode as well as some other goodies that don’t show up on the main part of the episode. Thank you so much for listening, and I’ll see you next time on Teaching in Higher Ed.

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The transcript of this episode has been made possible through a financial contribution by the Association of College and University Educators (ACUE). ACUE is on a mission to ensure student success through quality instruction. In partnership with institutions of higher education nationwide, ACUE supports and credentials faculty members in the use of evidence-based teaching practices that drive student engagement, retention, and learning.

Teaching in Higher Ed transcripts are created using a combination of an automated transcription service and human beings. This text likely will not represent the precise, word-for-word conversation that was had. The accuracy of the transcripts will vary. The authoritative record of the Teaching in Higher Ed podcasts is contained in the audio file.