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Rethinking Higher Education in the Age of AI · AI Advocates

• 0:00
  Reclaim your time, time, Welcome to AI Advocates.
• 0:08
  I'm Maggie Mosher.
• 0:11
  Hi, and I'm Lisa Dieker.
• 0:12
  And we are here at AI4, continuing the conversation with some amazing speakers.
• 0:15
  I'm going to present to you the very first speaker, and I'm going to have him give you one sentence about himself.
• 0:21
  I think you'll be really excited by who we have here today.
• 0:25
  Yeah, thank you for inviting me.
• 0:26
  One sentence.
• 0:27
  My name is David Chun.
• 0:29
  I'm a higher ed technology CIO executive, currently at Columbia doing some research.
• 0:33
  Awesome.
• 0:33
  So, what is your perspective on Columbia and R1 Research University's approach to that rise in generative AI, especially on campuses right now?
• 0:42
  Yeah, I mean things are changing quite a bit.
• 0:44
  It's so fast.
• 0:45
  There's new things coming out every day.
• 0:47
  I think there was an apprehension across most universities, including the R1s and Columbia, as well as Penn and University of Miami.
• 0:53
  We were all very worried about, you know, what does it mean for us?
• 0:57
  What does it mean for the revenue for the university?
• 0:59
  What does it mean for, you know, academic honesty?
• 1:02
  What does it mean for teaching?
• 1:03
  But I think that hump has been kind of overcome.
• 1:06
  We're we're not at this point where we're more embracing.
• 1:09
  We're more comfortable with what it does.
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  We realize they can really enhance academic curriculum.
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  And I think the most important thing is that most of these future universities are encouraging academic freedom in the world.
• 1:19
  So I think every faculty gets to decide what level of utilization is is good for the classroom and good for the learning as well as the research piece.
• 1:27
  Got it.
• 1:27
  I love that, and I think that's a perfect lead into our second question, which is kind of along that line.
• 1:33
  You've kind of alluded to it already, but like, do you see more banning, embracing, or reimagining with AI, or are there certain disciplines that you're kind of seeing leading it more than others?
• 1:44
  Yeah, you know that's a great question because I was at Oxford one time and I was in room full of like multidisciplined faculty members, and I think one of my colleagues says, "Well, who's working on AI research in the classroom?
• 1:56
  And they all raised their hand, right?
• 1:58
  And and there were some factions that were very offended because you know this is a realm of computer science and math.
• 2:04
  But I think it's kind of accepted now that that you know it belongs in the classroom, and I think the more clever you use it in the classroom, the better it is, and the students enjoy it.
• 2:15
  And I'm all for you know if you can increase student agency and student engagement in the classroom, you should use that, right?
• 2:22
  I mean, why why deny them of that, right?
• 2:24
  There's plenty of things to learn.
• 2:26
  It doesn't necessarily have to be a particular methodology and things like that.
• 2:30
  So, but I see a lot of faculty trying to incorporate the day-to-day activities.
• 2:34
  I see faculty trying to stay ahead of assessment and trying to make sure that the students don't use to kind of you know make sure they maintain their academic integrity, and I see other faculty members just kind of encourage you know self exploration of what the limits are.
• 2:49
  I think the key is is disclosure is the most important thing.
• 2:52
  Both the the faculty as well as students should disclose how they're using AI in the in the classroom.
• 2:58
  We love that.
• 2:58
  We actually recommend that everyone uses that APA seven disclosure that states exactly what organization, what kind of AI, what level of AI, when it was created, how you used it, actually the prompt you used, and then the output.
• 3:10
  I think that that's so important.
• 3:12
  And while you're speaking about students, we would love to know specifically what critical skills do you think high schoolers need when they come to college to be ready for the AI.
• 3:22
  Yeah, that's a great question.
• 3:23
  I always find, for whatever reason, the students that I've been involved in, I taught quite a bit as well in universities they're usually more prepared than the professors on these toolsets, right?
• 3:33
  Especially on technology, not the discipline that they're studying, but the technology.
• 3:36
  But I think the key is is the recent kind of survey actually at Educause did on student utilization, they really want guidance, right?
• 3:43
  So I think the guidance is the most important thing.
• 3:46
  They want kind of advice on you know what's a good usage and what's not.
• 3:51
  So I think that's the one more important things that that you want to kind of consider.
• 3:56
  So so kind of following that up, I'm a high school student or getting ready to come to college at your university, or maybe I'm a professor.
• 4:05
  What AI research tool would you recommend I use?
• 4:08
  And is free better than paid?
• 4:10
  How do I go about that?
• 4:13
  That's a great question.
• 4:14
  My wife is also a researcher too, and she did this quantitative study on what do students prefer?
• 4:20
  And the result was that they don't care as long as it's free.
• 4:24
  So I think that's kind of true, right?
• 4:26
  I think all the tools are particularly good about limits.
• 4:30
  They should the students shouldn't over rely on AI anyway, and those natural free limits allow them to explore enough that they still have to do the brunt of the thinking and the critical work.
• 4:41
  I think the most frontier models are pretty good at helping general things like gathering ideas.
• 4:46
  I love always using AI.
• 4:48
  I see students.
• 4:49
  I love seeing students use AI to kind of address weaknesses in their argument.
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  You know, or or missing elements.
• 4:55
  Of what I'm supposed to deliver, or what they're expecting in an assignment, and I see students do that.
• 5:01
  So, yeah, there's many ways to kind of look at that, but I think you want to encourage that as much as possible.
• 5:09
  Yeah.
• 5:09
  Now look, no, go ahead, please.
• 5:10
  Yeah, and so as far as tools are concerned, in in in I I recommend BoodleBox.
• 5:14
  I know it sounds We like BootleBox too.
• 5:18
  Oh you know Blue Box too?
• 5:19
  Yeah, we had the person who created it on our podcast.
• 5:22
  Oh yeah, yeah, oh yeah.
• 5:23
  So it's like, no, that's like amazing tool for faculty and students, and you get to use all the models, and you know, and it's kind of for them.
• 5:30
  And then you can look at it, so you can.
• 5:33
  I mean, it is like one of the most purpose built for teaching and learning, and I love that tool sets as well.
• 5:38
  But it's just plenty to.
• 5:40
  I think all frontier models are pretty good about at the at the free levels.
• 5:44
  Got it on that.
• 5:45
  Now, for teachers, are you seeing people update their curricula in a particular way or in a particular space that really helps students to be ready for the AI workforce?
• 5:53
  Yeah, I think workforce development is an important topic.
• 5:55
  I think I think you're right on.
• 5:57
  As I think a lot of things that I see is the assessment piece.
• 6:01
  I think there's a challenges.
• 6:03
  We just need to figure out new ways to assess our students and making sure they're keeping up with the learning content.
• 6:09
  Because I think the large language model has really made assessment a challenge for people who wants to kind of make sure that they keep those skill sets.
• 6:17
  So I see a lot of assessments being kind of altered in a way.
• 6:21
  I see faculty members see quite a bit of using more like group activities, kind of do those activities, and everybody brings something from the from their own respective explorations on AI research.
• 6:31
  I've seen also a lot of toolsets, training pieces.
• 6:33
  I think a lot of faculty wants to baseline skill levels.
• 6:37
  You don't want people who are very versed in it, like doing your homework in five minutes versus you know students who you you know don't really have the resources they rarely use it at home so and they don't have those skill sets and I see a lot of calibration in the beginning of the assignments especially at some of the R1's to make sure that the students have those base level base level skills.
• 6:59
  I'm gonna follow up on that do you think I've seen it actually improve the way we assess for some educators, particularly because now students are having to defend themselves, defend their choices, defend, and that's what we have to do in jobs is we have to collaborate, we have to be able to defend what we're saying and what we're putting out there.
• 7:14
  Do you see that improving?
• 7:16
  Yeah, I mean I see that quite a bit.
• 7:18
  I think the students know that the faculty are also embracing AI, and I think the more transparent you're about that, the better.
• 7:25
  And assessment, the beauty of assessment is you can do it so many different ways, right?
• 7:30
  And so for me, LLMs doesn't really help you collaborate as much, right?
• 7:34
  I mean, so when you get two students together or six students with a faculty member in there, you know that's very difficult for LLMs to kind of inject themselves.
• 7:44
  So I always like group projects, just like we said, and it helps assessment.
• 7:48
  And I think also I read the on the recent recent Educause report on AI usage for students that most students prefer faculty engagement, right?
• 7:56
  So it's kind of proven, like yeah, they know AI is there.
• 7:59
  They know make it makes it easier, as long as you're transparent about how you use it in the classroom, and you you set clear expectations.
• 8:08
  I think you're going to have a lot more fun, you know, engaging the students there.
• 8:13
  So now we're going to ask you to get your crystal ball out as our last question, and if you were, and we know you're a visionary from all the work you've done.
• 8:22
  So five years from now, what's higher ed gonna look like, and how do we prepare for it?
• 8:28
  Yeah, I think it's really about workforce preparation.
• 8:30
  I think the students demand that.
• 8:31
  That was also on the survey as well in AI, and I think there's gonna be a lot of curriculum and program shifts, and we see that today.
• 8:39
  I don't know if you see the latest Chinese report on their their attempts to kind of recalibrate the AI as a strategic priority by changing majors that don't really lead to job placement.
• 8:48
  So I think that the way we're going to look at curriculum, the way we're going to look at course offerings, the way we're going to prepare students for you know the changes that are ahead.
• 8:58
  I think that's the best way we can participate in that dialogue, and not just be sad that you know we're not going to read those books anymore, or you know we're not going to get to draw.
• 9:08
  I mean, I love that.
• 9:09
  I still do that to this day.
• 9:11
  Read books, so.
• 9:12
  But at the same time, we we just need to kind of get ready for these new toolsets to come in.
• 9:18
  Yeah, I think that's true, and I think the the ability to keep writing and to keep using that brain connection while we're also using AI and all I love that you said that and I want to thank you so much for your time today specifically thank you for helping us give teachers a way to improve their curricula and to work with students and we appreciate you helping them save their time.
• 9:37
  thank you so much for inviting me I enjoy talking to you.