Well, hello everybody. Thank you for coming and thank you for attending on Zoom. My name is Joshua Wilson. I'm an Associate Professor of Education at the University of Delaware. And I co facilitate the AI for teaching and learning working route with my wonderful colleagues Meg Brady, Associate University Librarian for Learning Engagement and Curriculum Support, who has generously offered this wonderful space and the library services to support this seminar series on Skeranza, the Director of IT for Academic Technology Services, and Mike Evans, Director of Computing Operations for Learner College, AI for Teaching and Learning Working Group has been charged by the Provost to help guide the University of Delaware over the next two academic years as we develop innovative practices and propose sound policies regarding the use of emerging AI tools. On behalf of all of us, I'd like to thank you for attending today's seminar titled AI Powered Career Advancement, Navigating Career Preparation, Recruitment, and Lifelong Learning. This seminar is the eighth in a year long series offered by the AI for Teaching and Learning Working Group designed to explore how AI might reshape teaching and learning in higher education. The goal is to help UD faculty and staff start to understand foundational AI concepts, their implications within various disciplines and their potential impact on the future work. We hope you'll join us at our next seminar, which you'll find listed on our website. In if you Google AI for Teaching and Learning, UD you'll find it today. We welcome our presenters, Dr. Stephanie Rabel, R. Lynn Sidnor Epps, and Dr. Rachel Opel. Dr. Bel is an assistant professor of entrepreneurship in the Lerner College of Business and Economics. In 2023, she was awarded with the University of Delaware Excellence in Teaching Award. R Lynn Sidner, Eps, serves as the Director of Career Connection and Experiences in the UD Career Center. In this strategic leadership role, Lynn leads her team in collaborating and consulting with partners across UD to facilitate and maximize the impact of equity focused recruiting programs and initiatives, career experiences, as well as connections with employers, professionals, and alumni throughout the curricular and co curricular experience. Dr. Rachel Coppola is the Director of Life Design and Career Integration at the University of Delaware's Career Center. She leads the LDCI team in the development of scalable equity focused programs and initiatives that integrate career and life design content into the university's curricular and co curricular initiatives. She works with faculty, staff, and students to ensure undergraduates and graduate students are equipped with the tools they need for postgraduate success. We're very privileged to benefit from all of their experience today. Before we dive into the talk, a few notes on logistics. First, we have attendees, both in person and zoom. If you're joining zoom, please mute your microphone and we'll do it for you. If you forget we are recording this session, you probably want to keep your video off. Second, please, everyone hold your questions until all of our presenters finish. We will have a dedicated Q and A time and we will alternate between and zoom questions. Zoom attendees, you can submit your questions through the chat and I or my colleague me will relay them to our presenters without further ado. Let's give a warm welcome to our presenters. Thank you so much, Josh, And thank you guys for being here and bearing through the weather. And hi everybody on zoom. It's good to see you. As Josh said, our topic is about AI powered career advancement. We'll talk about a few different topics. My part is a little bit of the starting mechanism. Here, I will give a little bit of background as to how I got here. In a way, this trajectory follows a lot of what I did. Believe it or not, there is such a thing called lifelong learning. And I did my second Master's in lifelong learning, policy and management. It's a thing. Part of what that trajectory took me to is understanding how people learn and how we as a society have these jobs and how we skill for them. Part of my interest in that space actually started many, many moons ago. Since being an entrepreneurship faculty member, I often get the question of, do you feel like you're immune to a lot of things, the ups and downs of the career cycles that we experience. And I'll get to that towards the end. But as we have hit AI and we've been dealing with it as faculty and as staff, and we're grappling with what this means. It's been really interesting because this isn't the first wave that we've experienced of having, or having some sort of disruptive technology. If you remember back in the day and I feel like I'm not talking to my students, maybe you guys will remember. But there was a time before Google and I feel like this is where my students would be like, wait what. There was a time before Google, as Google came into the picture, I remember that there was this disruption because we used to frame knowledge as the ultimate driver of our value. And we saw higher education as a mechanism to get knowledge. And the more knowledgeable that we were, we were able to go into these career paths and to use that knowledge. When Google came out and started becoming better and better as a search engine, we started realizing, oh, so many more people can access knowledge which is incredible. But it also is a little bit of a disruption because then higher education had to think about, okay, if we are the deliverers of knowledge and we're preparing people by giving them knowledge. What makes us unique? I remember as I was in one of my first positions as a faculty member, we started thinking more about the creative economy. And I'm not sure if anybody has come across this term, the cre, creative economy. We kept thinking, okay, well the thing that protects us is our ability to be creative. Google search engine can't be that creative. I can type things in, get access to knowledge that we know and understand. Technology can't touch creativity, right? Feel like I wish I could take my 2016 security blanket and just rip it to shred, because that is how I think we feel like right here we've gone through these times where we have a sense of comfort about Google Googling. Yes. We knew what that meant when we were like, students are Google the answer to things, great. How do we embrace that technology? We're not to be scared again because we're now just in that phase of trying to figure out how AI is resetting things and how we can also take advantage of it. And that's why I think the series has been a lot of fun because there have been different people in different perspectives and we get to talk about that from acres perspective. I want to go on public forums to look at how people are talking about jobs and the economy. Now, now that we have AI, what does this mean? So I have looked at some of these things and basically saying it's disruptive, it's chatbots are now replacing workers. I can tell you as an entrepreneurship faculty member, I often, and I teach social entrepreneurship. And I emphasize the social side because I would say about a third to half of my class thinks they're in a social media oriented class. And kindly disappointed that that's not the class they've signed up for, included this one as well. So I get a lot of students that want to be influencers and they're like, okay, social media is a good driver for jobs, right? I see all these people in public personas that get jobs on social media. But a Spanish agency that is modeling agency who is now featuring influencers. They can generate AI influencers that are a lot, a lot cheaper than the real influencers. And this is something that we're actually seeing bubble up in a lot of creative industries. When we think about like theater, film, things like that, that are actively being filed, photographed things like that, AI is actually invading those spaces as well. Thinking back to some of these things, the ability to be creative or even be yourself is into question. Which is a weird space to be in. When we think about past predictions and like what we used to have a security blanket about when we think about careers and what we thought would give us job security both in traditional and emerging roles. We have some things like adaptability, skill development, critical thinking, problem solving, being innovative, enterprising in what's called durable skills, being able to withstand that space. And I know you guys are more experts in space on durable skills in case you want to emphasize that point. But some of these things have persisted. Even though I shredded that security blanket from years and years ago, we still have a universal language of things that have persisted and still are these universal skills that we're looking to give students to have. I'm going to pass it over to Lynn to take us a little bit further in the presentation. Thank you, Stephany. Again, my name is Lynn and I'm here to talk a little bit about the employer side and what are employers doing. What they are seeking, what's working. Some of the challenges when it comes to students getting jobs out of college. One of the things that as we were talking, we're talking about lifelong learning and the economy of jobs. And we'll talk about career readiness and the question around what's important to employers, What are the things that they're evaluating? How are students going to be best prepared to get that first opportunity or the next opportunity? We did some digging and some research, and I'm going to distill it into three words. So here's what we know. We don't know, right, in terms of generating it, is a fast moving train, right, In terms of how things are changing in the marketplace and in the recruiting space. And so I want to level set a little bit in terms of when I say recruitment, what I'm referring to. Right? So recruitment, when we were talking about it from the aspect of the career center space, it's around employers that are identifying sourcing, attracting, selecting, hiring students or individuals for internships and full time job. That's when we talk about recruitment, that's what we're referring to. Some of the things that we're seeing in terms of, oh, there's one thing I wanted to share. I heard I was at a workshop with employers talking about AI, and one of the presenters referenced Amara's law. I'm not sure how to pronounce it, that's the right way to pronounce it. But the law is, we tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. The other piece that's important is that AI, the impact of AI will unfold sooner than anticipated. I don't know how much sooner it can be, but I think there are a lot of variables at play here. The other thing that we found out when it comes to employers in general, approximately right now, and this was a huge range, 12% to 45% nationally, are engaged in some type of generative AI. We'll talk a little bit more deeply about the recruiters that come to UD, so that'll give us some insight there as well. Some of the things that are working, what we're finding and recruiters are saying that it's helping with their recruitment quality in terms of the candidates that they're seeking and sourcing, there is increased efficiency from the recruiter side, just in terms of recruitment in general. If you're not already familiar, the recruitment cycle used to be cyclical is year round, for the most part now across, but it does vary by industry. And it varies in terms of how employers recruit. Some come on campus, some don't. And it's not that they don't want to come, it's just that it's just not a part of that work. So we're looking at a lot of moving pieces when it comes to what the employees are doing in the recruiting space. In terms of efficiency, what some are saying is that the use of generative AI is helping in terms of the ability to identify candidates across multiple areas and then also screening and matching candidates. Then there are some which is interesting, scary, or are using chat box in terms of the initial screening phase. But there's a theme that I saw in reading and talking and learning. There still is the emphasis on the face to face as much as there is the technology component. And that's where we'll talk more about our students and their readiness for that. Yes, you can use generative AI and you also need to be able to have a great conversation and promote yourself and understand share how you can contribute to that organization. And so in, as much as there are some benefits, there are also some challenges. And so these are some of the key challenges that are pretty obvious. One being also that small and medium sized companies don't always have the same resources to tap into the same resources that a larger company, which ultimately, from their perspective, cause more of a negative experience for the candidate, right? So everybody wants a great candidates experience because you're trying to secure that candidate for that role. The other piece is of course, bad data and bad data out there are some data that's already out. There are some studies out around the algorithmic bias, right? And so when it comes to screening in or screening out candidates based upon gender, ethnicity, it's real. And so that is evident. So even in the session that I was in, there were a lot of employers who expressed that there are concerns in that space. And so the other part is again, the chat box versus human applicants. So one of the things that we did was interesting, in fact the exciting for us is we asked our employers, those who come to UD, because we can get all the data in the world nationally and all. But what happens here that was important for us to begin to have these conversations. We asked, we sent it out to quite a few employers that actively recruit on campus. We received responses from 59 individuals across that represent 40 industries. A review D, which is pretty significant. And out of the 49 I'm going to, I'm going to, I'll read these so you don't have to read the chart. And then you'll also receive these via the slides. But in the first left side, the question is on a scale of one to five, how familiar are you with generative technology in the context of hiring and recruiting? One being not familiar at all, five being very familiar. This is where out of these 59 respondents where they sit, which is not surprising, right? So then if you go to the top. Right, left. If using AI tools in recruiting and hiring, what specific areas of the recruiting process do you utilize generative AI? And you'll see way out is the candidate outreach piece, that's what they're using. And that ties into the efficiency piece, right? It's a little more efficient to use the tool in that way. And then sourcing candidates, again, identifying the candidates for your roles. Here you'll see, are you currently using generative AI tools in your recruiting and hiring processes? No, it's large there. But what we're seeing is there's, there's some trending happening there. There's some where yes, they're using it some actually even had a date of March 4, that's where they're going to start using it. We're going somewhere with this. And the last one is how would you rate the effectiveness of generative AI in improving the efficiency of your recruiting and hiring processes? One being poor, five being excellent there, right in the middle. Right. Out of those respondents, one of the things that I wanted to share to six are actually using generative. Out of the 59 respondents, six are, and they're in the industries of hospitality, retail, government accounting, behavioral health, and software. But the other interesting aspect was eight are planning to use it in the next year. That's a pretty quick decision or rapid process in terms of them using that. The other thing that we asked, the final question, you did ask an open ended question. How can our students best prepare to leverage generated I in the job search process? One of the things that I tried to distill it by themes, but one thing that came out multiple times is around the face to face piece, you'll see this statement right here stood out. We are not hiring AI. We are hiring individuals who can articulate for themselves as much as it's a tool. There are things that they can do in terms of learning technical skills, building their skills, definitely for grammatical enhancements. And as importantly is how you communicate, who you are and why you're the best fit for this opportunity, and why we might be a great fit for you. The ability to communicate, to understand who you are, and all in those ways are super important and incredible, and necessary. And so that's where Rachel will come in and talk a little bit more about career ready. We're speaking. I do have one. I do have a site exciting. So if you are familiar, we use a platform called handshake. And it's used for the way that we deliver multiple services and experiences for our students. Handshake is introducing cocoa, which is an AI tool that students can use to help them get answers to some common career related questions. They can log in and ask Cocoa, ask their personal career pilot, which careers match my skills they'll be using. And they will that responsibly based upon looking at the student's profile in handshake, right? So they can ask, how do I get a job? For example, in data science, cocoa will give some general information there. The other piece that's really going to be really interesting, and this is going to be go full in the fall, is when a student logs into handshake and they want to apply for a role. They will be able to ask, am I a good fit for this role? The platform will look at the position description and look at the student's capabilities and help assess if this is a good of course there's always going to be you need to get some additional probably advice, some additional support. But also the other idea is what advice do you have on applying for this role? These are the types of ways that handshake and various platforms now are incorporating generative AI to help the candidate process, to help the employer matching process. This is brand new. It lapses again full in the fall. So again, you can see the trends in terms of how generative AI is impacting and how rapidly the change is taking place. Now I will turn it over to Rachel to talk about preparing students. Excellent. Everyone on zoom parallel everyone in the room. Again, my name is Rachel Pla. I am the Director of Life Design and Career Integration and the team that I work with, our job is to help students figure out who they are and what their places in the world and how they want to get there. And we will typically talk with students, and whenever I give presentations, I always ask students, you know, how many of you know exactly what you want to do and you know, a few hands will raise and how many of you are waffling between careers and usually a few And then how many of you have no clue. Right? And then a lot of them won't raise their hand, but there's a lot of hands that didn't go up the previous time. So we know they don't know exactly what they want to do. And one of the beautiful things about generative AI is that it can help students start to understand. What they need to know and what the limitations are to what Lynn was saying earlier. But I also think it's really important that faculty, because we know that students don't always come to the career center first. Like all the data shows, they go to faculty before they come to us. Making sure that faculty are aware of the ways that a student can use generative AI in their career. And professional development is so important because you are their first motive, like contact for this type of information. So basically when you're thinking about coaching students in the use of generative AI, it's not just about doing papers for the classes, right? They can also use that to connect what's happening in the classroom to what might happen in the future in their world of work. Getting them to ask the right questions with generative AI is important, we always say in the career center, you know, brainstorming, yes. For generative plagiarizing, no, we don't want them using it to write their papers, but we also don't want them using it to write their cover letters. Right. When generative AI first hit a lot of people in the career center of space, we were having conversations about what we were seeing. And a lot of my peers at institutions across the country were complaining about students are just taking their cover letter, asking genera, asking chat, GPT, write a cover letter for me for this job. And it was obvious to the career center employees and also the employers that the student didn't write that work, right? So helping students understand that they can't use it by itself. That it needs to be done in a collective space. So they need to understand the basics. That it doesn't replace the human touch, it doesn't replace common sense, right? And that it is, it has to be trained. The more that a student learns how and gets familiar and comfortable with using it and dumping in the right information, the easier it's going to be to generate the kind of responses they need to learn not to do the work for them. Because again, they're not hiring AI. They're hiring students. The students actually need to figure out how to define clear objectives. They need to learn how to ask the right questions. There was a wonderful event I heard at learner last week where a student talked about what are the kinds of prompts that I need to, that students can use to ask the questions of generative AI, chat, GPT and all these other places to understand, what do I need to know to become a data scientist, or what's an entry level position in such and such field. Like sometimes those questions are broad and abstract and you don't know, you're not necessarily going to have that in your head. You can ask generative those types of questions. So getting students to think about the industries and the jobs and what they want to do. And then asking those kinds of questions can help generate some answers that will help them process through this disconnect. The other thing is it can ask if it connects, right? How can I connect, you know, this happening in my marketing class with this happening in this field? And let generative AI try to help connect some of those dots for you. So again, it can help you define some clear objectives. But it can also, and this is probably one of my favorite things about generative AI, help you think outside the box, right? Help you think about what else might be out there. So being able to explore diverse resources like student groups and RSO's, and national organizations and industries, and niche industries that students may not be thinking of that could be a really good fit for the work. Again, getting them to think about like instead of asking it for the perfect job, ask broad questions. Kind of do a deeper dive and see what else is out there. U. You want to help students critically evaluate the results, but not just take them as it is, right, Not at face value, they need to evaluate them. But also maybe in conversation either with you or maybe that's where you decide to refer them to the career center so that they can meet with someone and actually process it if they're confused. Because the one thing that we know about generative AI is that it will not replace the human. Eventually a student is going to stand in front of someone for an interview, right? They're going to have to have that conversation. That cover letter that resume having the right answers to questions are only going to get you so far. You still need to be able to think and critically process that information. We're seeing this a lot across different platforms. It's still learning, right? Generative, AI, the word generative is telling us it's a process, right? So it's not always accurate. And I think sometimes students take the information that they're getting from chat boxes and chat GPT in all of these different places at face value. And they can't do that. They need to understand that it's not perfect, it's not always accurate, and sometimes it's only accurate to a certain point. But even then they're going to want to look beyond the data and actually see where is that information coming from? Can I find that in other places? Can I connect the dots, so to speak? Right? And then we want students to not be totally dependent on it, for their answers, because again, that's not going to help them in the long run. Stephanie talked about the need for durable skills and that idea of critically thinking is really important. If you're just using generative AI, you're not thinking you're regurgitating. You're a parent. And we want students to not be parents. We want them to learn. And this is a chance for them to look at that information, process it either alone or with someone else. And become a skilled thinker so that they can actually sell themselves, but also make the right decisions for themselves. All right, and what are the ways that the students can use it? Lynn talked about this. She had a slide where even the employers were kind of backing up some of this stuff that I actually wrote, right? It can help students learn about typical career paths within a given industry. Students will come to us and say, well, what can I do with this major, right? We even have whole platforms that can provide that information. But a student can ask that question within generative AI and get some really interesting answers. But it can also say, what else could I do? Right? Again, it's machine learning. It, you have to think about ways to kind of teach it to do the work for you, so to speak, right? So getting them to learn about typical career paths, it can provide current understanding, right, So that students can understand what's happening right now. And I love that because as faculty members, you don't have to think about what happened when you were coming up through a particular industry or when you were an undergrad, right? Generator. I will tell you what you need to know right now. What's happening in an industry right now? What's happening in the job market? What's happening, what are emerging roles? We always talk about the way in which things like cloud computing and genetic counseling and all these things didn't exist when we were undergrads. And now they exist. Who knows what's going to exist, what's emerging? Now when a student is getting ready to graduate chat GPT, you can ask it, those kinds of things. What are the emerging jobs? What are the emerging industries to be aware of in the next five years or the next ten years. So see what it says, but again, you're still going to want to do some research and when I say you, I mean the student. So I'm not saying you all have to do that and prepare it for the students. That's the task that you can give a student, that's their homework assignment, right, to go out and do that. Sometimes students don't know where to start. I was actually presenting to students last night and one of them was struggling with figuring out how to network. And they were a little bit of an introvert. And so we were talking about ways to use U sites like handshake and linked in to do that work for you, right? Sometimes you don't know what you want to ask. Chat PT or other sources can help you generate networking questions for someone in such and such industry. Let it gate, you don't have to ask, and this is what I said to the students. Don't ask everything that it tells you. What do you connect with getting students to think about who they are and what are the answers that they are looking for? And ask those questions again. Brainstorming, it's a great tool and students need to understand that that doesn't replace the work, but it can help remove a blockage. We all end up with blockages. Sometimes one thing students always want to know is salary, right? And that changes all the time and it's different for different industries and different locations and you know, cost of living and all of those things. They can learn that information right there on the platform. Then you don't have to know that, we don't have to know that. Again, it changes so much. So those are things that can be useful tools, useful ways in which to use chat GBT and other generative AI. The other thing in grammar was a big thing with employers. One of the biggest complaints employers have is getting resumes with typos and cover letters with typos and things like that. You can have generative AI do some of that formatting for you, right? So students can learn like they don't have to always just rely on themselves. We tell students not to rely on themselves anyway. That's why we have drop in hours at the career center. Right. They can come in and have somebody look at it, but they can't do that at 02:00 in the morning when they're in a panic. But they can upload it into GPT and have it take a look and format their resume or their cover letters or things like that. Keyword optimization. So a lot of industries we were talking about, they're going to maybe do some research on emerging job markets and understanding roles. Well, what are the key words that are being used in those areas? Are the sprinkling those into where appropriate for not lying, we talked about that yesterday too. But are they spin those keywords that are being used in the industry into their work, right? Into the their resume and their cover letters and even the language that they're using to talk about themselves in an interview. They can do keyword optimization using Chat and PT. It can also help them quantify. Students sometimes struggle with understanding like, how do I quantify what I'm saying about the work that I did or the work that I want to do? They can provide suggestions. And again, the keyword there is, I should have probably put that in both suggestions. It still needs to be true, they need to be accurate about what they're putting down. It can give them feedback on tone and language, and it can give them practice questions. So it can say, you know, you could ask it if you are planning to interview for a particular type of internship, you know, what are the top ten questions that might be asked for someone interviewing for this position? And then what are some really creative answers for that. And then the student can then compare those and decide how do I connect with that question and with that answer to be able to make sure that I'm presenting myself properly, right? So again, they don't. We want to be very clear that we're not encouraging students to lie or misrepresent themselves through the use of these tools, but we're using it as a way to help remove the blockages that they might have. The panic that they might feel. And learning, and learning more about these industries or more about themselves. Because as they learn about who they are, that's going to help them determine like am I a good fit for this? You know, Lynn talk about Cocoa being able to say, am I good for this position? Well, maybe it says they're not, but the student feels like they are. Well, that would be a question to come in to talk with a career counselor about. Or, you know, to maybe go back and look at how they're representing themselves. Maybe they're missing some things. And so it can really be eye opening for a student in positive ways even if the answers that they get aren't the ones that they thought they were going to get. Okay. Then also, in addition to practicing, they can get some post interview guidance. As one of the questions we get a lot in the career center from students after an interview is like, now what, what should I do? Sometimes it's industry specific about what the best practices are. Getting that information through a source like at GPT could provide insight that they wouldn't normally have. Um, additional coaching suggestions that students can use Cha, GPT and other generative AI platforms for is to provide a list of companies. Students will often say, I don't know where I want to work or I want to work at this company. Well, what's your plan B, right? I don't know. Okay. Well, let's see. You can ask, what are other companies related to this industry? Big do you want to be a big fish in a small pond or a small fish in a big pond? Right? So you can kind of do a little bit of research on different types of companies that might be a good fit for a student trying to go into those industries. It can also help them identify entry level students. Sometimes struggle with figuring out, well, what kind of jobs should I be looking for? Right? Well, take the guesswork out of that. It's not always going to be, first of all, it's not going to be like director of such and such, right, for their first stop. What's the first step in that role? What's the entry level position that they should be looking for? Instead of being overwhelmed by the thousands of positions that are posted on length in and handshake, they can start to really zero in on those types of key words to identify the titles that they should be looking for, for their work. You know, a lot of companies have employee resource groups, Students can recognize that connection with student organizations. Right. A lot of them are part of RSL's here on campus. Well, the adult version of that, when they graduate, are those employee resource groups that are going to be on in companies. So getting a list of what kinds of professional organizations and employee resource groups might be a good fit for someone going into XY Z industry. And maybe it's one because they know exactly what they want, or maybe it's two because they're not sure. But it's going to help them kind of understand that a little bit more when they're trying to provide a responses. So, you know, sometimes students will say, well, I don't necessarily need all of this because I'm going to grad school anyway. You could still benefit from using a resource like generative AI to help with framing essay responses and framing questions, and figuring out what are the best responses? What are the ways I need to organize what I'm trying to say to get into this particular grad program, right? Or even instead of providing a list of companies and start ups a list of graduate programs and such and such. Because maybe there's a really good program that a student wasn't even aware of because they were only focused on the one that, no offense their faculty member went to. There might be some other alternatives for them that could provide other scholarships or graduate assistantships or different things. Again, they can use it to think more broadly about things. And then also I can' already mentioned that generating questions that might be asked within a particular industry, the important thing, just like you all have different, since I'm on the AI for Teaching and Learning Working group, I've heard a lot of conversation from faculty. And some are really excited about generative AI and some not so much. And one of the things we tell students companies are no different. Just as Lynn pointed out, some companies are all in and some companies are not. Students need to be very strategic when they're thinking about doing their research so that they understand what might be happening, right? You can go to a company's website. This is where it's not, you're not going to generative AI for that information. You're going to the company's HR website to understand what are they doing. And most likely if they're doing something, it's going to be on there and it's going to say, this is the process, you're going to go through these rounds, or you're going to do this or you're going to talk to this chat box. That shouldn't be a surprise. They should know that kind of information and they can easily get that understanding what the different companies are doing with generative AI. Some of them, and we didn't really deep dive into this, but some might be using tools to determine if a student is using generative. I, I mean, I've talked to colleagues who can look at a cover letter and tell it was written not by that student. The same thing's going to happen with recruiters. They're going to know, right? There's that joke, like nobody's going to know. They're going to, they're going to know. Students need to be very cognizant about what they're putting out there. And then just being open to, again, I think the possibility, again, I can't emphasize enough. Generative is a tool, but it will not replace connecting with career center resources. It will not replace the student putting in the work to be able to appropriately demonstrate who they are and why they are a good fit. I'm going to turn it back over to Stephanie circling back to some of the misconceptions when we're on the faculty end of things, how we can regroup and think about how to translate this over to students. You'll see this graph here I thought was really interesting. And this is screen candidates by GPA, percentage of respondents. It goes to show that when we think. Of GPA and how important it is. Over time, we're seeing that GPA is less and less important. We see a lot of anxiety in our students to perform and to perform well. Oftentimes, it's a root cause of why a lot of students are depending on chat bots and other generative AI technologies. Part of the reason why they're depending on it is because they grew up during this time when they were told I can't like, you're not going to be able to find a job unless you're perfect. But we're seeing this less and less and this is something we should share with our students. Okay. I'm not encouraging like all of us to be like yet, we're not there yet. But I think we should give a sense of concert students that we're going into a very much like human economy, thinking economy. We have to be in a space where we're valuing you as a more holistic person. You're no longer just your set of knowledge, it's not your creativity in the old way that we thought about it, but it's your ability to take information in and to critically think it through. When we think about where these cal skills that employers are still thinking about how we can root some of our learning outcomes and other things. So we can tell students like, hey, it's still worthy to be here. Even if it's like, it's okay that you get a B or C in the class, but you still have to come away with these learning outcomes. We have things like problem solving skills, ability to learn within a team, a strong work ethic, analytical, quantitative skills, communication skills, and technical skills. You'll notice these technical skills to the point that Rachel was saying before, like technical skills do not replace the person. And I think a lot of students are, again, coming from this mindset of AI has the better answer than I ever would have come up with. But we want them to learn and employers want them to be people too. So we're in this spot of faculty having to really be more explicit about some of these things that we're showing students. We're basically showing them that GPA is mattering less and less to employers and that basically we are embedding some of these durable skills into the class. We're not just talking about, say, philosophy, sorry. Anybody who's in philosophy, I'll put myself like, we're not just talking about social entrepreneurship because we feel like it. There's a lot of these embedded skills within this, employers are looking for that. It gives a little bit of a more universal space to the work that we do. So instructor guidelines shout out to the series. There was actually a really good ethics in use. See October 19. All of these are actually up on the website. He you'll see this later if you're watching. Lynn and Rachel were the perfect examples of why career services is a great partner for faculty to have in the picture. Because oftentimes we're navigating the use of AI in almost like an assignment transactional way. We're thinking about it in a very narrow mindset. We're thinking about like, oh, okay, is this student being unethical in a particular assignment? Am I seeing the use of AI when they shouldn't use it, or are they using AI appropriately when I'm telling them to use it? But there's a bigger picture at hand and I think career services is a really good partner to show students, hey, if you're getting resistance from like a faculty perspective of students saying like, yeah, Jan, I want to use this anyway. They can give a little bit of a situatedness to say like employers don't want you to be a person. They're not going to be that impressed with your AI skills. Anybody can write a question or two. We really need you to be able to think about the material and be able to use that material in a meaningful way. From an instructor perspective, again, you have to think more in terms of embedding our student learning outcomes, in terms of these more durable skills that we see that are evergreen. Helping students think about how they can translate some of those skills and maybe even write them into a cover letter saying, hey, I tend to take classes where I'm learning critical thinking skills. I tend to be very good at that. Here's how that translates to the work that I want to do with you guys. Toll is a really great partner in this as well. They're running a working group right now. They're currently working through a few resources in terms of how to put it into your syllabus and other basics. But again, these are baselines of AI. When we think about this, we want students to think about their coursework as life work. This is really the start of their life, though a lot of our students, I actually presented to a group of freshman earlier. They asked if any of them had taken a gap year group of about 40 students. No one had taken a gap year for many of us for getting year 13, 14, very exhausted students. They don't have the lived perspectives to understand that they need to be people outside of just transaction assignments. As faculty and staff need to think about, how do we teach students to be people first in GPA. Second. And that leaves us two questions, our presenters. I'll go over here because otherwise I'm happy to get, I'm really intrigued by this idea of the movement towards human centered, sort of being human, like a human economy almost. And I'm curious if you could talk about that a little bit because I remember talking with you about the move to maybe like humanities and critical thinking. Probably actually like, contrary to what you might expect with the rise of AI, actually the push to humanities, that might accelerate that push. And that's what I'm hearing from your presentations, that you're hiring a person, You're not hiring an AI, you're hiring the ability of someone to think and critically evaluate. I was also thinking too like to be ethical, especially in this world now as students are coming up in this like social thinking about like being very socially conscious about like. I'm wondering if you could just talk about that a little bit. Is the right, is that a right takeaway that I'm having? Am I on the right track here? Is that how you're all thinking about like our movement from knowledge to creativity to what's what we're in now? Yes. Do you guys want to You can start. Okay. What I would say is, funny enough, it's somewhat on the fly, but I think there's a lot to it that we have been underestimating Over the past decade, we've been really thinking about a very direct relationship between careers and academic programs. And I think we need to start rethinking that because when you have technologies that can, you know when you go to the doctor's office. I don't know if anybody has done this recently. My Dr. will kind of turn away from me, Go on a laptop and actually search for things. I don't know what she's searching for, I don't look. But in any case, I feel as though even these highly, highly specialized technical positions that we used to train students very appropriately for, there's technology. Now for that, we're now in a phrase of mind that we have to be very thoughtful, we have to be people that are able to, again, have those critical thinking skills, communication skills. These are things that have been existing in the humanities and the social sciences embedded in the hard sciences. But maybe we've been looking away from them somewhat in terms of we're thinking too much about the technical skills and the professional skills, whereas we have a lot of these more universal durable skills that might be more meaningful when students go out to the career, especially when we see these bumps in technology that will continue to happen. Ai is this year, but we are going to have something else in five years. The one thing that oftentimes, I think historically we've been villainizing things like the humanities. And thinking, well, oh, I only need to know Shakespeare if I'm going on jeopardy, but at the same time, and not everybody's going to end up on No, I said that very digitally, but there's a lot of skills within that in terms of appreciating human artistry, being able to know how to see history within things, to see cultural references to appreciate the arts. So there are a lot of things embedded within these subjects that maybe we've just been putting on the back burner because it didn't have a direct relation to a job. Yeah, I would add that it's never one size fits all. Right. Industries are so different, even in and of themselves, that I think it's really important that we help students learn to be broad in the ways that they even think about what their career is going to look like. Because there was a time like my dad works for the government, he was IRS 40 years. That's not the typical path for people anymore. They're going to go into a lot of different careers in a lot of different industries. Which is why things like chat GPT can enhance understanding but shouldn't replace thinking. We shouldn't replace the human. Because we need to be able to think about who we are, what our places in the world where we want to go next, and then what's out there. And since that's changing, these are the tools that can help us understand that, but they're not the tools that are going to replace those job leads or even just how we present ourselves. We still ultimately have to stand in front of somebody, shake a hand, eventually make eye contact, and have a conversation. And if you can't do that because you're able to hide behind the work, then you might get to a certain level, but then you might hit a cap. We just think people need to think more broadly about it. So we have a question. So go ahead and head on that. And then come back to the room. Well, first we have a recommendation for a book. Which is exciting. Thank you Stephen Davis for linking us to the possibilities economy, Robert R Arko, which is who is one of the 100 most cited social scientists in the 20th century. So there's one that is recommended. And I do want to ask a question that Asif is asking. We know some AI tools generate false links and information. How do you suggest we approach this challenge check? Yeah, that's what this lady would say, Librarian always. The other thing I would say is just to piggyback on what was said before, I teach a field that didn't exist 15 years ago in a lot of institutions, and even now it's not even taught at a lot of institutions. So it's an emerging field. Sometimes I'll point that out to students about the cyclical nature of jobs. But the other piece of it is in terms of, can you remind me the last question? How do you suggest we approach the challenge of generating false information or links if we're sort of asking students to leverage the tools in this way? Yeah, so I think this is where we need to be much more explicit, as in faculty roles. We need to be more explicit about what our learning outcomes are, specific to our learning objectives, or rather for a particular assignment. And I say that with a half eyebrow raised because I had an interesting conversation with a colleague about how we permit AI and how we don't. And we actually had the exact opposite. So she was someone that was saying, okay, you're generating a business plan. You can put that into like chat GPT or something like that, like hold up in my class. Like that's the skill I want you to learn. I want you to say advance your knowledge of stats in a particular like social cause then that way you can get yourself a little more prepared to figure that out. But this is actually where in class, like we actually dissect like, okay, use AI in this, Like we want to elevate that conversation. Because then when we look at some of these things, like where are the blind spots of this data? Where are we seeing this? And this is that human part of it. Yeah, I think we need to be much more intentional to say how our learning outcomes are mapping. Because someone can have an opposite situation if they're taking her class in my class. A student might get this confused and then see like, oh, I can use AI for this but not for this. And why in this class it's okay and why in this class it's not? Yeah, absolutely. It reminds me of the way we have to approach copyright, right? It's like it's always, it's complicated and it depends situation, right? So it really depends on what the underlying situation is, the need and how you do it. Of course, I really appreciate that question and there's going to be a ton of need for evaluative skills in almost any context of using these tools. That in itself could be an assignment especially so we know chat, GPT itself doesn't give you correct data for like last year. This year you have to go, it only goes up to 2020 something. I can't 22 something having it ask about real time stuff and seeing what it does. Because sometimes it'll just say, I can't tell you that. And sometimes it'll just make something up. And I think that could be a really interesting class conversation. Yeah, yeah, I think it was a Harvard professor who did that as an assignment. And you had the right SA and then also use generative AI board and then had them compare. Yeah, I did a version of that. Yeah. Through line that I feel like I'm hearing this is we've moved from a certain kind of knowledge economy to a skills economy. Right. And so higher ed has moved from big knowledge providers and guardians to big skilled providers and our conventional metrics, my degree, my GPA, even some of the other like the co curricular stuff doesn't cut it anymore, right? So what I thought this might can lead to is some talk of credentialing and badging, like, are you so I'm just curious. Like especially for career services, are you seeing more of that, more of it from the student, More of it from the employer wanting to see it. Because it strikes me that badging and that kind of like newer credentialing is filling a gap as we move from a knowledge to a skill mindset. So interesting that you should ask. We have an employer advisory committee meeting coming up next Thursday. That's actually one of our questions. So one of our team members pose that. Let's ask, because again, there's the big picture. And then there's what are the employers doing that recruit our students? So we will be asking that actually eight of some of the top employees in the region, eight to nine next week. Where does badging stand in terms of recruiting and hiring students? So I have to give a shout out to our team for hacking question. And we're adding that to the list so we'll report back what they're saying. The other thing that was interesting, I was on a webinar and I'm drawing a complete blank on the president of the institution. But they were talking about, there was a lot of talk about Google, and they were hiring all of these entry level roles, but they didn't require the degree, right? So they were hiring them with their credentials and with the certifications. I just thought it was interesting that the actual stat was maybe 22 2021. Out of the 30,000 people that they hired, were those 300 were ones that just had the certifications in the badging. So there's a lot of talk about we won't need degrees, we won't need degree. But then what it actually comes down to right now, the actual hiring, there's still a huge gap there. So Yeah. But we will certainly provide some feedback about the credential and the badging. The one thing I'll add is, I think even when I was a student studying lifelong learning, it was a wild West back then and it still persisted as a wild West. The whole badging in terms of other potentials that are maybe not as industry recognized. And there are a lot of massively open online courses, there are a lot of things, I don't know if anybody has taken them. Their quality level varies quite a bit. I think this is why employers are probably, I'm just guessing they're probably grasping at straws a little bit because one person could have a really great learning experience through a badging or credential program. And others could just be like click, click, click, and you're done. But you can't click, Click your way through a class, which is why I, but I think, you know, I think it's not either or. Right. Yeah, right. It's both in this case. And took kind of along those same lines, do you see our students having or needing the, like a new vocabulary to pinch themselves successfully on this job market, right? Because you're talking about them needing to represent themselves in newer ways and skills based ways. Do they know how to say that? Do you help with that? I just feel like that must be a real difference between like my generation and theirs. I think we do help them with that. And part of it really is just them understanding that they're learning a lot more than they realize. And that they can make a lot more connections than they typically think of when they're just sitting in the classroom. And I think that speaks to what Stephanie was saying earlier about they're so focused on getting the grade, they're not necessarily thinking on the process. And so when they meet with us and they're trying to prep or taking one of our canvas modules, because we have a whole canvas site which is just going to give a plug for our campus, that it's a self based module based learning guide for students to go into, that all undergraduates have. It teaches them how to think about who they are and it actually will help them understand what is the language that I need to intelligently articulate that to an employer. Because they are learning, they have the language. They just they haven't accessed it yet because they haven't really needed to for the classroom, they needed to prove that they knew something. They need to translate how they knew that, how they learned that. And that's where using our resources can help them make those connections. And I think to a second part of that, it depends. So in terms of technology or technical skills, certainly there probably needs to be increased experiences and learning around certain technology and then the ability to translate that in the interviewer on the resume. So absolutely, yes, and then I just wanted to throw that out there, that there is another component to that as well. But a lot of it is around translating your experiences in your learning into the interview, on the resume, and networking. And actually I want to plug that last bullet course work was life work, help students. That was a presentation that the UD Career Center did in conjunction with Tall. And I do believe that the handout or the Powerpoint is still available, but it really help help faculty think about how to help students connect the dots between what they're doing in the classroom and how that's going to translate in the world of work. I have a question that builds on that. I was really interested in your discussion of cocoa and handshake. I made me think about, no, I'm not studying this, so this could be way out of date. But, you know, I have read that there are gender differences between what we have seen in terms of how people represent themselves, right? So what I remember reading years ago is that a woman may be less likely to apply for a job that may be just the tiniest bit of a stretch. She's not entirely 100% qualified, so I'm always really interested in the possibility that these kinds of tools could be a democratizing force in some of these ways. Of course, it could go the other way too, and be much more narrowly focusing. I wonder what kinds of things you all are curious about with cocoa and other systems like that that are feeding through an algorithm. These options to students or those who are job seekers. Yes, I think as we learn and see it in action 100% there's the bias and position descriptions, right? Just even the way that they're written. Sometimes you can literally pull out and see whether it's focusing on a specific gender or more attractive. But it calls out that level of bias. Yes, I think the answer is, we are really interested in that handshake. One of their, the phrases that they use all the time is democratizing access. It will be really interesting to see a evolved that looks like, yeah, I got to believe cocoa will be really trained by human users before they launch. I mean, it just seems like it's specifically designed to open up possibility, not to mitigate by exactly exactly they're using pilot now. They're using check GPT 4.0 and some mare that they're using to help as the baseline for it. Yes, it's actually it's a pilot. We're not a pilot. I wish. Yeah, those are great question. We are at time. So please join me in thanking our presenters.
AI-Powered Career Advancement: Navigating Career Preparation, Recruitment, and Lifelong Learning
From Margaret Grotti March 18, 2024
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