AI In The Classroom
Maria |
March 28, 2024

In the latest Business Casual,  the hosts dive into the transformative role of artificial intelligence (AI) in education with Professor Rajiv Garg from Emory University’s Goizueta Business School.

Professor Garg shares compelling insights from his study examining the effectiveness of AI in enhancing learning outcomes. The research intriguingly reveals that courses designed with human-generated content but delivered by AI avatars lead to the most successful student learning experiences. This nuanced finding opens up a discussion on the future of education, where AI could play a significant role in personalizing and delivering content, while human educators focus on content creation and the cultivation of critical thinking and creativity.

The conversation also explores the broader implications of AI in academia and the potential for a symbiotic relationship between AI and educators to foster a more engaging and effective learning environment. This episode offers a thought-provoking look at the intersection of technology and education, suggesting a future where AI supports rather than supplants the human touch in teaching.

 

 

 

 

Episode Transcript

[00:00:04.370] – John

Well, hello, everyone. This is John Byrne with Poets and Quants. Welcome to Business Casual, our weekly podcast. We have a special guest today with my co-host, Maria Wich-Vila and Caroline Diarte Edwards. He is a professor at Emory University’s Goizueta Business School, and he’s done a recent study on artificial intelligence. Now, I don’t need to tell you that AI is odd. Everyone is trying to figure out how is it really going to have an impact on education and in every single way, meaning how should students use it? How should faculty use it? Can it be used in research when it’s used in the classroom? To what effect will it occur? Rajiv Garg, the professor at Emory, has done an interesting study. We wrote about this. Very cool story. You want to check it out on our site. It’s called When AI Helps Students Learn and When It Doesn’t. An Emory professor’s ground A Ground-Breaking Study. Welcome.

[00:01:02.560] – Rajiv

Thank you, John. Thank you. That’s great. I don’t think it’s a groundbreaking, but it’s just- Yeah, we think it’s groundbreaking.

[00:01:09.530] – John

Tell us what you did. Lay it out and tell us how you came to do this study.

[00:01:15.120] – Rajiv

I guess I started the study trying to prove that I should save my job. The alternative AI has gotten really… We are seeing applications in all kinds of domain: education, marketing, advertising, even the content writing. I have literally research projects in almost all of those domains I’m talking about. But what we really wanted to see is because the AI, while it’s exciting, it could be a little blunt. The results could be planned, the delivery could be planned. We wanted to compare that the way the generative AI systems are right now, could they really help in the learnings of the students? When we talk as humans, we can modulate our voices, we can actually communicate better, we can emphasize in some points, we can make things a little bit more in the layman terms rather than making it more sophisticated. The generative AI, you can change the temperature, which is essentially how creative the content is going to be, but it doesn’t always do a very good job at keeping the content factual, but making it more in a layman term at the same time. It’s essentially the factual is more formal, which is maybe writing or reading a research paper.

[00:02:34.360] – Rajiv

Now, if you teach students as if you’re reading a research paper to them, the hypothesis was they’re probably not going to learn as well as if you were talking to them as a human person who can take the same content but simplify in a way that would be easily comprehensible. What we started doing was, I said, Look, the two systems or forces that I have to create, there has to be no talking, no spillover between them. I have to create one instructor or have an instructor who’s going to create the content on her own. This person has to be knowledgeable. I hired a student who is a graduate of the master’s degree in analytics, who has taken the database and machine learning and all kinds of courses. I said, Look, you got to create an intro to sequel course. I’m going to give you the six different topics for six modules that we’re going to talk about. Now, the six topics that we came up with is asking ChatGPT saying, what would be the six different modules you will talk about if you were to create a course on introduction to SQL? ChatGPT came up with six different topics.

[00:03:52.030] – Rajiv

We tweaked them a little bit. We asked them the question, Okay, you need to simplify this. This is too much content, et cetera. We I came up with a single prompt that gave us a simplified six topics that ChatGPT could cover for a one-hour course. Now, I gave these topics to the human instructor and said, Go ahead, create a script on what you would talk, what your slides will be, and I will go over what you’re doing or delivering in that course. I hired another student to essentially create prompts that are essentially standardized. We are not doing a multi-shot. We are doing a zero or a single-shot prompt where we are saying for an intro to sequel course, when talking about this module, what will be the content you will cover? More specifically, can you write a script for 10 minutes? Create the slide content for 10 slides. We provided all the information necessary to make the course structure very similar. Once we had the two courses created, the initial two, which is purely generated by AI, purely generated by human, and this is just the content. We thought, Okay, we can have the AI deliver it, and we can have the human deliver it.

[00:05:08.320] – Rajiv

But what if the human delivery is better? Can we show human delivery is better with the AI content? This is the same human being, same instructor, but not delivering AI content. Can they do a better job compared to just AI delivery? We ended up creating four different courses. The AI-generated course with AI instructor, which is essentially an AI avatar with their own, the text to voice for a speech in there, and a video for essentially the slides with that avatar. The second was the AI content with the human instructor. The human sat in front of the camera, recorded their avatar and spoke, like it literally taught, that slides that the AI created. Then this instructor taught the human generated course, and then we had the same AI avatar teach the human generated course. We ended We ended up having four courses. Then we hired students, randomly assigned a course to each of them. After every module we had, because the module was a similar module across both the courses, we gave them the same quiz to those two different students and said, Look, let’s see what your scores are going to be. We didn’t tell them, and the students didn’t know that any of the course was an AI-generated course.

[00:06:25.530] – Rajiv

We told them, Here are some online courses that we are evaluating effectiveness. That’s what we told the students. After the study, when some students, I met with them and I asked them, What did you find interesting about the course? They said, Oh, this is a very good learning experience. I I was like, Did you know this was created by AI? I said, No, this is so amazing. But at least by not sharing, and the AI was so close to the human that they didn’t have the wow factor that we were initially thinking with the hologram for technology.

[00:07:03.810] – John

The best learning outcomes occurred in which group, though?

[00:07:07.370] – Rajiv

The best learning outcome was the human generated content with the AI delivery. When we had the AI avatar deliver the whole slide and followed the script for teaching what the human generated. The worst was, interestingly, was the AI generated content delivered by human. There are multiple things that we try to reason why. Again, these are some sample points we found. Some students said they actually were listening at the content at the 1.5xp. At 1.5x, I tried listening to the human versus AI, and AI is more comprehensible than the human. When we are speaking, because we’re essentially recording from a microphone, there’s some noise as well. When you speed it up, it’s not as perfect. We need a better maybe microphone, a better speaker who is slow and is able to communicate more effectively. AI, on the other hand, is system generated. There’s no noise. If they’re listening at 1.5x, they can understand. I was actually surprised that students are doing or taking courses at 1.5, 1.25x speeds and still understand the content. This is something I thought maybe if I do the next study, I need to ask in a post-survey, like the E4 survey, that you listen at a higher speed, because they did.

[00:08:38.630] – Rajiv

That could impact their learning as well.

[00:08:41.580] – John

How vulnerable do you now feel as a professor Having conducted this experiment, do you think you’re going to have a job in five years?

[00:08:48.920] – Rajiv

I think, based on my study, I will because we need somebody to create the content, right? I think what I learned is AI is phenomenal in personalizing the content for us. Even if I was a person who is delivering, I can create my own slides. Assuming I created a course today, I have my whole 27 lectures, or sorry, about 27, 28 lectures, and I put it to a ChatGPT and say, Hey, wherever I’m taking case study examples, tweak it for this audience. We can do that. I can actually go deliver the course to master students with the examples of case studies they could understand. I can take the same course material, the slides, the content, and I can customize it for the undergraduate course. Students may be in arts, may be in engineering, may be in business. I can dynamically or using generative AI change the content if I want to deliver. Alternatively, because I created this content, I can have the AI deliver and personalized for the audience as well. I think the job, our job, is going to be creating knowledge. I think AI is phenomenal in creating the patterns in text and videos and audio based on what they have seen in the past.

[00:10:21.200] – Rajiv

But they’re good at communication, but they’re not good at creating knowledge, creating awareness as much. We’re going to realize that. Maybe How did it get better. Maybe if you ask me this question a year from today and say, Do you fear for your job? Maybe, right? At that time. But today, no. I think we can still create, I think, better content for learning and for knowledge diffusion. Yes.

[00:10:52.850] – Caroline

That’s what I was going to ask you, Rajiv. Don’t you feel like this is a temporary advantage that professors have? I have a I’m interested to read John’s article about this, and you talk about how in the future professors will be content creators and the AI will be delivering. But you also talk about how this is changing week by week, month by month, right? So Maybe this is just a temporary advantage that professors have over the AI. In another year or two years, that balance of power will have shifted. I wanted to ask you about that. Then also, do you think, therefore, that there there will be need for fewer professors in the future? Maybe there will be a few guru professors who are brilliant and have an amazing reputation and can still bring that extra input that AI cannot bring. And the AI will leverage their knowledge, and you won’t need as many people actually involved in teaching at universities or schools. It seems like a very concerning potential.

[00:12:00.370] – Rajiv

I think your questions are awesome. I’m going to answer this in two parts. There are two kinds of learnings that we do. One is essentially a skill that we are gaining. Now, if you’re taking courses that could be learned online, I completely agree with you that the need for professors who are creating online content is going to go down because essentially you can have one very talented person create a content, and that could be to personalize in different settings for different audience for the digital delivery of the content. The second part, what we’re going to see is as these things become more advanced. There was an article, I can’t remember the source right now. It’s in one of my papers where we say that the 70% of the jobs will be eliminated in 10 years, sorry, next six years. But 85% of the jobs that will exist are not even invented yet. They It will be these jobs that are needing the invention that will require some complex content to be taught in the classroom, which will require more human beings. Like you said, rightly put, that the sensory element is very critical. A human professor can look into the eye of every student, can determine, are they getting the content or not, where to repeat, where to slow down, where to speed up.

[00:13:28.670] – Rajiv

The technology for AI doesn’t exist yet. It could exist. Maybe that is the next step for AI and education. Over the next year, you have a camera. Literally everybody has a camera looking at them. Now, a professor creates a content, a digital content. They look at the student and you detect that they’re becoming sleepy, they’re becoming distracted, and I can slow down and I can say, Hey, Caroline, do you have any questions? And on the fly. Those things will happen. But as we keep creating this content, we probably will have a more complex content that requires a more personal touch. Now, can AI deliver for that personal touch with that complex content? I don’t know the answer to that yet. We are getting there. We will get there in next year or in five years. That’s a very good question on what we keep innovating over the next month. But you’re right. For digital delivery, for the content that is more skill-based, that is upscaling people’s portfolio, we will see the need for faculty will go down in those settings as we adopt more AI. But the need for faculty or humans in delivering more complex content in the real-world setting in person is going to increase over time.

[00:15:00.340] – John

You would think that it’s most applicable, obviously, for online learning, and less so for in-person learning for a number of these reasons. You mentioned earlier, for example, that when you’re standing in the classroom looking at students, you can tell who’s getting and who’s not. You can tell by their body language who you want to call. You know the backgrounds of your students. If you wanted someone who had a background in marketing, and it was a marketing twist a finance question, you’d call on the marketer. AI really, I don’t even think in other iterations, will be easily able to do that, frankly. The other issue you have is people who are in person are paying very high tuition rates, and there is an expectation that they don’t want to be taught by an algorithm, right? Absolutely.

[00:15:57.600] – Rajiv

Yeah. No, you’re John. Again, the two things that you mentioned, one is the cost. Definitely, if AI is teaching me and the AI is becoming a commodity, then yes, it’s not worth the $3,000 for the course or $2,500 for the course that we are paying for higher education right now. If it is not a commodity, if a university does something unique which is proprietary in personalizing the content for the student, where they’re able to learn from this esteemed faculty, which otherwise they will not get an opportunity to learn from, and this professor’s avatar is being personalized for them, then maybe it’s worth the cost. Again, but the cost is an issue which I can’t really say much about. But I understand that I personally, if I were to learn a digital content, which which is recorded, I probably wouldn’t pay the $2,500 for that one course if it’s delivered online. I’m more willing to pay if there’s a person, if you, John, were to teach and say, Look, Rajiv, I’m going to teach this course. You want to join? The tuition is $2,500. I will probably join.

[00:17:16.270] – John

If I can download all of your expertise and your experience into a proprietary generative AI system, and then I ask it questions that it still can’t answer, it probably will hallucinate an answer for me that will be totally incorrect, don’t you? At this point, it will, right?

[00:17:39.260] – Rajiv

Yes. There are ways to actually talk about, so there are ways to reduce the hallucination You can bound the AI’s response to what I talk about, my slide content, my books, et cetera. You can limit it. That is one area which I can almost guarantee that you’re going to see the the amount of hallucination going down significantly or by almost 90% within this year, because that’s what everybody’s focus is. I ran a workshop last week on large language models, and that was one of the things that one hands-on session we did on reducing hallucination, and people were like, This is awesome. We could actually reduce the hallucination, which is such a big problem. I mean, even if you ask ChatGPT, What is a reference for this content? They’re going to make up an article. They make up a publication completely.

[00:18:33.770] – John

Yes. It is amazing, though. One little experiment that I tried earlier on was asking ChatGPT for to write an essay for Stanford Business School. They have one of these iconic essays, What Matters Most to You and Why. I said, I have a great passion in sustainability, so write the essay for me and write it the way that Hemingway would write. Then I asked it to write it in the way that F. Scott Fitzgerald would write, and in fact, it did. I see. It is remarkable. It’s really… Can you see yourself using this as a research tool as a faculty member?

[00:19:21.610] – Rajiv

So I’m interested in you bring this up. I’m with another faculty member, Jessie Boxer, at the Goizueta. We are working on research where you give a topic, what you want to research on, and we will write you a whole paper, a research paper with results, with analysis, everything in 10 minutes. The whole purpose of this exercise of this research is to educate the community that the generative AI’s hallucination could be used for this bad use. I mean, if If I were to say that the increased use, again, this is fake, don’t quote it, but if increased use of generative AI is going to cause climate change, and I want to write a research paper on it with data, with the analysis properly done and all the charts and literature review, abstract, everything, I can write the whole paper in 10 minutes right now. Would you believe it? We are seeing the fake content in terms of the YouTube and TikTok and Instagram places or news articles. But we’re going to see the research articles as fake moving forward. It’s a problem. How do you control that fake information moving forward? The responsibility on editors is going to be increasing so much.

[00:20:54.860] – Rajiv

I mean, you have points and points. If you were to hire a freelancer to write an article and the person just ChatGPT to write the whole thing, how would you know? It’s very well written. Like you said, maybe you’re in the style of Hemingway, and it’s like, This is amazing.

[00:21:15.540] – John

Oh, that’s terrible.

[00:21:18.550] – Caroline

That seems like an opportunity for the universities, though, that you can be the gatekeepers of knowledge and provide credibility courses and to sources, right? And in this environment where there are a lot of threats to the education industry, that seems like something where you have a tremendous opportunity to play a role in the future.

[00:21:48.980] – Rajiv

Caroline, you just invented another academic job, the gatekeeper of knowledge. Technically, you have professors who would gatekeep the courses that are being created, the articles that are being published, not just the editors and the viewers, but there are people who understand the technology, understand how to interpret the text, whatever you are creating. And is it really novel that a person has done, or is it something, a collection of next predicted word using large language models done by somebody? So definitely that is going to be a new job in the academic institutions.

[00:22:34.320] – John

Now, Rajiv, Caroline has an MBA from INSEAD. Maria has an MBA from Harvard. I’m going to ask them if enrolling in an MBA program today, would they like to be taught by an algorithm? Maria?

[00:22:50.970] – Maria

I mean, if it costs a lot less, sure. Oh, they’re price sensitive. That’s right. I’m a I’m a bargain hunter. I think, look, if the fundamental knowledge is sound, if it’s not hallucinating, and if the content itself is of high quality, then whether it’s an avatar of a professor teaching or giving a particular lecture, for example, or the actual person, I don’t know that I’m super… I don’t really care one way or the other as long as the knowledge is being imparted. But I do think that some of the best learning in business schools actually comes from dialog in between students and from students and professors. I’m not really sure. Professor Garg was making the point that if you’re teaching a skill, that’s one thing. But if you’re trying to do higher-level thinking or higher-level those light-bulb moments in someone’s head for more complex concepts, I’m not sure that the AI would be quite there yet.

[00:23:52.460] – John

I can’t see an algorithm orchestrating a case study discussion. I just don’t see it.

[00:23:59.220] – Maria

That would be really That’s going to be ChatGPT 5.

[00:24:02.380] – Rajiv

I’m on it. I am working on it right now for that personalization, and hopefully I’ll show you. It’s not that much. It’s going to happen. It’s not that much. Really? It’s going to happen. I can show you a prototype in the next month. But it’s going to happen. We’re getting there.

[00:24:21.310] – Maria

It would be interesting if the AI could actually teach professors how to become better professors even when they’re in person. One of the things that you mentioned was that one of the things that made the AI delivery or one of your hypotheses around why the AI delivery was more effective was that it was clearer. There was no accent. I’ve started playing around with some editing software for the videos that I create where it will go through and it will eliminate all of my ums and my likes and my you know’s. It’s still pretty buggy, but I can envision a place where eventually, maybe it is a live professor, but AI catches… It becomes almost like a hybrid. The AI becomes instead of a replacement for the professor, almost like a little assistant that pops up and it says something like, Hey, you know that 33% of the students have tuned out. The eyeballs are not paying attention to you, things like that, or, You should probably restate that in a different way, or, Let’s scrub out that accent that people from other countries might not fully understand. I mean, I almost wonder. I’m sure that it would probably just leapfrog, and I’m just being overly optimistic about the future of the professor.

[00:25:36.280] – Rajiv

Maria, you’re on the spot. We actually at Goizueta have what we call global classroom, where for online learning, we even see, we have the technology to detect the student’s attention. If students are paying attention, if their eyes are closed, et cetera, so as a professor on the screen, I can see signals of those things. If I see multiple students not paying attention or their eyes closed or something, I can then talk to those people directly, and I can do that in a digital setting. In terms of voice that you mentioned, so I actually have another research paper where we look at the effectiveness of voice. We do show that there are certain voices that are actually better for information-seeking behavior that will create the need for engaging with the technology as well. We actually analyzed some thousand voices. We did some experiments. The paper is online, but we created six buckets or clusters of voices, and we said, Okay, this cluster with female voice is actually the best for information-seeking behavior, to create information-seeking behavior in people. Whereas the certain other bucket with male voice is actually better for selling products to users. What you were saying is already happening right now.

[00:27:04.960] – Maria

Holy smoke. Okay.

[00:27:06.570] – Rajiv

I actually have to ask Maria. When you mention about it teaches professor, you probably are thinking of some professor you didn’t like in the business school.

[00:27:16.790] – Maria

No comment. No comment. I do not want to be. No, but I definitely… Who hasn’t had a professor in their lives or even a boss or a colleague where their communication style just isn’t quite hitting for you or things just aren’t gelling. I think we’ve all had experiences with that. Wouldn’t it be great if the AI, instead of replacing it, it doesn’t have to be a binary thing. It doesn’t have to be zero or 100%. There may be some way to layer on AI in a way that helps superpower or turbocharge. True.

[00:27:49.460] – Rajiv

But think about it, if I’m talking, if I’m teaching, and you hate my voice, if that’s the feedback, I’m just saying, I know you love my voice. I’m sorry.

[00:27:59.590] – Maria

I I do. We all do here at Poets and Quants.

[00:28:02.280] – Rajiv

But maybe you love the voice of Tom Hanks better. I am teaching in the real-time. We can change the voice in Tom Hanks’ voice, and maybe that’ll keep you more engaged. So what I was saying, the value of AI is that delivery to connect to people. My own research, which talks about different voices based on the delivery itself. During the delivery, I can change the voice of the avatar to whatever I want, and I can personalize it to every person. Mf4, John, maybe Morgan Freeman, for you, Tom Hanks. I can pick any different voice. It’s the same professor teaching, but in different voices. Will that be more effective? My hypothesis is yes. That’s why the AI delivery is going to Trump the human delivery for these skill-based or more digital content. Like you said, the interaction that A light bulb moment happening digitally is harder. But then you need people who can connect better in their class. They need to be educated, trained. There’s one saying that says, Really smart professors are horrible teachers. Really good teachers are horrible professors. How do you find that balance? Maybe technology can help create that connection that we can have really good professors become really good teachers.

[00:29:28.490] – John

Yeah, really good point. I don’t know if I should be happy that I’m toward the end of my career or sad because of all these exciting changes that are about to come. Somehow, I think the former…

[00:29:42.990] – Rajiv

No, you should be sad. Yes. Yes, indeed. You would love to continue this career for another two decades.

[00:29:50.590] – John

Of course. It’s going to transform what we do and how we do it. Hopefully, it will free us from the more mundane things that we know we have to do that’s part of the daily grind and allow us the time to be more creative and more thoughtful and more innovative about what we do, right? I mean, ultimately, that’s the hope. That’s true. Other than the shorter work week, or what have you. I think that’s the real pipe dream in America. But who knows what can happen.

[00:30:21.730] – Rajiv

I think the AI has open opportunities, like you were saying, to do more creative. I think when we are creative, we are more If you’re happy, we look forward to the Monday, we hate the Friday, that look, I may not be as creative this weekend. I probably have to fix the shed in the back of my house this weekend, but I’d like to create something new That’s exciting, right?

[00:30:46.990] – John

That’s right. Well, the robot might be able to do those household chores for you in the future, right? I mean, already, it can vacuum a floor and do a lot of other things for you, so why not fix a shed?

[00:31:02.090] – Rajiv

Yeah.

[00:31:02.390] – John

Rajiv, thank you so much for being with us today, and we’ll look forward to your other studies on this topic.

[00:31:09.620] – Rajiv

Thank you, John.

[00:31:10.730] – John

It’s been an interesting discussion. I think everybody We’re talking about AI, and not only its immediate applications, but how it’s going to morph into something even more meaningful in the near future. People are afraid of it. People wonder if it will be regulated. People are wondering who the leaders will be and what overall the implications will be for society, never mind just higher education. Whatever it’s going to be, it’s a big challenge for everybody involved. Rajiv, thank you so much for joining us. And shedding so much.

[00:31:46.500] – Rajiv

Thank you, John.

[00:31:47.500] – John

yes. Thank you for joining us. And we hope you’re excited by the changes that AI is about to bring, and not like me, Happy that I’m toward the end of my career and I don’t have to deal with this stuff.

[00:32:05.840] – Caroline

John, we’re never going to let you retire.

[00:32:08.810] – John

No, I’m just trying. You know what? I really don’t want to retire anyway.

[00:32:12.720] – Maria

We’re going to upload your consciousness to a hard drive. It’s going to be fine. Don’t worry.

[00:32:17.130] – John

Who wants to listen to me? I’m thinking if you can do any voice you want, maybe some people want Marilyn Monroe’s voice singing to JFK, Happy birthday.

[00:32:28.160] – Maria

That’s right. That’s how you do a search in the sequel database with Marilyn Monroe’s breathy. You’ve unlocked it, Dawn. That’s the billion-dollar idea right there.

[00:32:41.070] – John

All right, everyone out there, thank you for listening. You’ve been listening to Business Casual, and our professor here from Emory, Goizueta Rajiv Garg. Thank you so much.

AI In The Classroom
Maria |
March 28, 2024

[00:00:00] John Byrne: Well hello everyone, this is John Byrne with Poets and Quants, welcome to Business Casual, our weekly podcast with my co-hosts Maria Wich-Vila and Caroline Diarte Edwards. Today we have a special guest, Heidi Hillis from Fortuna Admissions. She is based in Australia, is a senior expert coach for Fortuna, and has three degrees, all from Stanford, a BA in English literature, that’s my degree, an MA in Russian studies, and an MBA from the Graduate School of Business. And we have Heidi here to discuss some really fascinating research. Here’s what Fortuna did. They dug into the last Two class profiles of the Stanford Graduate School of Business.

That’s the class of ‘23 and the class of ‘24. They looked up all these folks on LinkedIn to identify a little bit more about their backgrounds, including their former employers and their places of undergraduate education to come up with an incredible analysis. Heidi, welcome.

[00:00:46] Heidi Hillis: Thank you. I’m glad to be here.

[00:00:48] John Byrne: Heidi, what is, what are the big takeaways from your deep dive discovery?

[00:00:54] Heidi Hillis: It’s hard to know even where to start. I think there’s a quite a few interesting kind of trends that we’ve seen that have taken place over the years. We were mentioning before the call that traditionally there hadn’t been, 10 years ago, if you’d looked, you wouldn’t have seen so many tech companies represented, but now there’s a big presence of tech companies who are feeding a lot of these MBA programs in Stanford in particular.

I think that the thing that was really interesting was, looking, not just at where the companies that were feeding the students, the applicants to Stanford. When they were working there, when they were applying, but actually the paths that they took prior to their current job.

So how many people were working, if you look at McKinsey, for example, or Bain and BCG, those are obviously companies that feed a lot of applicants to the program, but we found 20%, which seemed to be normal of, the class came from consulting, but if you actually look into the numbers in their background, You would see that actually 37 percent of these two classes had worked at McKinsey sometime prior, or actually in consulting, so it was, it’s The kind of the patterns that are behind, what you would normally see in terms of what Stanford tells us.

So you get a sense of the paths that people have taken. And so that’s something that was really interesting to see.

[00:02:16] John Byrne: Absolutely. And of course, this is this analysis goes so far beyond what any applicant would learn by simply looking at the class profile that the school up because, this level of detail is never available to people.

[00:02:33] Heidi Hillis: No, and yeah, for example, you could see that, Stanford will say that they have around, each year around 50 percent of applicants are international, which is a great statistic and gives you lots of hope if you are an international student. But when you dig into the numbers, you actually understand that.

75 percent of the people who get into Stanford actually went to a U. S. University. So even if you’re international, it does have does seem to have kind of an advantage of having been educated in the U. S. That seems to be something that they look for. However, I think. The concentration of universities in the U.

S. that are feeding to Stanford is something also that, if you’re looking at it, you might find a little bit dis, disconcerting. There’s a few programs that are really, obviously the top. Programs as you would expect places like Harvard, Stanford, Yale, the Ivies but if you look at the international universities very diverse from all over the world, really lots of people from different places, which is also really interesting.

[00:03:38] John Byrne: Yeah I tell you, one of the things that struck me in the data is how consistent it is. 10 years ago, we did the same exercise at Stanford and a bunch of other. Schools from Harvard and Dartmouth and Columbia and talk and a few others and back 10 years ago, we found that 25. 2 percent of the class of 2013 were from Ivy League colleges.

And the Ivy League 8 schools, not including Stanford. And if you included Stanford, it would have been 32. 6%. So now, let’s move forward to your data. And in 23, 30. 7 percent went to Ivy League schools, even above the 25. 2. And in 24, 27. 9 percent went to Ivy League schools. So it looks like Stanford has gotten even a little bit more elitist than it was.

Yeah,

[00:04:41] Heidi Hillis: It’s, it is it’s what the data says, right? Obviously, this is a sample. We have 80 percent of the two classes. So we don’t know where those other people went. And that might skew the data a little bit in another direction. But it is, if you look at there’s 15 schools, that include the Ivy’s and then you have UC Berkeley and obviously Stanford that really are contributing, 49 percent of the class of 23, 47. 3 percent of the class of 24. So that is a pretty heavy concentration and But, if you actually look into the data, you see a lot of people also, each of these is actually an individual story.

You see a lot of people who come from other schools as well. So it’s not like you have to give up hope if you come from a different school. I see a lot of individual stories that, from the whole range of U. S. schools that really are feeding into Stanford. So I think what the data doesn’t also tell you, unfortunately, is how many of these Of people from these backgrounds are actually applying.

So

[00:05:39] John Byrne: good point.

[00:05:40] Heidi Hillis: It’s it’s hard to know. And sometimes I think people this is. A path that a lot of people who go to these schools plan to take from the very beginning. So I would see, it would be interesting to know that I don’t know that we will ever find that out. But, um, that’s something to keep in mind as well.

[00:05:56] John Byrne: Yeah. And that’s a fair point. Because how reflective are these results of the applicant pool reflective of an elitist attitude probably a combination of if I had to guess, but, it is what it is, and these institutions obviously are great filters, so you come from McKinsey, Bain, BCG, and you go to Harvard or Stanford or Penn, and you pass through a fine filter, and it makes you less of a admissions risk than if you went to, frankly, the University of Kentucky and worked for a company that no one knows of.

That’s just the reality of elite MBA admissions, right?

[00:06:40] Heidi Hillis: Yeah. And so you will see that the people who are not going, you’ll see a lot of the people who you would, the profiles that you would expect, the Harvard undergrad that then goes to Goldman that then was working at a PE firm.

That’s a really typical profile that you’ll see. But you’ll also see some really, unique and interesting ones, which I think, Okay. Helps you understand that if you don’t have that path, you also have a real chance at these schools, and maybe even more of a chance, again, not knowing, how many of those Goldman P.

E. Harvard grads are applying. So I’m thinking of the guy that I saw who he went to UPenn undergrad, studied engineering, started out a kind of pretty typical path working in private equity, but then made a big pivot to work for go to Poland where he was working in a real estate investment firm and the head coach of the Polish lacrosse team.

So you have really interesting profiles like that, that you can see that. aren’t necessarily taking that typical path. And sometimes that really does help you stand out.

[00:07:42] John Byrne: True. Maria, what surprised you most about the data?

[00:07:48] Maria Wich-Vila: Wow. I think we already covered, the, one of the biggest ones was the number, the percentage of people who would had some sort of either their undergraduate or graduate education within the United States.

Intuitively, I had felt that was true. And sometimes when I try to, give some honest, tough love to applicants from certain countries, and they’ll say, oh, but Maria, I think you’re being a little too pessimistic. After all, X percent of the applicants at these schools are international, and Y percent are from a certain geography internationally.

I’ll say yes, but that doesn’t mean that they’re all Solely from that area. A lot of them are, do have significant international educational experiences. I think another, speaking of the international piece the percentage of people who had significant international work experience as well was something else that really jumped out at me.

Because it would signal to me that Stanford really does value this global perspective both within probably its domestic applicants and also its international applicants. So I thought that was also a really interesting piece of data that jumped out at me.

[00:08:52] John Byrne: Now remind me what percentage was that?

[00:08:56] Heidi Hillis: People who are international

[00:08:58] John Byrne: who have had international work experience.

[00:09:01] Heidi Hillis: I think it was 30%.

[00:09:02] Caroline Diarte Edwards: Yeah. Yeah. Yeah, it’s pretty

[00:09:04] John Byrne: impressive.

[00:09:04] Caroline Diarte Edwards: 30%, which I was thrilled to see. As well as coming from in Seattle and Europe. Obviously the international schools put a heavy emphasis on international experience and I hadn’t fully appreciated that. A school like Stanford would also.

really value that to the same extent. And it’s great to see that candidates are making the effort to get outside of the U. S. and get international experience because I think you gain so much from that exposure. And you bring more to the classroom if you’ve got that experience. I know that both Maria and Heidi.

I’ve worked outside of the home countries as well. Pre MBA and I think that you just have so much more to contribute to the whole experience. And it was great to see that 30%.

[00:09:50] John Byrne: What else struck you, Caroline?

[00:09:53] Caroline Diarte Edwards: We talked about the concentration of academic institutions, and I was also surprised about the concentration in employers.

So while there is a very long list of employers where the students have worked pre MBA when you dig into the career paths that they’ve taken there is some interesting concentration. Heidi had noted that the reports that There are 26 companies that account for nearly one third of the class in terms of where they were working right before Stanford.

But when you look at their whole career history, those same 26 companies represent over 60 percent of the class. So that is, yeah, that’s quite extraordinary that so many of the class have experience of working at quite a short list of companies.

[00:10:46] Heidi Hillis: I think that’s reflective of, if you really think about it, you have a lot of these companies.

You’re talking about the Goldmans and the Morgan Stanley and McKinsey that have really large programs that recruit out of undergrad that are really training grounds for. A lot of people that then on to do, work in industry or go on to work for in finance in particular, a lot of people starting out at some of these bulge bracket banks and then going into.

Private equity or smaller firms. So the diversity within finance in terms of where they were working prior to MBA is quite large compared to consulting because there just aren’t as many consulting firms, but a lot of people in financing, a lot of different firms, but they, a lot of them really do start out in these training programs, these analyst programs that are so big and popular.

[00:11:34] John Byrne: Yeah, true. And looking back, I did this exercise as well. The feeder companies to Stanford 10 years ago in the class of 2023, 22. 8 percent from McKinsey, Bain, BCG, and your data, 22. 5 percent work there. Incredible consistency over a 10 year period. When you look at the top six employers 10 years ago, they were McKinsey, BCG, Bain, Goldman, Morgan Stanley, and JP.

Morgan Chase. They accounted alone for 34 percent of all the students in the class of 20, 2013 at Stanford. In your data for 23 and 24 they account for 29. 8%, just a few percentage points less. So remarkable consistency. And I think you’re right, Heidi, this is a function of the fact that these firms bring in a lot of people who are analysts and actually expect them after 3 to 5 years to go to a top MBA school.

So there’s a good number of them in the applicant pool to choose from and let’s face it, they’re terrific candidates.

[00:12:46] Heidi Hillis: Yeah. I think another pool of really terrific candidates that you see, and I don’t know what the 2013 data was saying, but is the US military, which is really, I think, again, something that I felt having worked with lots of military candidates myself, understand that, Yeah, intuitively, I would have expected, but to see it in the data is actually really interesting.

You just see Stanford in particular, I think, is really looking for leadership potential, and it’s so hard to show that as an analyst, as a consultant, but as in the military, these people have such incredible leadership experience that it really helps them to stand out.

[00:13:23] John Byrne: Yeah. And let’s tell people what the data shows.

How many out of us military academies,

[00:13:28] Heidi Hillis: In all in total, we had, 20 over the two years. So that’s in the two classes that we found. So that’s, a pretty large number. And they come from all the different academies, right? So you’ll find them from different, not academies, in the army, navy and the marines.

So you’ll see that. And you also see quite a few, in the data we’ll, we see a lot from the Israeli military as well, but that’s actually a little bit difficult to because every Israeli does go into the military. So it’s they have that in their background. Any Israeli candidate would have Israeli military background as well, but again, that’s.

Place that people can really highlight their leadership. So you had eight people from who had been, who were Israeli and obviously had military experience where they were able to demonstrate significant impact and leadership prior to MBA.

[00:14:18] John Byrne: Yeah. In fact, 10 years ago, roughly 2%. of the class went to either West Point or the U.

S. Naval Academy. Good number of people actually from the military. Maria, any other observations?

[00:14:34] Maria Wich-Vila: Yeah, I was also surprised at the fact that within those top employers And when we look at the tech companies, it was Google and Facebook and Meta with a pretty large showing. Google was actually the fourth largest employer after the MBBs and, but then, I was expecting there to be an equal distribution amongst those famous large cap technology companies.

So I, I would have expected even representation amongst Google, Meta, Microsoft, Apple, Nvidia, Amazon, et cetera. And yet. Apple and Amazon only had one or two people each versus Google at 25. So I thought that was really fascinating and it makes me wonder if perhaps it’s a function of maybe Google and Meta might give their younger talent more opportunities to lead impactful projects, perhaps.

I’m just guessing here, but maybe Apple and Amazon perhaps are more hierarchical. And maybe don’t give their younger talent so many opportunities, but I was really surprised by that. I would have expected a much more even distribution amongst the those famous those famous tech companies.

[00:15:40] John Byrne: Yeah. You’re right. And I crunched the numbers on the percentages and Google took three and a half percent of the two classes and that’s better than Goldman, Morgan Stanley, JP Morgan Chase. Facebook had 2. 7 percent and Microsoft at 1. 5, and I was shocked at Amazon because, Amazon is widely known as the largest single recruiter of MBAs in the past five years.

At one point, they were recruiting a thousand MBAs a year, but in, in one sense, maybe Amazon quite doesn’t really have the prestige. For Stanford MBAs who might rather work elsewhere, I think that might be is, you look at the employment reports at a lot of the other schools and Amazon is number one at a number of schools and very low percentage of people from Amazon going to Stanford.

We don’t know, of course, how many. Leaving Stanford and going back to Amazon, but it can’t be that many.

[00:16:41] Heidi Hillis: I wonder if there’s something about just a proximity effect here. You have the plate, like the meta and Google just being so close to Stanford, maybe it just, attracts more people applying because they.

They’re almost on campus and maybe, just being Amazon all over the world and different places could be not attracting as many. I don’t know.

[00:17:03] John Byrne: Yeah, true. The other thing, the analysis shows, and this is what you also gather from the more public class profile is really the remarkable diversity of talent that a school like Stanford can attract year after year.

It is, it blows you away, really. The quality and the diversity of people despite the concentration of undergraduate degree holders or company employers, it’s it’s really mind boggling, isn’t it?

[00:17:33] Heidi Hillis: Yeah, they come from everywhere and really interesting paths and even the people I think that, have those kind of typical paths, you see a lot of diversity within them as well.

So I think, even if you’re coming from a Goldman or a McKinsey having lived in another country or gone to done a fellowship abroad or running a non profit on the side. These things are actually what helped them to stand out. But you do see some really interesting, I think, profiles, too, of people who’ve just done, you get a sense of what it would be like to be in the Stanford classroom.

People from really unique and different backgrounds. People who come from all different countries and lawyers, doctors people who have run, nonprofits in developing countries people running large programs for places like Heineken or Amazon too. But, it’s a real diversity of backgrounds.

[00:18:27] John Byrne: Now, Heidi, I wonder if one is an applicant. Is this discouraging to read and here’s why if I’m not from Harvard, Stanford, Penn, Columbia, Brown, Cornell, Dartmouth, and if I didn’t work for McKinsey, Bain, BCG, Goldman, Google am I at a disadvantage and should I even try? Some people look at the data and come away with that conclusion.

[00:18:52] Heidi Hillis: I think it’s a reality check for a lot of people. I think it’s just, it’s really, it just helps people understand, what it, the difficulty of this, why it’s so competitive, but I think that there is, again, behind the kind of the percentages, you do look at these individual profiles and I would get, I would actually take a lot of hope from it if I were looking, as an applicant, because especially if you are.

Maybe a little bit more of a big fish or small fish in a bigger pond or big fish in a smaller pond you go to Rice or you go to Purdue or, and you do really well, those are the people who, they’re definitely looking for that diversity of background as well as the international.

I think that’s really neat. think that, instead of looking at the data and saying, why not, why I shouldn’t even apply, it’s why not me look at these other profiles of people who have taken really unique paths that that do get in. So I think it is actually a Kind of a mix of both, it is a reality check for a lot of people, but it’s actually, there is so much diversity in the data as well.

I think also one thing that we haven’t really covered is about is just the prevalence of social impact in, that’s really taken hold of the class. I don’t, again, going back to your 2013 analysis, I’m not sure how easy it was to tell that, but a lot of you can see reflected in the both the types of organizations people are working for, but also their titles and the kinds of work that they’re doing that that there’s a huge 40 percent of the class of the two classes had some kind of social impact in their background.

Whether that’s, running their own nonprofit on the side or volunteering or. Running trans transformational kind of programs within companies that are, either in finance or consulting or in industry. That’s a big trend. I think that people can take heart from as well.

So if you’re working if you feel like you’re in an organization where you’re not getting the leadership that you. can use to highlight your potential for Stanford, that’s definitely a place you can go is working for in volunteer capacity for a non profit or on the board of a of some kind of foundation.

Those are the kinds of places that you can highlight your potential

[00:21:00] John Byrne: true. And I know we have a overrepresented part of every applicant pool at an elite business school are software engineers from India. And I wonder in your analysis, how many of them did you find from like the IITs?

[00:21:18] Heidi Hillis: That’s a good question. The IITs, it was again, it was one of these you have about 50 percent of classes internet, so 25 percent of the class. was educated outside of the US. The IITs are going to be up there. Let’s see from India, 2. 1 percent of the class came from India. So probably, I don’t know offhand exactly how many of those were IITs, but

[00:21:43] John Byrne: I’ve had a lot of them.

[00:21:45] Heidi Hillis: Yeah, probably a lot of them. Although I think, that’s the other thing is that people who come, to work with me from India, they feel like if they haven’t gone to IIT, then that’s going to be a disadvantage. But I think, you’ll find that there are, there’s representation of other universities as well.

Definitely.

[00:22:00] Caroline Diarte Edwards: Yeah, I was just looking at the list of undergrad institutions. And for example, you’ve got Osmania University from Hyderabad. So it is not, it’s not all IIT. Okay.

[00:22:12] John Byrne: Yeah, exactly. And Caroline, 1 of the things about the institutions that are really represented here and that I don’t really see unless I missed it.

I didn’t see a Cambridge or an Oxford. Two of the best five universities in the world. And I wonder if that’s just a function of fewer people in the applicant pool or what? What do you think that could be about?

[00:22:36] Caroline Diarte Edwards: I had a look through the uk Institutions and you have got cambridge in there.

I think I also noticed. Bristol university there are a few different universities. So i’m aston university, which is not it’s not on a par with Oxford or Cambridge. So I think that speaks to the point that Heidi made that you don’t have to have been to an elite school to get into Stanford.

Aston is a good solid university, nothing wrong with Aston, but it’s not it’s not one of the top UK universities. So there’s definitely some interesting variety in the educational backgrounds of the students going to Stanford. And

[00:23:16] John Byrne: then, yeah, it is if you’re a big fish in a small pond, like Afton, you’ll you could still stand out in the pool.

[00:23:26] Heidi Hillis: Absolutely. There’s a lot of really interesting background, you have look hard on blue and you have Miami University and some really smaller universities abroad. I think. Again, it’s really, if you look at that, it does give you hope because it’s really what you do afterwards and if you, obviously, if you come from one of these schools, you probably want to be in the top, 5 percent of the graduating class, you want to show that you have the GPA that can support an academic background that they feel comfortable that you’ll be able to compete academically, but, and maybe that’s what you’re Offset by the, the GMA or the scores, you don’t know, we don’t have those on here.

But, um, the path post university really becomes much more important in those cases. What you’ve done since then where you’ve, how you’ve risen from starting at a entry level position to, running a division or heading a country group or something like that.

[00:24:21] John Byrne: And as far as Cordon Bleu goes, every good business program needs a Cordon Bleu, for God’s sake, right?

You want to eat well at those NBA parties, don’t you?

[00:24:32] Heidi Hillis: Absolutely.

[00:24:35] John Byrne: Maria, I’m sure that was true at Harvard.

[00:24:38] Maria Wich-Vila: I wasn’t the one doing the cooking but I certainly, I was certainly a member of the wine and cuisine society where I happily participated in the eating and consuming a part of that.

But to, to the point that we were just recently talking about. regarding being a big fish in a small pond. Not only have I seen it personally with applicants that I’ve worked with who did not attend these elite universities, but even many years ago, I attended a, an admissions conference where Kirsten Moss, who was the former head of admissions at Stanford, she actually told stories about how they’ve accepted people who even attended community college.

But within the context of that community college, they had really moved mountains. And she said that one of the things that they look for is, Within the context and the opportunities that you’ve been given, how much impact have you had? So maybe you don’t have an opportunity to go to Yale or MIT or IIT for your undergraduate, but whatever opportunity you have been given, have you grabbed that opportunity and really made the most of it and really driven change?

So she specifically called out, I believe, I believe there were two students that year at the GSB who had both started their educations, their higher educations at community college. Anything is possible. It really is about finding the people who, wherever they go, they jump in and make an impact.

[00:25:55] Heidi Hillis: Yeah, I think that to that point, I think it can almost be a more difficult if you’ve gone to Harvard and then worked at one of these, gone on one of these paths because we know that there’s, that’s an overrepresented pool in the applicant pool to stand out among those to have had that, that pedigree sometimes can be a disadvantage, right?

If you haven’t done as much as you should have with that, or if you started at that high level to show that level of progress over the course of your career is actually a little bit more difficult. Okay. And coming from a community college and rising to, a country level manager in some places is actually puts you at a significant advantage, I would say.

[00:26:31] Maria Wich-Vila: Because it’s hard for those people, it’s hard for those people to stand out, but also I think some of them go on autopilot, right? I think some people are on this kind of achievement, elite achievement treadmill, where they’re not even really thinking about what do I want to do with my life?

They’re always reaching for whatever that next, what’s the best college to go to? It’s Harvard Princeton. Yeah. Okay. Now that I’m here, what’s the best employer to work for? It’s McKinsey, Bain, BCG and without actually perhaps stopping to think about what is my passion? What impact do I want to make in the world?

And so I feel sometimes those autopilot candidates, I feel a little bit bad for them because they’re doing everything quote unquote and yet sometimes when you speak with them, that passion just isn’t there. And I do think that may ultimately harm them in the very, very elite business school.

Admissions because business schools want people who are passionate because at the end of the day, in order to do hard things, you’re going to need passion at some point to get you through those low periods. And so I think that’s something business schools look for. And I do think that sometimes these.

These kind of autopilot candidates might sometimes be at a disadvantage.

[00:27:29] Heidi Hillis: Yeah, I think that, to that point look in the data, when you look at it, you see so many people who’ve gone to McKinsey, Bain, Weasley, or Goldman, but then there’s a, you see a lot of success for people who’ve actually pivoted.

So those pivots that are post The second or third job really do show you that, if you’re if you get a candidate who’s coming from, still at McKinsey, okay, that’s fine. They have to be the top 5 percent of McKinsey, like they have to be going to get so many McKinsey applicants that the only the, you can look at the data in a couple ways.

One is, oh, my God, they took 12 people from McKinsey and the others. Oh, my God, they only took 12 people from McKinsey, right? That’s So if you want to be one of those 12, you have to be the top 12 in the world, right? Whereas if you’ve gone to McKinsey and then done an externship at a health care startup and then moved on to be a product manager at for health at Google, that kind of a path is definitely showing a little bit more, maybe risk taking, maybe ability to follow your passions.

So I think that. When I see candidates who come to me, for example, and they’re like, not thinking about applying now, but maybe in a year or two, I say, look for an externship, maybe think about pivoting out of one of these places and looking for some operational experience.

And because you see in the data that works.

[00:28:42] Maria Wich-Vila: And they’re doing themselves a service not only in terms of enhancing their admissions chances, but even just in terms of determining, what do I want to do with my career? If I do eventually want to go into industry, what functional role do I want to have?

What industry do I want to work in? So it’s, it actually benefits them in the long term to do that as well, even if they don’t go to business school. I think those secondments and externships and second job, post consulting jobs are extremely valuable. Totally agree with you.

[00:29:06] Caroline Diarte Edwards: And I’m sure they also bring more to the classroom as well.

I would think that’s also why Stanford is selecting some of those candidates, because not only have they worked at McKinsey, but they’ve also led a non profit in Africa or worked in private equity or whatever it is. So they have much more breadth that they can bring to the classroom. And I think that It’s seen as a very valuable contribution

[00:29:29] John Byrne: in Heidi.

Did you see that? The majority of the candidates to examined actually did work in more than one place, right?

[00:29:37] Heidi Hillis: Yes, most of them did. There were very few that, you see working at one place. And I would say that those are people that would have really risen through the ranks.

Someone who’s worked at Walmart and become, started in, I don’t know, in one state, but then to become a regional manager and things like that really are going to onto a global role. The people who have stayed at one place really have shown significant career progression within that.

And then the other people I think you do see a lot of movement. The big. The most typical would be from investment banking to private equity and then you do find in finance, there’s a little bit less kind of movement into other industries. You see a lot of people staying within finance, but within finance.

Yeah. Yeah. The other industries, especially consulting or other, tech, people are really moving into other places and it’s becoming, it is a little bit difficult. We have these categories that we’ve talked about, for example, healthcare, but it’s hard to categorize some of these companies.

Are they healthcare? Are they tech? There’s a lot of overlap. And so everything’s a little bit of tech in something nowadays. So whether it’s finance and fintech or education and ed tech or health care and health tech, these are all merging and combining. It’s hard to categorize them.

[00:30:53] John Byrne: So looking at the data here I wonder if you’ve seen your old classmates in the sense that these new people are very much like the people you went to school with at Stanford. I

[00:31:05] Heidi Hillis: put this out and it’s really interesting to a lot of my classmates downloaded the report and read it. And a lot of them came back and said, oh, boy, I would never get in now.

It’s these people are super impressive. I think that you see a lot of. It’s just become more and more competitive. And I think that with more information and more people every year applying, it is becoming really difficult. I think that you do see a lot of, I am encouraged by the diversity part of it that you see still Stanford.

I feel like they do take risks on some really interesting profiles and candidates that maybe some other schools are less likely to do. And so that’s what does give me. A lot of hope when I get some kind of really nontraditional candidate who wants to, their dream school is Stanford. I feel like, I say all the time, there’s a 6 percent chance.

You’re going to get in, but there’s 100 percent chance. You won’t get in if you don’t apply. So you’ve got to, you got to give it a go. And that’s, the attitude that we take to it.

[00:32:04] John Byrne: Indeed. So for all of you out there read Heidi’s article on our site, it’s called who gets in and why exclusive research.

Into Stanford GSB and I’ll tell you one conclusion I have about this is that, man, if you really want to get into Stanford, you need a Sherpa, and and Heidi would be a great Sherpa for you because the, just the profiles of these folks, where they’ve been, what they’ve done, what they’ve accomplished in their early lives is so remarkable that To compete against, in this pool for a spot in the class you need every possible advantage you can get.

And and having an expert guide you through this trip probably would be a really big advantage. So Heidi, thank you for sharing your insights with us and the research, the very cool research.

[00:33:01] Heidi Hillis: Thank you

[00:33:03] John Byrne: and for all of you out there. Good luck. And if you want to go to Stanford, you got to check out this report.

Okay. It will inspire you to up your game, even if you are from Harvard, Stanford, Wharton, or wherever McKinsey, Bain, BCG, Goldman, Google, you want to look at this report and you want to really think about. What it will really take to get in. I think it will inspire you, motivate you to really put your best foot forward.

Thanks for listening. This is John Byrne with Poets& Quants.

Maria

New around here? I’m an HBS graduate and a proud member (and former Board Member) of AIGAC. I considered opening a high-end boutique admissions consulting firm, but I wanted to make high-quality admissions advice accessible to all, so I “scaled myself” by creating ApplicantLab. ApplicantLab provides the SAME advice as high-end consultants at a much more affordable price. Read our rave reviews on GMATClub, and check out our free trial (no credit card required) today!