Listen to Professor Josh Samani describe how artificial intelligence reshapes education, why real-world connections prove essential to meaningful scientific understanding, and how his Iranian American identity informs his interest in physics.

Megan Vahdat: I’m Megan Vahdat, and this is “Persian Perspectives Today,” a podcast that explores the viewpoints of Iranian leaders in arts, science, education and politics in the UCLA community and beyond. Today, I am joined by physics professor Josh Samani.

Professor Samani earned his Ph.D. in theoretical high energy physics from UCLA, where he serves as a leading voice in innovative science education. His scholarship especially focuses on advancing our understanding of human learning through rigorous, classroom-based research. By combining controlled experiments with continuous, data-driven refinement, he transforms each course into a dynamic laboratory for educational innovation. In 2017, he received UCLA’s prestigious “My Last Lecture” award – the university’s largest student-nominated faculty honor. He is widely regarded as a standout professor at UCLA. Thank you so much for joining us today, Professor Samani.

Josh Samani: Thanks for having me.

MV: You’re someone who spent much of your career studying how people learn and encouraging students to take small, manageable steps to understand complicated topics. You’re known for emphasizing the importance of reviewing material regularly, staying organized and returning to previous topics to truly retain them. So I’m curious – when you were a college student, would you characterize yourself as someone who was already methodical and organized? Did you study the way you now recommend your students to?

JS: No, very far from it. When I was a college student, I was a huge procrastinator. I had no idea how to study. I failed my first math class in college. Yeah. In general, it took me a really long time to figure out how to study. And even until grad school, I would say I didn’t really know evidence-based principles for how to study well. It’s very rare for people in that age group to have an understanding of the science of learning. So it’s not until I started teaching it to other people and doing the research that I understood some of these principles.

MV: That’s interesting. I think so often we look up to our professors and forget that, just like us, they’ve had setbacks and made mistakes in the same subjects they now teach. And along those lines, you were a college student experiencing these setbacks for the first time when you were studying math and physics. You’re a math and physics major, I believe, so I’m curious – when did your interest in physics in particular really take root? Was your first exposure to physics in college or even before then?

JS: Yeah, so I’d say the formal field of physics I didn’t discover until very late in high school when I took a physics class. But if I look back at my childhood, I was always doing things that were physics-adjacent, even though I didn’t know that’s what they were. So one of my earliest memories with physics actually is, my dad and I were on a train to go to Yosemite. We’d go to Yosemite in the summer sometimes, and while we were on the train, I was holding a balloon. I don’t remember why or how I got the balloon, but I was holding the balloon, and I remember thinking to myself, “If I were to let go of this balloon, would it keep traveling with the train, or would it kind of blow back to the back of the train and hit the back wall?” And neither me nor my dad could answer this question convincingly. And I remember thinking about this question for many years until probably I got to high school and then learned what the answer was. But there were a lot of occasions like that in my childhood where I wondered about things. I didn’t know I was thinking about physics, but I was. And I loved science, even though a lot of times I didn’t know that it was science that I loved. But I would do things where it turned out they were kind of mathy, sciencey kind of things.

MV: It’s interesting. A lot of people have an early interest in physics but don’t realize that what they’re fascinated by is physics. But you are well known for saying that with the right approach, anyone can really grasp the most complicated of topics. What do you think are some of the biggest misconceptions that people have about physics?

JS: I think people think of physics as an abstract, highly mathematical field, which it is. I mean, physicists do in modern times work with very mathematical, abstract concepts. But physics, at its root, is an attempt to describe the world. Most of the time, I would say, when you really understand how to describe the world, you tend to be able to explain it or describe it in a simple way – at least the fundamental principles in a pretty simple way. So typically, I think people’s fear comes from this projection of physics that’s this really formalized thing. But in reality, most really fundamental physics is actually really simple and beautiful and elegant, and you can explain it to most people. So, I commonly say to my students, “If you can’t explain it to a 10-year-old, you probably don’t understand it.” So, yeah, I think it’s just a perception issue to a large extent. But it’s also true – if you want to get to the frontier of physics, you need to do a lot of math and a lot of abstract stuff as well.

MV: Could you even explain the topic of your Ph.D. dissertation as you would to a 10-year-old?

JS: Yeah, yeah. I’m not totally sure – I should be able to. I mean, what I would say is that the universe is made of basically two things. There’s what we call matter, which is what things are made of, and then the interactions between those things. Matter is made up of what’s called quarks and leptons – these subatomic particles, really small particles. The forces are kind of facilitated or mediated by these other particles. And there’s been a huge attempt to understand how the particles that describe gravity – which is one of the forces we experience all the time – how that force unifies with the other forces that particles feel at subatomic scales.
In the nucleus, there are forces that keep nuclei together, and there’s forces in electricity and magnetism. So there’s this push to try to understand all these things in a unified way, to think about them all in the same way. And in my Ph.D., I studied how you could attempt to unify some aspects of gravity with some of the other forces that we experience.

MV: I think a lot of students hear anecdotes like these – or they’ve mentioned to me – about your growing up, or your experiences in grad school, or your broader thoughts about learning like you’ve just mentioned, or your mottos in your open office hours, which is a time you set aside each week for students to come talk about anything that is not related to the course material and what you’re learning in class. Students mention that you even play chess and listen to music with them. What made you want to create this kind of space, and why is that important to you?

JS: I felt like in recent years, people have become more isolated from each other.
Partly, social media and technology – they purport to connect us, but really, a lot of times it causes people to connect only in a digital form. And I felt like especially since COVID, and online learning has become a lot more common, people don’t often meet up at UCLA to discuss interesting things that aren’t related to the course or just connect with each other. And it used to be, I think, more people would do this. And so I was trying to create a space with students where we deliberately come in real life, talk to each other about interesting things, connect with each other – especially around things that are just fun. Like, coming to UCLA, I hope, would be fun. And learning would be fun. And so you want to kind of create a community around that. That’s an attempt to do that.

MV: It’s interesting – we’re in a very digitized age. So much so that all the time at UCLA, I’ll see people sitting around a table, at lunch or whatever, or in Ackerman, and they’re all on their phones. I mean, even with me and my friends – everyone’s sitting down on their phone. And especially, it’s such a large campus where it’s really hard to get to know people. Sometimes those spaces, when you’re transforming part of your classroom into a smaller segment for people to get to know each other, are especially important, I think. And it seems that getting to know people outside of the classroom is really central to your teaching philosophy. But one part of your identity that many students might not know about is your background as an Iranian American. Can you share a little about that aspect of who you are? How has growing up Iranian influenced the way you think about education or science more broadly?

JS: Yeah, so my parents are both immigrants from Iran. Both of them came here in the ’70s. My dad is a structural engineer, and he got his master’s degree in the United States – in Iowa, in fact. And then my parents moved to California when my dad got a job. So, my household was always kind of – there was a duality. There was always an extremely strong appreciation for American culture and values, because my parents kind of shared those values, and that’s why they were here. And on the other hand, there was an extremely strong appreciation for Iranian culture and music and food and all that. So, in some sense, I was torn between these two identities. Especially when I was younger, I grew up in an area where it was mainly white and Asian. So most of my friends now are white and Asian, and I didn’t have very many Iranian friends growing up. But I always still had a strong connection to my Iranian roots – you know, the language, the culture, the music, everything. So especially as I got older, I started to appreciate that.

Having this experience, this dual experience, has given me, I think, a broader sense of what’s possible for people to think and experience. And it has really colored my sense of, you know, the value of diverse experiences and different cultures. And it’s influenced – I think – the way I think of science, too. In science, there are different perspectives. People bring different experiences based on even what country they’re from. They have different approaches to science or different cultural approaches to things. And so that, I think, to some extent, has impacted me. I place a pretty high value on cultivating lots of different perspectives in science.

MV: And you mentioned that you grew up around a very small Iranian community. You weren’t around a lot of Iranians as a high school student. So what did you do to keep that culture alive in your growing up? Did you speak Farsi? Just curious about your experiences related to that.

JS: Yeah, yeah. My first language was actually Farsi. So for the first, I think, probably like five years of my life, I spoke only Farsi. And we had a lot of family in the area, too. So we would visit with them all the time, and we had family functions. But really, also, when I was younger, I don’t think I explicitly really appreciated it as much. It’s more as I’ve gotten older, especially after grad school, that I’m more explicitly like – I’ll listen to Persian music, or try to learn about history, or things like that.

MV: Along those lines, have you ever reflected on the legacy of Iranian contributors to science and mathematics? You know, from historical figures to the strong presence of Iranian scientists today – has that heritage shaped how you see your own place in physics and academia?

JS: Yeah, I think that’s definitely played a role – especially implicitly. My dad is kind of from that Iranian tradition of science and engineering and has placed an enormous value on science and math and education. So I think I was implicitly really strongly influenced by that. When I was growing up, he had a certain way of doing math, for example. We would do math together, and he had this organization and kind of – he just really – you could tell that he valued the process of doing it. It was valuable to him. So yeah, I would say that’s probably my most direct influence – through him. I don’t actually interact with Iranian scientists now very much. I have in the past, in grad school. I would meet sometimes at conferences. I would meet Iranian physicists, in fact, from Iran. But yeah – my current role, I don’t really interact with Iranians that much. But yeah, in my past, I think it’s more of an implicit effect.

MV: Interesting – it’s like your culture helped foster maybe a bond with the subject through your dad. And switching gears a little from your personal background to your experiences in the classroom and how you’ve maybe applied that, you’ve said that understanding real-world applications is essential to how you teach physics now. One issue that you pointed out is that students can sometimes get the right answer on a test but don’t really understand how what they’re doing is used in real life. How do you help students connect what they’re learning in class to the real world in your teaching?

JS: Well, the thing that really matters the most to me is that when students take a science class, they are equipped with a set of tools. And they can use those tools to make sense of the world. So what I mean by that is, we go into the world, and we receive enormous amounts of information. And physicists have learned ways to answer the question, “Is the information I’m receiving—does it make sense? Is it kind of sensible in any way? Like, is this number too large or too small? Or does it make sense that this person told me that 50% of the water in California is non-drinkable?” or whatever. Someone could say just something random, and you want to assess that. So my goal, really, is to give students the tools to answer these sorts of sense-making questions and in as mathematical a way, I guess you could say, as possible – or maybe not even that – but just to have some basic tools for figuring that out. And so what I try to do – even though mostly I feel like I fail to a large extent to do this – but what I try to do is pick examples where they’re connected to everyday life and simple enough that we can actually use the things we’re learning in class to calculate something or say something concrete about them.

And by modeling this over and over again and asking students to answer questions of that type over and over again, my hope is that they go on into the world, and they see something, and they think to themselves – oh, well, maybe not even consciously – but they just do this sense-making process because they’ve been trained to do that.

MV: I think you – like you mentioned very often – it’s become especially important for us to make sense and to analyze the facts we’re given through the lens of physics. And you care about that so much so that you even wrote your own textbook for your courses, which implements a lot of these real-world, real-life examples, analogies and animations sometimes of these physical concepts. What are some of the problems you see in traditional physics textbooks, and what motivated you to create your own?

JS: Well, there’s a central problem with basically all traditional textbooks, which is that the textbooks change over time. And sometimes they change in a way that’s an improvement, and sometimes they may not. And sometimes they may improve, but the improvement is not known to be an improvement. Like, you can make a change, and it may happen to improve the book or learning. But if you haven’t measured if that’s happened, then you don’t know. And so the reason I wrote the book I did – on this platform called CourseKata, which actually was created by a faculty member in our psychology department many years ago – the reason I wrote on this platform is that it’s designed to allow the instructional designer, the writer of the book, to do randomized controlled experiments within the book.

So what that means is that we can change something in the book and give half the students a changed version and half the students the unchanged version. And then we can measure the impact of that on, say, answering a certain question in the book or some sort of interaction with the book or so on. So we can continuously run these experiments to test theories of what’s going to improve learning and what’s not. And so we’re doing science at scale in the book all the time. We’re doing all these different experiments all the time and trying to see what works and what doesn’t. So this is the thing I’m most interested in – continuously improving education and learning using science at these very small scales, meaning you build a theory of what you think will happen. You test that theory over and over and over again – the idea being that over time, the book will become really, really good in a way that most standard books probably don’t because they aren’t being developed in this way.

MV: And I think because you’re someone who is constantly adapting your course to fit the changing perspectives of students, especially as we enter an AI era, students often describe you as an unbelievably dynamic speaker and professor—so much so that you were nominated by the student body to win UCLA’s Last Lecture Award, which honors the most engaging professors on campus. In your view, what makes a great lecture that can help students learn while keeping them engaged?

JS: Yeah, so that intersection of engagement and learning is really central – and difficult. A lot of times, people focus on one or the other. So it’s really easy to make a great, fun lecture that people enjoy. It’s possible to make a lecture that people learn a lot from.

Both of those on their own are difficult, but to make one that intersects both of those things is particularly hard. So on the engagement side, I also do science with that. So I have questions embedded in the worksheets we do each lecture that ask students about their level of engagement and interest, and we measure that. But also I use some traditional principles of making things engaging – like, you should try to open up with a question or with a story, or maybe a story that contains a question or an interesting fact. So I try to open the lectures with some example like that and then design the rest of the lecture so that we answer that question or we explore the story. And at the same time, the lecture’s designed in such a way that students have to think deeply about what we’re doing, answer questions themselves during the lecture, show their work and talk to each other and then have a discussion altogether. So I try to combine all of those elements every lecture.

MV: Students have mentioned to me that you sometimes will show videos in your backyard of bubbles floating or even show videos of motorcycles racing down to illustrate topics like the Doppler effect. So I think that, like what you’ve said so far, you’re someone very focused on clarity and understanding and adapting to the student experience. So I want to turn both in science and in education, which is kind of this influx of artificial intelligence. As someone who has dedicated years to studying the science of human learning, how do you think AI will impact education itself? Students now can outsource their homework, generate answers, and even simulate labs or lab reports. Do you think these tools will ultimately enhance human learning or undermine their ability to think critically?

JS: My feeling on this is that AI is an incredible learning tool for people who have the discipline to kind of eat their learning vegetables. So you know I said it’s hard to intersect engagement and learning. Part of the reason for that is that learning typically requires a certain kind of cognitive effort that can be uncomfortable. So you know – we’ve talked in class, for example, about how if you want to remember something for a long time, you need to force yourself to retrieve that memory. These things can be difficult and uncomfortable. So, as most people know, the adage “no pain, no gain” – it applies to learning, too. And so AI gives you this entity that you can interact with and learn an enormous amount from and actually learn how to think from, for example, or check your reasoning or have really deep conversations with. But it can also be the thing that thinks for you. And so it just depends, I think, on the learner. If the learner wants to use the tool in a productive way, they can accelerate their learning in ways that weren’t possible before. But if they’re not – if they’re not disciplined in doing that – then it can really undermine their learning. So I’m really hopeful but also very concerned that society might further stratify into people who already love to learn and use AI tools to get better and better, and those who don’t know how to use it or don’t have the discipline to use it in these ways – in which case, that’s, I think, not a great thing. We want people – most people – to be pretty educated, have these sense-making tools and so on. So I do worry about that.

MV: Looking ahead, if we fast forward maybe 10 years in your course, how do you imagine your own physics course at UCLA might evolve with the integration of AI?
What changes do you anticipate in how you teach, even?

JS: Yeah, I think there could be pretty enormous disruptions in the way we do things currently. For example, a lot of the things that we teaching assistants do – like grading, for example – it’s hard not to imagine that at some point, these things will be replaced by artificial intelligence to some degree at least. So I think that will probably change a lot. I worry sometimes it could replace me. And I think in terms of understanding physics and explaining physics, interacting with people in productive ways to learn physics – we’re already at a point where most advanced AI tools can do that. But I think potentially our saving grace is that human beings have evolved to connect with each other. And there’s actually research on how human beings are social learners and how that’s kind of our superpower. So, I think it’ll be difficult to beat person-to-person learning – social forms of learning – basically forever, because of how we evolved. But I do worry that there are going to be disruptions to the way we do things, and it’s not clear how that’s going to pan out.

MV: And to wrap up our conversation today: What advice would you give to students right now about how to navigate AI in their own education? How can we use these tools responsibly while still building a real understanding as we’re learning topics in your classes and beyond at UCLA?

JS: Well, I think there’s a fundamental hard problem to solve, which is that – as we talked about before, to go full circle – when I was a college student, I didn’t know what productive learning behaviors were. So if you had given me an AI tool back then, it would be very hard for me to use it appropriately. Now I know things like: it’s really important to spend time explicitly analyzing your errors. It’s important to spend time making sense of principles. So I’ve built up all these things in my mind about what productive learning behaviors are. So I think the challenge is, if you’re a student who wants to get the most out of AI, you kind of need to know some of those basic things. And I think some people do. Many people know these things on an intuitive level.

So as long as you have those in mind, then I’d say, use AI as much as you can. Because – I mean, I personally use AI all the time, every day, constantly – because it makes me a much faster and better learner. But I think it’s only that way because I now know these things and have these tools where I can use it productively. So my advice would be: Use it a lot. Try to understand how it works. See where it makes mistakes and so on – its strengths, its limitations. But also try to understand some basic things about how learning works so that you know what to do and what not to do.

MV: Thank you so much for sharing your insights and perspective with our audiences today, Professor Samani.

JS: Thank you so much. Thanks for having me.

MV: This episode of Persian Perspectives Today was brought to you by Daily Bruin Podcasts. You can listen to this episode and all other Daily Bruin podcasts on Spotify, Apple Podcasts, and SoundCloud. The audio and transcript of today’s interview are available at dailybruin.com. I’m Megan Vahdat. Thank you for listening.