An Art Form Of Its Own: Teaching Assistants in EECS.

By Jane Halpern

July 24, 2025 | Department of Electrical Engineering and Computer Science

Hope Dargan SB ’21 MEng ’23, a second-year PhD student in EECS who got her bachelors’ degrees in History and Computer Science, sees her graduate instructor role through an intersectional lens. “I value people and their stories—and teaching is a nice intersection of people, computer science, and stories: all the things I really like.” Photo credit: Frankie Schulte.

“It’s probably the hardest thing I’ve ever done at MIT,” says Haley Nakamura, a second-year MEng student in the Department of Electrical Engineering and Computer Science. She’s not reflecting on a class, final exam, or research paper. Haley is talking about the experience of being a Teaching Assistant (TA). “It’s really an art form, in that there is no formula for being a good teacher. It’s a skill and something you have to continuously work at and adapt to different people.” 

Haley, like approximately 16% of her EECS MEng peers, balances her own coursework with teaching responsibilities. The TA role is complex, nuanced, and at MIT, can involve much more planning and logistics than you might imagine. Haley works on a central CS course, 6.3900 Introduction to Machine Learning, which registers around 400-500 students per semester. For that enrollment, the course requires 8 instructors at the lecturer/professor level; 15 TAs, between undergrad and graduate; and about 50 Lab Assistants (LAs). Students are split across 8 sections corresponding to each senior instructor, with a group of TAs and LAs for each section of 60-70 students. 

To keep everyone moving forward at the same pace, coordination and organization are key. “A lot of the reason I got my initial TAship was because I was pretty organized,” Haley explains. “Everyone here at MIT can be so busy that it can be difficult to be on top of things, and students will be the first to point out logistical confusion and inconsistencies. If they’re worried about some quirk on the website, or wondering how their grades are being calculated, those things can prevent them from focusing on content.” Haley’s organizational skills made her a good candidate to spot and deal with potential wrinkles before they derailed a course section. “When I joined the course, we wanted someone on the TA side to be more specifically responsible for underlying administrative tasks, so I became the first head TA for the course. Since then, we’ve built that role up more and more. There is now a head TA, a head undergraduate TA, and section leads working on internal documentation such as instructions for how to improve content and how to manage office hours.” The result of this administrative work is consistency across sections and semesters.

Haley Nakamura, a Computer Science and Engineering major minoring in Environmental Engineering, is the first-ever Head TA for 6.3900 Introduction to Machine Learning, which registers 400-500 students per semester. “The organizational structure of the course is almost like a company,” she says. “We’ve made many changes to the management structure, and I hope they continue to pay off.” This year, Haley was honored with the MIT Goodwin Medal, which is given annually to a graduate student whose performance of teaching duties is “conspicuously effective over and above ordinary excellence.” Photo credit: Frankie Schulte

The other side of a TA-ship is, of course, teaching. “I was eager to engage with students in a meaningful way,” says Soroush Araei, a 6th-year graduate student who had already fulfilled the teaching requirement for his degree in electrical engineering, but who jumped at the chance to teach alongside his PhD adviser. “I enjoy teaching and have always found that explaining concepts to others deepens my own understanding.” He was recently awarded the ​MIT School of Engineering’s 2025 Graduate Student Teaching and Mentoring Award, which honors “a graduate student in the School of Engineering who has demonstrated extraordinary teaching and mentoring as a teaching or research assistant”. Soroush’s dedication comes at the price of sleep: “Juggling my own research with my TA duties was no small feat. I often found myself in the lab for long hours, helping students troubleshoot their circuits. While their design simulations looked perfect, the circuits they implemented on protoboards didn’t always perform as expected. I had to dive deep into the issues alongside the students, which often required considerable time and effort.” 

The rewards for Soroush’s work are often intrinsic: “Teaching has shown me that there are always deeper layers to understanding. There are concepts I thought I had mastered, but I realized gaps in my own knowledge when trying to explain them,” he says. Another challenge: the variety of background knowledge between students in a single class. “Some had never encountered transistors, while others had tape-out experience. Designing problem sets and selecting questions for office hours required careful planning to keep all students engaged.” For Soroush, some of the best moments have come during office hours. “Witnessing the “aha” moment on a student’s face when a complex concept finally clicked was incredibly rewarding.”

Soroush Araei, an EECS graduate student in the Research Laboratory of Electronics (RLE), relishes the moments “when a student asks a deep question that I can’t immediately answer, and I have to dive deeper into the material to find a response.” Photo credit: Frankie Schulte.

The pursuit of the “aha” moment is a common thread between TAs. “I still struggle with the feeling that you’re responsible for someone’s understanding in a given topic, and, if you’re not doing a good job, that could affect that person for the rest of their life,” says Haley. “But the flip side of that moment of confusion is when someone has the “aha!” moment as you’re talking to them, when you’re able to explain something that wasn’t conveyed in the other materials. It was your help that broke through and gave understanding. And that reward really overruns the fear of causing confusion.”

Hope Dargan SB ’21 MEng ’23, a second-year PhD student in EECS, uses her role as a graduate instructor to try and reach students who may not fit into the stereotype of the scientist. Hope started her career at MIT planning to major in CS and become a software engineer, but a missionary trip to Sweden in 2016-17 (when refugees from the Syrian civil war were resettling in the region), sparked a broader interest in both the Middle East and in how groups of people contextualized their own narratives. When Hope returned to MIT, she took on a History degree, writing her thesis on the experiences of queer Mormon women. Additionally, she taught for MEET, an educational initiative for Israeli and Palestinian high school students. “I realized I loved teaching, and this experience set me on a trajectory to teaching as a career,” says Hope, who gained her teaching license as an undergrad through the MIT Scheller Teacher Education Program (STEP). She then joined the MEng program, in which she designed an educational intervention for students who were struggling in 6.101 “Fundamentals of Programming”. The next step was a PhD. “Teaching is so context-dependent,” says Hope, who was awarded the Goodwin Medal for her teaching efforts in 2023. “When I taught students for MEET, it was very different from when I was teaching 8th graders at Josiah Quincy Upper School for my teaching license, and very different now when I teach students in 6.101 versus when I teach the LGO students Python in the summers. Each student has their own unique perspective on what’s motivating them, how they learn, and what they connect to… So even if I’ve taught the material for 5 years (as I have for 6.101, because I was an LA, then a TA, and now an instructor), improving my teaching is always challenging. Getting better at adapting my teaching to the context of the students and their stories, which are ever-evolving, is always interesting.”

Hope Dargan has set a goal of making the CS learning process more accessible. “The stereotypes associated with software engineering, such as the idea that you have to be super smart to code,  that are really good for people who like to problem solve for problem solving’s sake. But I want CS to expand and include everyone, especially   people who want to solve human problems and social problems, who are not being served by this idea that coding is just sitting behind a screen all day solving complex technical problems.” Photo credit: Gretchen Ertl.

Although Hope considers teaching one of her greatest passions, she is clear-eyed about the cost of the profession. “I think the things that we’re passionate about tell us a lot about ourselves, both our strengths and our weaknesses, and teaching has taught me a lot about my weaknesses,” she says. “Teaching is a tough career because it tends to take people who care a lot and are perfectionists, and it can lead to a lot of burnout.” 

Hope’s students have also expressed enthusiasm and gratitude for her work. “Hope is objectively the most helpful instructor I’ve ever had,” shared one anonymous reviewer. Another wrote, “I never felt judged when I asked her questions, and she was great at guiding me through problems by asking motivating questions… I truly felt like she cared about me as a student and person.” Hope herself is modest about her role, saying, “For me, the tradeoff between teaching and research is that teaching has an immediate day-to-day impact, while research has this unknown potential for long term impact.”  

With an ever-growing percentage of the Institute’s students, the Department of EECS relies heavily on dedicated and passionate students like Nakamura, Araei, and Hope. As their caring and humane influence ripples outwards through thousands of new electrical engineers and computer scientists, the day-to-day impact of their work is clear; but the long-term impact may be greater than any of them know.