Two CNS Faculty Receive Inaugural Award for Outstanding Teaching Innovation from Jacobs School of Engineering
Developed by Niema Moshiri, an associate teaching professor in the Department of Computer Science and Engineering, the scalable adaptive automated grading system framework provides several key benefits:
Students receive descriptive feedback if they submit an incorrect answer, so they are able to diagnose the error and learn from the mistake
Faculty and instructional staff spend less time grading assignments, and more time interacting with students and designing more effective, creative coursework
Students receive immediate feedback, instead of waiting to see what course material they need to review
“AI systems and algorithms will never be able to create empathy or connection with students,” Moshiri said. “So I use technology to automate what I can automate, so that I can maximize the human empathy aspect to work with students, diagnose issues, and talk with them about the class.”
Faculty in structural engineering, bioengineering, electrical engineering and even biology have met with Moshiri to discuss potentially implementing similar grading systems for their classes. While some components of Moshiri’s system are modular and could be adapted by any faculty, the key element – the structure of the questions and feedback provided for incorrect answers – is tailored by Moshiri for each course and does not rely on any AI models. Moshiri views the grading system as a living document that he updates each quarter as he and his instructional staff continue to learn about pitfalls that students face when learning the course material.
Moshiri designs the assessment questions to build off one another, so that he is able to predict the misconceptions that students will have for each question, and provides specific feedback for the top few incorrect answers he suspects students may submit. In introductory courses, he is very detailed about the output and guidance provided to students. In upper division courses, he starts out providing a good deal of feedback, but reigns it in as the course progresses.
Automating all grading through the tools he created frees up his instructional staff to devote the bulk of their time to in-person student support.
“Every day of the week we have two or three people at any given time from roughly 9am to 7pm ready to talk to students and help them truly learn this material,” said Moshiri.
The grading system also allows faculty to randomize the data set generation, so that they don’t need to spend time recreating the same problem with different numbers or figures from quarter to quarter, or even from a homework assignment to an exam. This reduces the faculty workload, and ensures that the problems students see on exams correspond to problems they’ve seen in class, removing concerns about exams testing on unfamiliar material.
Jacobs School of Engineering Teaching and Mentorship Awards
The new Jacobs School of Engineering Teaching Innovation Award was created to recognize a specific teaching innovation with impact beyond a single classroom.
The award can go to either an individual faculty member or a faculty team, and can include such innovations as the creation of new pedagogical techniques, developing innovative undergraduate curriculum, progressive assessment strategies, educational enhancement tools, inclusive classroom practices, development of educational technologies, or impactful educational research.
This new award complements the Jacobs School’s suite of annual teaching and mentorship awards, which include a best undergraduate teaching award in each academic department, an outstanding graduate student mentorship award in each department, and a Jacobs School-wide outstanding faculty mentor award.
“Educating the innovation workforce for the economy of the future is at the core of what we do at the Jacobs School of Engineering,” said Albert P. Pisano, Dean of the Jacobs School of Engineering and Special Adviser to the Chancellor for Campus Strategic Initiatives. “We are able to deliver on this mission because of our talented and creative educators of every stripe. Congratulations to all our faculty who have received teaching and mentorship awards this year.”
Best Undergraduate Teacher Awards
Each year, the Jacobs School honors a faculty member from each academic department as a Best Undergraduate Teacher of the year.
The 2024 – 2025 Best Undergraduate Teacher Awards to go:
Alyssa Taylor, Bioengineering
Justin Opatkiewicz, Chemical and Nano Engineering
Sicun Gao, Computer Science and Engineering
Rajeev Sahay, Electrical and Computer Engineering
Sylvia Herbert, Mechanical and Aerospace Engineering
Lelli Van Den Einde, Structural Engineering
Best Graduate Mentor Awards
The Jacobs School honors six faculty awarded Best Graduate Mentor
2024-2025 Outstanding Graduate Mentor Award:
Vira Kravets, Bioengineering
Liangfang Zhang, Chemical and Nano Engineering
Imani Munyaka, Computer Science and Engineering, and CNS Faculty Member
Gabriel Rebeiz, Electrical and Computer Engineering
Hyonny Kim, Structural Engineering
Sergei Krasheninnikov, Mechanical and Aerospace Engineering
Outstanding Faculty Mentor Award
Each year, the Jacobs School names one Outstanding Faculty Mentor from the Jacobs School of Engineering.
2024-2025 Outstanding Faculty Mentor:
Shaya Fainman, Electrical and Computer Engineering, and CNS Faculty Member
Story Written by Katherine Connor
khconnor@ucsd.edu