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LEARNER: Learning through Exams that are Auto-graded, Randomized, and Novel, for Equity and Resilience

Reorienting Formative and Summative Assessment Towards Mastery Learning for Learner Success, Student Equity, and Institutional Resilience

NEW: Spring 2023 special topics course aligned with the LEARNER Center’s agenda!


With seed funds from the UC Berkeley College of Engineering and the Office of the Vice Chancellor for Undergraduate Education, and a major award from the California Education Learning Lab (CELL), UC Berkeley, Cal State Long Beach, and El Camino College have launched an innovative and exciting pilot project to improve student equity/diversity and institutional resilience in Computer Science through Proficiency-Based Learning (also called Mastery Learning). The goal is to gain enough experience from the pilot project to establish a permanent Center for promoting proficiency-based learning on these and other California campuses.

Traditional teaching and evaluation methods used in STEM higher education, such as lab assignments, homework, and exams, can impede mastery learning and magnify equity gaps in student preparation. This two-year project will look at the impact of using proficiency-based learning methods, especially paradigm-based question generators (PQGs), to encourage and support “mastery” over foundational Computer Science concepts tailored to each student versus fast-paced learning and evaluation. This project will adapt and adopt the University Illinois at Urbana-Champaign’s PrairieLearn platform for mastery learning in computer-based assessments.

The project’s hypotheses are that mastery learning using PQGs will contribute to higher retention, stronger learning outcomes, more effective use of instructor time, and an increase in successful participation in computing for traditionally underrepresented students. We hope the findings of this project will open the door towards new learning approaches to expand diversity and inclusion in Computer Science. 

Grant abstract in CELL website.

Supported Courses

CS C8 Foundations of Data Science
CS 10 Beauty & Joy of Computing
CS 61C Great Ideas of Comp. Arch.
CS 88 Comp. Struct. in Data Science
CS 169 Software Engineering 
CS 186 Intro. to Databases Systems
CSULB inverted
CECS 174 Intro. Programming
CECS 323 Database Fundamentals
CSCI 7 Beauty of CS Principles
CSCI 8 Foundations of Data Sci.
CSCI 14 Comp. Prog. in Python for CS

Principal Investigators

Armando Fox

Armando Fox is a Professor of Computer Science, Faculty Advisor for Digital Learning Strategy, and Campus Equity Advisor at UC Berkeley; ACM Distinguished Scientist; and recipient of the 2015 ACM Karl V. Karlstrom Outstanding Educator Award.

Dan Garcia

Dan Garcia is a Teaching Professor in the Electrical Engineering and Computer Sciences department at UC Berkeley, an ACM Distinguished Educator, and a national leader in the CSforAll movement.

Alvaro Monge

Alvaro Monge is a Professor at California State University Long Beach in the Department of Computer Engineering and Computer Science. He teaches classes at different levels from introduction to programming for first-year students, database systems for third-year students, and capstone projects for graduating seniors.

Solomon Russell

Solomon Russell is a Professor of Computer Science at El Camino College and an adjunct instructor at the University of California, Los Angeles. He teaches classes in BJC, C++, data structures, and advanced programming. 

Edwin Ambrosio

Edwin Ambrosio is a Professor of Computer Science at El Camino College, an adjunct instructor at Santa Monica College, and an adjunct instructor at the University of California, Los Angeles. He teaches classes in C++, data structures, Java, Android, UNIX, assembly language, and advanced programming. 

PrairieLearn Highlights

Student Testimonials

"For once, I felt like an exam actually helped me understand everything better and tested me on that, rather than testing my ability to cram"
"Loved this exam format, props"
"I found it to be the best remote exam experience I've had this semester, in terms of reducing test-taking-related stress and anxiety as much as possible, allowing me to really focus on the material and learn it to the best of my ability"
"Awesome exam! You guys absolutely nailed it!"
"Usually going into midterms, I try to cram a bunch of different stuff and I end up understanding only bits and pieces of all the content. But with this format, I noticed that my studying went really differently"