About

The AskOski Project seeks to improve equity and achievement in higher education by making colleges and universities first-class beneficiaries of human-centered AI research.

AskOski, named after Cal's sports mascot, is a personalized academic exploration and degree planning system that collects various University data into a central platform allowing students to illuminate the academic terrain of their institution like never before. The system incorporates degree audit, course description, class schedule, future course preferences, and historic enrollment information combined with machine learning to help students explore their interests, connect course concepts across departments and draw up plans for future semesters while satisfying constraints of their programs.

This system is a product of ongoing research in data science, education, and cognition conducted by the Computational Approaches to Human Learning (CAHL) research lab. It is not meant to replace academic advising but rather allow students to benefits from the course pathways taken by students with similar course histories and majors and explore topical relationships between courses as informed by their peers. In this sense, the recommendations provided are not objective, but rather an alternative source of perspective on the conceptual landscape of the university which we hope students find informative.

Projects in learning analytics, such as this one, require the engagement of a cross-campus community. Our research is supported by grants from the National Science Foundation (#1547055 and #1446641) and Schmidt Futures. The system's data feeds are made possible by Enterprise Data & Analytics (ED&A) with approval and feedback from the UC Berkeley Office of the Registrar (OR). User studies conducted for research purposes have been approved by an Internal Review Board where deemed necessary by the UC Berkeley Committee for Protection of Human Subjects. We thank the following UCB staff and leadership for their essential past and continuing support: Andrew Eppig (OPA), Sanghamithra Bandi (ED&A), Radha Karichedu (ED&A), Aswan Movva (ED&A), Anji Gannavarapu (EDW), Mark Chiang (ex-EDW), Daniel Grieb (RTL), Raul Infante (OR), Max Michel (ex-ED&A), Jenn Stringer (CIO), Larry Conrad (ex-CIO), Johanna Metzgar (ex-OR), and Walter Wong (Registrar).

Research

Meet the Team

Zachary Pardos

Zachary Pardos
Principal Investigator

Dr. Pardos is an Associate Professor at UC Berkeley in the Graduate School of Education and affiliate faculty in Cognitive Science.

Alex Luu

Alex Luu
Developer

Alex is a undergraduate computer science and data science student at UC Berkeley. He is interested in cybersecurity, machine learning, and full-stack development.

Arda Kaz

Arda Kaz
Developer

Arda is a freshman majoring in computer science at UC Berkeley. He is interested in artificial intelligence and computer vision. He is currently working on AskOski’s backend, primarily optimization and development of AskOski’s database system.

Jiaqi Wei

Jiaqi Wei
Developer

Jiaqi is an undergraduate computer science student at UC Berkeley and CUHKSZ. Her research interests include Machine Learning, Data Mining, AI and Database. She's currently working on AskOski model improvement.

Kasra Lekan

Kasra Lekan
Developer

Kasra is an AskOski full-stack developer with research interests in NLP, interpretability, and human-AI interaction.

Nicole Ni

Nicole Ni
Developer

Nicole is an undergrad student studying Computer Science and Data Science. She is interested in the intersection of humanity and technology, and education. She is working on the modeling for AskOski.

Priscilla Chen

Priscilla Chen
Developer

Priscilla is an undergraduate student majoring in computer science and data science at UC Berkeley. Her research interest centers around Machine Learning, NLP, AI, and education.

Quang Nguyen

Quang Nguyen
Developer

Quang is an undergraduate EECS student at UC Berkeley interested in Signal Processing and Backend Developement. He mainly works on AskOski backend.

Serena Gu

Serena Gu
Developer

Serena is a senior computer science and economics student at UC Berkeley. She is interested in Machine Learning, backend development, and LLMs.

Sher Shah

Sher Shah
Senior Developer

Sher is an undergraduate computer science student at UC Berkeley. He is interested in full stack web development, UX design and Machine Learning.

Tanya Mehta

Tanya Mehta
Developer

Tanya is an undergraduate at UC Berkeley, studying EECS. She is interested in full-stack development and computer science education. She is currently working on the back-end for AskOski.

Alumni

Anirudhan Badrinath

Anirudhan Badrinath
Developer

Ariel Fogel

Ariel Fogel
Research Intern

Arshad Ali

Arshad Ali
Full-Stack Developer

Brian Lin

Brian Lin
Developer

Carly Feng

Carly Feng
Project Manager, Developer

Christopher Le

Christopher Le
Lead Developer

Ethan Zhang

Ethan Zhang
Developer

Jason Yu

Jason Yu
Developer

Johanna Metzgar

Johanna Metzgar
Associate Registrar

Matthew Dong

Matthew Dong
Full-Stack Developer

Max Litster

Max Litster
Developer

Run Yu

Run Yu
Senior Developer, Researcher

Shiyuan (Jeff) Guo

Shiyuan (Jeff) Guo
Lead Developer, Researcher

Weijie (Jenny) Jiang

Weijie (Jenny) Jiang
Recommendation Algorithms Researcher

Yuetian Luo

Yuetian Luo
Developer

Zihao Han

Zihao Han
Machine Learning