Innostruction
Led by Tianle Yu, this AI-equipped course management system provides real-time feedback and personalized study plans for students by matching practice questions to their background and performance level. A core component is the Question Repository, which now includes more than 1,200 categorized questions. Instructors can instantly generate fully formatted exams, practice worksheets, and handouts in PDF form.
Iris
Led by Wong Zhao, this AI-enhanced course content management platform focuses on accessibility, usability, and universal design through adaptive content delivery. These changes particularly benefit students with dyslexia, ADHD, and non-native English speakers, making course content easier to navigate and understand. This system has transformed how assignments and learning materials are delivered. Iris is merging with Innostruction to combine personalization with accessibility, expanding its impact on student learning.
EQUAL (Equitable Question Understanding and Learning)
Led by Bobby Chavez, this AI-equipped questions search system assists with question selection. Using the Innostruction’s question repository to fulfill two main goals: To build a model capable of estimating question difficulty, topic, and time-to-complete, and to provide a reusable module that enables instructors to train and extend for intelligent question selection.
Ethics module: Search Systems and Ethics
Developed by Sammy Lesner, this module introduces students to the design of search engines while engaging them in ethical discussions. Students learn to build a simple search engine using an inverted index and different ranking methods while examining issues of misinformation, bias, trust, and economic incentives. The module encourages reflection on how technical design choices shape fairness and responsibility in society.
Ethics module: Creativity and Machine Learning
Developed by Joseph Douglass, this module examines creativity through the lenses of philosophy, psychology, music, and computer science. Students explore definitions of creativity, novelty, value, intentionality, and non-formulaic processes, and apply them to coding and problem-solving. Using music as a parallel to computational thinking, the project challenges students to reflect on whether AI can be truly creative and what that means for human learning and expression.
Ethics module: Intellectual Property and Generative AI
Developed by Tanvi Ladha, this module helps students understand the legal and ethical complexities of using AI in software development. It introduces the foundations of intellectual property, including copyright, patents, trademarks, trade secrets, and fair use, and connects them to contemporary challenges like AI training data, model outputs, and licensing. Through case studies, students analyze stakeholder perspectives and practice making informed professional decisions.
Ethics of Implementing AI in Quant Algorithms
Developed by Aditya Tawari, this project analyzes the efficiencies of ticker trading with simple rule based models vs. machine learning models, with an additional analysis on client and market understanding of these models when utilized by hedge funds for portfolio optimization.
Ethics module: Privacy Policy Permission Modeling
Developed by Professor Maryam Majedi, this module explores how privacy policies can be represented graphically and discusses the importance of informed consent, helping users better understand what privacy permissions mean in practice.
