Projects

Equitable AI Alliance: Empowering Students through Equitable AI Education

As artificial intelligence (AI) becomes integral to the workforce, unequal access to AI resources threatens to widen existing gaps, particularly for students from historically underrepresented communities. Recognizing the need for equitable AI education, San Diego State University (SDSU), UC San Diego (UCSD), and the San Diego Community College District (SDCCD) have established the “Equitable AI Alliance”. The Alliance is built on three key activities: (1) AI needs assessment, (2) AI literacy education, and (3) AI access. It begins with a

Peer & AI Review + Reflection (PAIRR) in Writing Instruction

PAIRR- Transforming writing education through peer review and AI literacy To address equity gaps in writing skills and AI literacy, our intervention, Peer & AI Review + Reflection (PAIRR), leverages GenAI to increase writing support and boost AI literacy for both students and instructors. This intervention enhances metacognition and the human relationships that motivate students to learn. PAIRR has been recognized by a small competitive grant ($3,000) from the national Association for Writing Across the Curriculum Research Initiative, based on

Enhancing Academic Writing and Digital Literacy with an AI Coach

Promoting academic writing and AI literacy This project will iteratively develop, implement, and evaluate an AI tool to improve academic writing and digital literacy across California public higher education segments. The project will leverage PapyrusAI, a tool created with NSF funding to help students plan and revise their writing by using embedded prompts to guide interaction with AI. The PapyrusAI platform, associated resources, and professional development activities will be further developed to broadly support both foundational writing in first-year English

Across-the-Curriculum AI-based Personalized Assistants to Support Student Success in Engineering

Transforming Engineering Education with AI — Supporting Every Student, Every Step of the Way. This project aims to develop adaptive software to 1) improve mastery of domain knowledge among engineering students, 2) improve student outcomes for all groups, and 3) reduce equity gaps. The adaptive software will take the form of a personalized assistant that coordinates content knowledge expected of students; the software will deliver that content in relation to individual student’s’ actual learning behavior, thus providing them with personalized

Improving Student Engagement and Outcomes Equitably with Course-specific Open-sourced AI tutors

Smart Learning Hub- Personalized Learning for AllThe large, lecture-based courses that characterize early STEM coursework often fail to meet the needs of learners. The general intelligence and multimodal interactive capabilities of large language models offer unprecedented opportunities for providing individualized instruction through customizable, AI-based tutors which have the potential to reduce the barriers faced by students and significantly improve learning outcomes. Leveraging SmartLearning Hub, a system being developed at UC San Diego that enables instructors to generate AI-based tutors based

GenAI Preparedness for Teaching & Learning at SF State

San Francisco State University faculty have reacted to Generative AI (GenAI) in varying ways from critical to enthusiastic. Many faculty have not engaged with GenAI at all, resulting in students seeking clarity on their course-related use of GenAI and a lack of curricular integration that leaves students unprepared for future workplace skills. Many academic departments have also not yet started evaluation and discussion of discipline impacts, curricular adaptations, and methods to consistently engage students on AI. To address faculty readiness

Cost-effective, Bespoke Adaptive Tutoring using Open Source Tools and GenAI

Despite advancements in reducing the time required to create an Intelligent Tutoring System (ITS), the process remains prohibitively expensive. Additionally, basic STEM preparation poses a challenge in California and nationwide, partly due to knowledge gaps resulting from the idiosyncratic curricular contractions during the pandemic. Our proposal addresses these problems with a series of mastery-based interventions intended to increase student performance in STEM and drive down costs of ITS to a level close to $0. The interventions utilize a free, open-source

Acquiring math prerequisites efficiently and scalably with AI

There are many students arriving at UC San Diego who are not qualifying to take the credit-bearing precalculus or calculus courses. This number has greatly increased in the last few years, and our previous solution of small courses with personalized instruction is not feasible. Our project is focused on improving progress through preparatory mathematics material where background is extremely varied and efficient progress is needed for students to advance to the credit-bearing material needed for their degree. The methods developed

AI-Assistance in Lower Division Chemistry Laboratory Course Curriculum

We have adopted Stemble, a chemistry-specific educational technology platform with AI-assisted feedback, in UC Irvine’s large lower division chemistry laboratory courses. Our project will combine discipline-specific knowledge from chemistry experts and data analysis expertise from education researchers in a holistic way to determine how Stemble’s AI-enhanced feedback supports student learning by providing 1) real time interactive feedback during lab sessions and 2) improved constructive feedback after assignment submission used by students to resubmit work. Currently, students interact with Stemble as

SCAPE: Student-centered Collaborative AI Platform for Personalized Engineering Learning Experience

This project aims to design and develop an open-source, Student-centered Collaborative AI Platform for Personalized Engineering Learning Experience (SCAPE), grounded in AI methodologies, transparent educational practices, and equity and inclusion principles. SCAPE addresses the limitations of current AI tutoring systems by prioritizing human insight, accessibility, and critical thinking. It ensures transparency and educator control, integrates human insight to provide emotional support, and carefully examines training data to minimize bias and misinformation. SCAPE guides students through problem-solving processes with detailed, step-by-step

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