A member of ACM for more than 20 years, Russell was acknowledged for her outstanding and innovative contributions to computer science education research and her expertise in developing curricular models for artificial intelligence (AI), computer science education, as well as evaluating the effectiveness of these models. Her groundbreaking work is on the innovative Machine Learning Experiences in Artificial Intelligence (MLeXAI) curriculum model. MLeXAI takes a unique approach of using machine learning as a unified theme to link AI topics in theoretical aspects, and more importantly, through implementations and applications. This was a significant step forward in computing education and artificial intelligence education. MLeXAI has been since implemented and adapted by many researchers worldwide, adding to the body of knowledge and creating a community of researchers around it.
Russell has had more than 100 articles published and her work has been funded by several highly competitive grants from the National Science Foundation (NSF). Currently, Russell is studying the role of bias and fairness in AI systems and how they can influence self-learning. “I plan to incorporate these areas into my MLeXAI model and plan to apply for additional NSF grants to support this work and to have students participating in this research, as was the case with the NSF-funded MLeXAI project.”
Russell joined UHart in 1985 and teaches a variety of courses in computer science that span first-year to senior level courses, including upper-level courses in artificial intelligence, programming languages, and software engineering. She says UHart’s small size classes allow for a variety of teaching strategies to meet the students’ learning needs and allows her to develop relationships with students “Students come to UHart with mixed levels of ability and varying learning styles,” she says. “Helping these students move forward and seeing them succeed is both a challenge and a reward.”
In addition to using the MLeXAI model in teaching artificial intelligence courses, Russell says she uses a variety of innovative teaching practices including active learning, and the student-centered Process Oriented Inquiry Learning (POGIL) methodology that allows students to develop research skills by working in teams.