Computer Science Curriculum, Faculty Achievement Highlighted at Two CT Universities
/It’s all about the sequence at one university in Connecticut. The Computer and Data Science program at the University of Saint Joseph is designed to prepare students for employment in both computer science and data science. The combination of skills is highly attractive to employers who are increasingly inclined to use data-driven and evidence-based decision-making.
As a Computer and Data Science major, students combine coursework and internship experience to gain practical skills in areas such as computer programming, application development, data analysis, data mining, and machine learning, which will give them a competitive edge in the job market.
Traditionally, students take general education courses before diving into their field of study. But beginning this fall, the University will offer a “21-Month Upside-Down Curriculum,” in which students will “jump right into field of study classes.” Under the program, within 21 months, students “will be ready to enter the workforce full or part-time while finishing General Education and Capstone requirements.”
Students will also have an opportunity to gain real-world experience, working in the USJ IT department up to 19 hours per week during the term and up to 29 hours during session breaks.
In addition to the new “upside-down” curriculum, the University will continue to offer the traditional sequence of courses for students who prefer that approach.
USJ isn’t the only Hartford area university with news to share in recent weeks.
The Association for Computing Machinery (ACM) has recognized University of Hartford Computer Science Professor Ingrid Russell as a Distinguished Member for her Outstanding Educational Contributions to Computing. ACM is world’s largest computing society and is the premiere global scientific and educational organization dedicated to advancing computing.
A member of ACM for more than 20 years, Russell, who has been a faculty member at the University of Hartford since 1985, 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.
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.”