Computer Science Education Research

Our Computer Science Education Research program prioritizes inclusivity and diversity to provide equitable access to computer science learning for students from various backgrounds. It offers a comprehensive curriculum, teacher training and resources that cater to diverse populations, emphasizing the importance of digital literacy and computational thinking. The program encourages underrepresented groups to engage in coding, problem-solving and technology exploration, fostering a more inclusive and empowered generation of young learners in the field of computer science.

 

Academics and Coursework

Our Computer Science Education Research program has exceptional certificate and continuing education programs aimed at enhancing CS skills and literacy, preparing a diverse workforce for the evolving field of computing. In addition to broader requirements for a CS undergraduate or graduate degree, students may specialize their education around Computer Science Education Research topics via these undergraduate and graduate level courses, minors, and certificate programs:

  • CSC 699: Learning by Teaching
  • CSC 699: Computational Thinking
  • CSC 309: Computer Programming
  • CSC 645: Computer Networks
  • CSC 305: Impacts of Computing
  • CSC 698: Software Development and Pedagogy
  • CSC 209: Introduction to Programming using Python
  • CSC 306: An Interdisciplinary Approach to Computer Programming
  • CSC 219: Data Structure for Data Science Application Development
  • CSC 308: Introduction to Machine Learning for Data Scientists
  • CSC 508: Machine Learning and Data Science for Personalized Medicine
  • CSC 509: Data Science and Machine Learning for Medical Image Analysis
  • CSC 308: Introduction to Machine Learning for Data Scientists
  • CSC 508: Machine Learning and Data Science for Personalized Medicine
  • CSC 509: Data Science and Machine Learning for Medical Image Analysis
  • CSC 601: Data Science and Machine Learning for Biotechnology Seminar Series
  • CSC 602: Interview Preparation for Data Science and Machine Learning for Biotechnology

Faculty and Focus Areas

Hao Yue

K-12 CS education, inclusive pedagogy, broaden participation in K-16 CS education

Anagha Kulkarni

PI of the Data Science and Machine Learning for Biotechnology Certificate Program (gSTAR Certificate) and the Artificial Intelligence Scholarships that Improve Academic Achievement, Retention, and Career Success (AI-STAARS) Program

Ilmi Yoon

Inclusive computing (Promoting Inclusivity in Computing, PINC), Computing Application Minor, Data Science and Machine Learning for Biotechnology, socially responsible computing