by Margaret Mahan | at MinneBar 11 | 10:50 – 11:40 in Challenge | View Schedule
College: For the 2014-2015 academic year at the University of Minnesota, 64 MS and 27 PhDs in computer science were earned r1. Across all University of Minnesota graduate programs, this turns out to be < 2% of total MS and ≅3% of PhDs earned; 22 graduate degrees in computer science were earned by females. Minnesota has 14,420 open computing jobs but had only 796 computer science graduates in 2014 r2; 14% were female.
High school: In 2015, 666 high school students in Minnesota took the AP computer science exam; 20% were female, 14 were Hispanic, and 10 were Black r2. Only 13% of Minnesota schools with AP programs offered the AP computer science course in 2014-2015. Minnesota does not allow computer science to count as a mathematics or science admission requirement at institutions of higher education. Minnesota does not require that all schools offer computer science.
Yep – that’s the same pattern you’ve been hearing for years. We know computer science is foundational yet we continue to underprepare our students for high school and college level computer science. In this presentation, you’ll hear the latest status for computer science education in Minnesota, why we need to start computer science education early, and what programs are aiming to fill the current gaps. You’ll also hear from SuPoCo, a Technovation[MN] team, (Allie Nordeen, Annalee Kester, Gracie Marek, and Kali Jarrard) r3, about their experience (panel format). Lastly, you will learn what you can do to help and resources to get you started.
Margaret is a scientist (data, computer, neuro, & network) at the Minneapolis Medical Research Foundation working in Dr. Samadani's Brain Injury Research Lab and also pursuing a PhD in Biomedical Informatics and Computational Biology at the University of Minnesota. She has obtained an MS in Computer Science from the University of Minnesota and a BA in Biology and Psychology from Metropolitan State University. Her research falls primarily in the area of brain connectivity, with an emphasis on developing analytical methods for integrating data from multimodal sources.
