The primary goal of the authentic learning approach is to engage and motivate students in learning real world problem solving. We report our experience in developing k-nearest neighbor (KNN) classification for anomaly user behavior detection, one of the authentic learning modules based on 10 cybersecurity cases with machine learning solutions. All portable labs are made available on Google CoLab. So students can access and practice these hands-on labs anywhere and anytime without software installation and configuration which will engage students in learning of concepts and getting more experience for hands-on problem solving skills.
Zhen Wu Computer Science Department, University of Pittsburgh, Amanda Buddemeyer Learning Research & Development Center and School of Computing and Information, University of Pittsburgh, Erin Walker University of Pittsburgh, Angela Stewart Computer Science Department, University of Pittsburgh
Xiaoxue Du MIT Media Lab, Robert Parks Massachusetts Institute of Technology, Selim Tezel Massachusetts Institute of Technology, Jeff Freilich Massachusetts Institute of Technology, Nicole Pang Massachusetts Institute of Technology, Hal Abelson Massachusetts Institute of Technology, Cynthia Breazeal Massachusetts Institute of Technology