Guest Editors
Narges Norouzi, University of California, Santa Cruz, USA, nanorouz@ucsc.edu
Bita Akram, North Carolina State University, North Carolina, USA, bakram@ncsu.edu
Editors' Message
We are very pleased to welcome you to this special issue of EngageCSEdu Open Educational Resources (OERs) on Artificial Intelligence (AI), Data Science (DS), and Machine Learning (ML). The confluence of AI, DS, and ML is an emerging discipline that combines statistics and computer science tools to develop methodologies that can extract knowledge from data to support discovery and decisions. DS has broad applications, including technology and sciences (natural and social), and has the potential to offer meaningful and welcoming pathways to Science, Technology, Engineering, and Mathematics (STEM). This special issue aims to support and broaden students’ and instructors’ access to AI, DS, and ML curricula.
A call for OERs was distributed in the Fall of 2021, seeking 1) standard assignments to reinforce course-specific topics (such as search, CSP, MDP, RL, NN, CNN, etc.), 2) course projects, 3) engaging tournaments, 4) active learning exercises, 5) engaging lecture slides, 6) labs and 7) tutorials. After a double anonymous peer review, we accepted three submissions to this special issue of EngageCSEdu on Artificial Intelligence, Data Science, and Machine Learning. Accepted OERs are available for download on the EngageCSEdu website.
- AI: Informed Search to Navigate the Subway by Dr. Brian O'Neill (Western New England University) is an assignment that uses a subway map to teach students how to implement different informed and uninformed search strategies. (https://dl.acm.org/doi/book/10.1145/3564622)
- AI: Connect Four Agent by Dr. Brian O'Neill (Western New England University) is a tournament project using minimax and alpha-beta pruning to build a competitive connect four-playing agent. (https://dl.acm.org/doi/book/10.1145/3554916)
- Two POGIL Activities on Search Concepts and Strategies by Dr. Clif Kussmaul (Green Mango Associates) is a set of Process Oriented Guided Inquiry Learning (POGIL) active learning exercises in a lab or lecture. (https://dl.acm.org/doi/book/10.1145/3554914)
To conclude, we invite you to visit the EngageCSEdu Website, https://www.engage-csedu.org/ where you will find all the OERs of this special issue and several other OERs on computer science education. We hope you’ll enjoy reading this special issue and that it will inspire your teaching and pedagogy.