'Serious games' is a term used to describe games that have a purpose beyond entertainment. Each game should include educational components to allow the player to learn as they interact with the game. Industries related to health, economics, defense, education, etc. use serious games for a variety of purposes.
Our focus is to create serious games that build skill through repetition. Repetition allows information to move from short-term to long-term memory; allowing skills to be processed at a higher level. Over time, the skill will be learned and become mastered. Currently, we are building games for college-level mathematics and computer science topics.
Frank Vahid (Ph.D. Computer Science, UC Irvine) - Personal Webpage
Frank is a UC Riverside CSE professor, an active researcher, and has also written several popular textbooks with major publishers and received many teaching awards, before co-founding zyBooks in 2012. He produced zyBooks' first materials and currently co-leads all authoring.
Joe Michael Allen (Computer Science Ph.D. Student, UC Riverside) - Personal Webpage
Joe Michael Allen is a Ph.D. student in Computer Science at the University of California, Riverside. His research interests include educational games for building skills for college-level computer science and mathematics.
Shayan Salehian (Computer Science M.S. Student, UC Riverside) - Personal Webpage
Shayan Salehian is a Master's student in Computer Science at the University of California, Riverside. His research interests lie at the intersection of machine learning and embedded systems. He also develops educational games for computer science and mathematics students.
Alex Edgcomb (Ph.D. Computer Science, UC Riverside) - Personal Webpage
Alex Edgcomb holds a Ph.D. in computer science from UC Riverside. Alex develops interactive learning material at zyBooks, a UC Riverside spin-off startup. Alex also works as a research specialist at UC Riverside, studying and publishing on the efficacy of web-native content for STEM education.
This material is based upon work supported by the National Science Foundation under Grant No.1542851. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation