Leveraging Crowd for Game-based Learning: A Case Study of Privacy   Education Game Design and Evaluation by Crowdsourcing
  As the Internet grows in importance, it is vital to develop methods and techniques for educating end-users to improve their awareness of online privacy. Web-based education tools have been proven effective in many domains and have been increasingly adopted by many online professional and educational services. However, the design and development of Web-based education tools for online privacy is still in the early stage. The traditional solutions always involve privacy experts who have sophisticated expertise. Such involvement can make the tool development costly. Furthermore, it is not clear how inspiring and effective these education tools are to general users of varying backgrounds, specially to novice users who have rarely dealt with online privacy issues before. In this paper, we design, develop, and evaluate a game-based privacy learning system by leveraging the wisdom of a crowd of non-experts on Amazon Mechanic Turk. Empirical study demonstrates that the crowd can provide high-quality ideas of designing and developing a practical, educational privacy learning game. 
Wendy Wang, Yu Tao, Kai Wang, Dominik Jedruszczak, Ben Knutson
cs.CY