In his book, "Digital Games-based Learning," Marc Parensky identifies six key elements of games. Our work shows that these elements are surprisingly similar to the elements of learning. Based on these similarities, we have created deep learning games by wrapping game elements around traditional capping projects using an appropriate role-playing, problem-based scenario.

In many courses, instructors are now using individual focussed games for a number of purposes. These interactivities operate at the lower level of Bloom's Taxonomy and are used to review and reinforce the content. They can be played repeatedly until the desired results -- and learning -- takes place.

We have been moving games-based learning to the higher levels of learning by wrapping a traditional capping project inside a team-based, role-playing scenario that forms a deep learning game. These deep learning games, working on the discovery principle, encourage participants to work at the higher levels of learning since successful "playing" requires them to analyze, synthesize and evaluate information gleaned from course materials and readings.

The enthusiasm and excitement the deep learning game generates is obvious in the student evaluations. Comments range from "awesome" to "kick-ass fun" with one student acknowledging that the "course has become addictive, it's the first thing I check every morning". While these and other comments are a clear testament to the high fun quotient, a number of indicators also affirm that using a deep learning game increased learning beyond what was expected in a traditional capping assignment.