Programming environments and game environments share many of the same characteristics, such as requiring their users to understand strategies and solve difficult challenges. Yet, only game designers have been able to capitalize on methods that are consistently able to keep their users engaged. Consequently, software engineers have been increasingly interested in understanding how these game experiences can be transferred to programming experiences, a process termed gamification.
In this perspective paper, we offer a formal argument that gamification as applied today is predominately narrow, placing emphasis on the reward aspects of game mechanics at the expense of other important game elements, such as framing. We argue that more authentic game experiences are possible when programming environments are re-conceptualized and assessed as holistic, serious games. This broad gamification enables us to more effectively apply and leverage the breadth of game elements to the construction and understanding of programming environments.
This paper describes the development of subsymbolic ACT-R models for the Concentration game. Performance data is taken from an experiment in which participants played the game under two conditions: minimizing the number of mismatches/turns during a game, and minimizing the time to complete a game. Conflict resolution and parameter tuning are used to implement an accuracy model and a speed model that capture the differences for the two conditions. Visual attention drives exploration of the game board in the models. Modeling results are generally consistent with human performance, though some systematic differences can be seen. Modeling decisions, model limitations, and open issues are discussed.
An article on our work in using low-level input characteristics as a mechanism for bot detection has appeared in The Abstract, the official blog of the NC State Newsroom. Bot detection is one of many possible applications in the broader research context of how computational approaches to evaluating input interactions can be leveraged in order to better understand and predict the underlying cognitive processes of a user.
If you’re interested in contributing to a related follow-up work, then please take a moment to participate in my newest research study, the Concentration Game.
This article describes the process for playing Fallout and Fallout 2 in windowed mode (that is, not full screen) successfully on Windows 7. The modifications to both Fallout and Fallout 2 apply to the non-DRM versions available at GOG.
For Fallout 1, you will need to use D3DWindower. Unfortunately, the program and Geocities site (surprise!) are in Korean or Japanese, but a badly ported English version is available if you look hard enough. Extract the files and copy them directly into the Fallout installation directory.
At this year’s Carolina Games Summit, Rogelio and I presented a talk on Introduction to Game AI Using Python. You can browse the project files for your own use (and experimentation!) at our GitHub page.