Live demo of the Whack a Mole Game can be found here. Updated August 16th, 2017.
Whack a Mole: By Amy Kwan (2017) in the Human Computer Interaction Lab under Dr. Regan Mandryk (Department of Computer Science, University of Saskatchewan)
This is a game (whack a mole) created in the summer (July-August) of 2017 within the Human Computer Interaction Lab at the University of Saskatchewan.
Upon becoming a summer research student awarded the Undergraduate Student Research Award (USRA) prior to my third year of my undergraduate Computer Science honors degree at the University of Saskatchewan, I was assigned to the Human Computer Interaction lab under the supervision of Dr. Regan Mandryk. I was tasked with assisting her in creating target acquisition games that would be used for HCI and mental health studies.
The goal was to create a game that combines all elements of human computer interaction, mental health, stress, Fitts' Law, and target acquisition. This game features a menu and a play screen. There are three different sizes of moles and distances that are crossed (small, medium and large), with both size of mole and distances crossed double each time to conduct studies in target acquisition. Moreover, two separate sets of data are logged onto a SQLite database externally using the Python-Flask framework, that consist of mouse activity of the user and target information of the moles displayed within the game canvas. These data sets are utilized for analysis in HCI and mental health related research.
Note: Two separate versions of this project are available, one that is more geared for logging, research and study purposes located on an external repository, and this current project, which may potentially be developed into a side recreational project/game that I will continue to contribute in the future to in order to learn more about programming principles, different programming languages, game/software development, with added gamelike features so I can enhance and hone my technical skills and knowledge of algorithms and programming.
Languages utilized: Javascript, Processing, Python and SQL (Python and SQL files not published)
Additional tools utilized: Terminal, Visual Studio Code, Photoshop CS6, DB Visualizer for SQLite