The game industry is growing. As it has expanded to include social and mobile gaming; games in health, education, and training; and innovations in play psychology, middleware, graphics tools, game mechanics, game evaluation methods, and advanced artificial intelligence and narrative techniques, it has become an increasingly competitive space.
The selectiveness of the industry and the diversity of the skills required mean that students seeking entry need both broad and deep skills. As an emergent industry using diverse technology and collaborative practices, Games needs workers with interdisciplinary skill sets that can weave knowledge about development with knowledge about evaluation methods and players’ behavior and psychology.
Jointly offered by Northeastern’s Colleges of Computer and Information Sciences and Arts, Media and Design, the MS in Game Science and Design is a one-of-a-kind interdisciplinary program that prepares students to meet this need. Weaving together science and design, the two-year, 34-credit hour program gives students a choice of three concentrations: game analytics, game user research and game design and development.
Virtual Personality Assessment Laboratory (V-PAL)
Overview: Given the popularity of games, and their use for education, health and training, there is a unique opportunity to develop games that can identify and adapt to personality differences thus increasing their success. This project, called V-PAL, aims to address this link between personality and game behavior. The goal of the project is developing a preliminary taxonomy of game-based mechanics, grounded on personality research, that allows researchers to use in-game behavioral patterns of individual players to assess their real-world personality. Such virtual personality detection mechanism can then be used by other researchers to adapt the game system further, which would be one ultimate goal – the design of more personalized and adaptive applications that may improve impact on large societal problems.
Previous research has confirmed the existence of correlations between game behavior and various models of personality and motivation. However, none of the previous works adopted personality theories to guide the design and development of a game aimed at assessing players’ personality. This is the target of this proposal. Specifically, the aim is to leverage already existing work in personality to develop a game able to detect and identify specific aspects of personality. The design of the game is driven by personality theory and validated by a wide range of personality measures such as the Need For Cognition, the California Q-Sort, the Reiss Motivation Profiler and the Five Factor Model. The game will be developed as a set of modular challenges and situations that make use of the mechanics individuated in the taxonomy. These situations are constructed to elicit personality preferences. The game will be validated through two iterations to ensure that scenarios are assimilated and that they conform to the intention of the designers. A final summative evaluation will be administered utilizing in-game data as well as various personality measures such as scores from personality questionnaires, informant interviews, and behavior coding. Correlation analysis will be used to investigate relationships between in-game choices emerging from the context of play and personality scores.
Faculty Members: Alessandro Canossa (PI), Magy Seif El-Nasr (Co-PI), and Randy Colvin (Co-PI).
Emotions and contextual individual differences
This project examines the use of virtual environment as a tool to elicit scenarios that aid in investigating emotions and individual differences.
PhD Students: Eric Anderson
Faculty: Lisa Barrett Feldman, Magy Seif El-Nasr, Alessandro Canossa
Visualization and Learning Analytics
This project seeks to develop an interactive visualization system to investigate group and individual differences in game play strategies and decision making over time.
So far the group has developed a visualization system called Glyph that shows paths through game states and how many users are going through them. Interactivity is used to allow users to isolate specific traces and see how many users took them. Thus, allowing designers to see dominant or popular strategies and not so popular ones. They can also clearly see winning vs. loosing strategies. More work is currently underway to look into separating the traces by different rewards to see individual differences and preferences.
Doctoral Fellows: Shree Durga, Truong Huy Nguyen Dinh
Faculty Members: Alessandro Canossa (PI), and Magy Seif El-Nasr (Co-PI).
The project was funded by Northeastern University Interdisciplinary Tier 1 grant.
Please visit the CAMD Graduate Studies website for detailed admission information including a listing of required application materials and answers to frequently asked questions.