Reasoning on the basis of diverse, dynamic, and massive data is becoming a routine aspect of many jobs. This is particularly true for the intelligence analyst, who must gather and analyze ambiguous data, and communicate time-sensitive inferences and recommendations derived from these under stressful conditions. The question is can people be trained to improve these skills? If so, there is a need for proven methods that can help strengthen our ability to reason flexibly with complex information - in other words, fluid intelligence - to make smart people smarter!
The Intelligence Advanced Research Projects Activity (IARPA), the research arm of the Office of the Director of National Intelligence, is funding a rigorous, high-quality research through a program called Strengthening Human Adaptive Reasoning and Problem-Solving (SHARP). The goal of SHARP is to advance the science on optimizing human adaptive reasoning and problem-solving, by testing and validating interventions that have the potential to significantly improve these abilities - with the goal of enhancing the cognitive performance of high-performing adults in information-rich environments.
Honeywell; Harvard University, Northeastern University, University of Oxford
One research team, headed by Honeywell asked Simcoach Games to design, develop and deliver a video game that would form a central component of their research intervention. The game, which places the player in the context of being a worker in a robot factory, was built from the ground up to engage fundamental cognitive processes that play a crucial role in fluid intelligence. Simcoach Games worked closely with leading experts from major commercial and academic research institutions to design a game closely aligned with current scientific theory but, also a game that would provide endless variety and entertainment over the span of several weeks of training.
Robot Factory is currently being used in active experiments at Harvard, Northeastern and Oxford to test validity of the approach.
"Simcoach Games brought three elements that impressed every member of our interdisciplinary research team: First, an unwavering focus on the intent behind the game - evident when it came to generating requirements that satisfied scientific constraints, or prolonged fine tuning of the game - to create an effective training intervention; second, the creative talent to create a delightful experience combining humor, delightful artwork, and deeply engaging themes; third, outstanding software engineering talent to implement the game iteratively, and fast - with a beautifully abstracted architecture that made it possible to adapt and improve the game iteratively and quickly from experience."