Research and policy changes over the recent years have brought a newfound focus on STEM for young children. Policy decisions regarding how and when to introduce computer science education would benefit from additional data. This project will investigate the cognitive and neural basis of learning computer science in early childhood. The project will use functional MRI to evaluate the novel hypothesis that engaging in programming activities can be similar to engaging in language comprehension and production. This project comes at a time when there is a re-envisioning of STEM in early childhood education as well as a push for integrating coding at all levels of the educational system. This empirical project will provide critical insights into the cognitive and neural basis of programming, which is key for furthering the goal to bring computer science for all and the design of learning technologies for young children.
This interdisciplinary project will focus on understanding the cognitive and neural basis of computer programming in young children. Since computer programming is traditionally associated with problem solving it is taught as a STEM discipline. However, the underlying assumption that programming abilities are related to math and general problem solving skills has not gone unchallenged. Some researchers proposed that learning a programming language may also be related to the cognitive processes associated with literacy, akin to acquiring a foreign language. In this interdisciplinary project the research team will use functional MRI to evaluate whether engaging in coding and computational thinking primarily activates the domain-general problem-solving brain regions (the fronto-parietal multiple demand network), and whether it additionally engages the fronto-temporal language network. The team will ask this question by conducting a pilot study with children 8 years of age programming with ScratchJr, an introductory programming language developed by the PI. Understanding whether engaging in computer programming primarily relies on domain-general problem-solving resources or whether it additionally engages language processing mechanisms, will provide critical insights into the cognitive and neural basis of programming, which is needed for understanding learning trajectories in computational thinking, developing effective learning technologies, and making policy recommendations for incorporating the teaching of computer science.