Individual Differences in Complex Skill Learning: Relating Natural Language Learning to Learning Programming Languages
Abstract
This proposal extends an existing program of research funded by CSOL entitled Learning Complex Cognitive Skills: Bridging Neuroscience and Education through Individual Differences Research. One of the most recent, and novel findings of this research is that the neurocognitive predictors of natural language learning in adulthood predicted up to 72% of the variance in learningto program in Python. Among these predictors were characterizations of resting-state brain activity, which provided tremendous predictive utility both for learning natural languages and learning to program in Python, with both considerable overlap and differences in the predictors of each skill. These findings are both novel and important, as the ability to program computers has moved from a niche skill to one that is of increasing centrality to all fields of science andtechnology. Over the past decade, the nature of programming languages has also rapidly evolved, and many have come to increasingly resemble the structure and form of natural languages. Thus, the goal of this new proposal will be to extend our understanding of the similarities and differences in the neurocognitive bases of learning to program and learning natural languages. In doing so, we will continue to adopt a neuropsychometric approach, extending our ability to map characteristics of individual brains at rest to complex skill learning. Four interrelated aims will be addressed: (1) to investigate the role of natural language experience on learning to program; (2) to explore theextent to which language-based pre-training versus non-linguistic programming pre-training may facilitate learning to program in Python, (3) to compare the neurocognitive predictors of learning programming languages that vary in their structural similarity to natural languages (e.g., R versus Python); and (4) to understand the degree of specificity versus generality of neurocognitivemeasures of language aptitude. The results of this proposed program of research will significantly increase our understanding of the nature of individual differences in learning computer programming languages. They will also more broadly facilitate our efforts to improve both assessment and training of complex skills.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 17, 2020
- Source ID
- N000142012393
Entities
People
- Chantel Spring Prat
Organizations
- Office of Naval Research
- United States Navy
- University of Washington