The neurocognitive basis of knowledge acquisition: Building better brains
Abstract
The proposed research will neurally assess how well new technical knowledge is learned from on-the-job instructional text, as a function of individual differences in cognitive abilities, prior knowledge, and neural processing capabilities. The project leverages previous advances in unraveling brain coding of single concepts to enable the neural assessment of the knowledge gained from a short technical passage. The goal of this research is to determine the structure of new conceptual knowledge that is being learned, and its variation across people as a function of their abilities, previous knowledge, and method of instruction. The proposed research builds on the remarkable ability to link the fMRI-measured neural signature of a thought to the content of the thought. The fMRI activation patterns are systematic (reliably repeatable) and decomposable into elements of meaning. Moreover, they are similar across people, even if they are speakers of different languages, because the patterns conform to a universal language of the brain. The components of that “brain language” are the codes in each of the brain’s subsystems, such as a motor code, a social code, a perceptual code, etc. For example, one of the brain’s component codes for the concept of a screwdriver is the motor code for how one holds and twists a screwdriver. One component of the research will find the determinants of how well declarative knowledge is learned from a text by individual learners, such as the knowledge of how a mechanical system works. Another component will analogously find the determinants of procedural learning from a text, such as a computer coding procedure. A third component of the research will compile a “neural thought library” of 1000 frequent technical concepts, determine its main underlying dimensions of organization, and test its ability to predict the neural coding of new knowledge. The resulting understanding of technical knowledge learning will be applicable to the design of instructional materials and to personnel selection for technical specializations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 31, 2020
- Source ID
- N000142012625
Entities
People
- Marcel Just
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Navy