31 research outputs found
The effect of scoring and feedback mechanisms in an online educational game
A research and development (R&D) team designed and developed the BiblioBouts online information literacy game to give undergraduate students opportunities to learn and practice information literacy skills using online library research tools and scholarly databases while they work on a research‐and‐writing assignment. To evaluate the alpha version of BiblioBouts, the R&D team analyzed game‐play logs from two undergraduate classes and invited students who played the game in class to participate in focus group interviews. The resulting insights into the impact of scoring and game feedback on student game play were used to help instructors plan for game play in their classes and to help the R&D team improve BiblioBouts. These results also spawned game premises to guide the R&D team and other designers of educational games build better games.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90098/1/14504801038_ftp.pd
The genetic architecture of the human cerebral cortex
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder
The genetic architecture of the human cerebral cortex
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder
Criminal Intent, with Special Reference to Liability of Master Criminally, for Willful Acts of His Servants
A multi-fidelity machine learning approach to high throughput materials screening
AbstractThe ever-increasing capability of computational methods has resulted in their general acceptance as a key part of the materials design process. Traditionally this has been achieved using a so-called computational funnel, where increasingly accurate - and expensive – methodologies are used to winnow down a large initial library to a size which can be tackled by experiment. In this paper we present an alternative approach, using a multi-output Gaussian process to fuse the information gained from both experimental and computational methods into a single, dynamically evolving design. Common challenges with computational funnels, such as mis-ordering methods, and the inclusion of non-informative steps are avoided by learning the relationships between methods on the fly. We show this approach reduces overall optimisation cost on average by around a factor of three compared to other commonly used approaches, through evaluation on three challenging materials design problems.</jats:p