News Service, Kevin Brown

Perry Samson

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I developed LectureTools with NSF support in response to a need to increase opportunities for student participation in larger lecture courses. It was subsequently spun off campus using NSF SBIR funding and was acquired by Echo360 which has incorporated it into its Active Learning Platform (ALP).  ALP collects data on how students behave before, during and after class including how many slides they view, how many notes they type, how many questions they answer and how many gradable questions they get correct as well as what question they pose and how often do they indicate confusion.

These unique data are used to understand how student participation is related to exam grades and to build models to forecast which students will have trouble in class far earlier in the semester.  My goal is to combine data from ALP with other data sets to ascertain which, if any, participation data allows the best prediction of student success.

Exam grades as a function of the number of words typed in students notes.

Exam grades as a function of the number of words typed in students notes.

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Quentin Stout

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I primarily work on developing scalable parallel algorithms to solve large scientific problems. This has been done with teams from several different disciplines and application areas. I’m most concerned with algorithms emphasizing in-memory approaches. Another area of research has developed serial algorithms for nonparametric regression. This is a flexible form of regression that only assumes a general shape, such as upward, rather than a parametric form such as linear. It can be applied to a range of learning and classification problems, such as taxonomy trees. I also work some in adaptive learning, designing efficient sampling procedures.