Using Automatic Detection and Characterization to Measure Educational Impact of nanoHUB
datasetposted on 17.10.2018 by Michael Zentner, Nathan Denny, Krishna Madhavan, Swaroop Samek, George Bunch Adams, Gerhard Klimeck
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The science gateway and online community nanoHUB hosts over 4000 technical resources related to nanoscience and nanotechnology and online capabilities for nano community engagement. nanoHUB also hosts over 500 online simulation tools. nanoHUB serves the nano community spectrum ranging from undergraduate students to high profile researchers. In this paper, the evolution of nanoHUB online simulation is discussed along with the impact of that simulation on student behavior. With over 52,000 simulation users, the nanoHUB team is not personally aware of most new classrooms that adopt simulation in their syllabi. Yet, these classroom users feed the next generation of nano community contributors. A method is presented to detect classroom by clustering coordinated behavior among simulation users, thereby automatically detecting adoption of simulation tools in a classroom environment. Several prototypical patterns of clustered behavior are analyzed, ranging from peripheral to systemic classroom integration of simulation. Visualizations of detailed user behavior illustrate the varying behavior structures. Between the fall of 2000 and the fall of 2011, in 846 clustered behaviors have been detected. This number of classroom settings is on a continuous growth trend as nanoHUB becomes more widely adopted. A discussion on the rate of adoption of published simulation tools in clustered behaviors is presented.