Collaborative Research: Deep Insights Anytime, Anywhere (DIA2) - Central Resource for Characterizing the TUES Portfolio through Interactive Knowledge Mining and Visualizations
Collaborative Research: Deep Insights Anytime, Anywhere (DIA2) - Central Resource for Characterizing the TUES Portfolio through Interactive Knowledge Mining and Visualizations
批准号:
1123108
负责人:
Krishna Madhavan
金额:
$130.75万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-15 至 2017-08-31
中文摘要
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英文摘要
LEAD INSTITUTION: Purdue UniversityCOLLABORATORS: Arizona State University, Stanford University and Virginia Polytechnic Institute and State UniversityPROJECT DESCRIPTIONThis TUES Central Resource Project is designed to help those engaged in improving STEM education to synthesize knowledge produced through NSF investments through a web-based knowledge mining and interactive visualization platform. The Deep Insights Anytime, Anywhere (DIA2) project allows users (e.g., current and potential principle investigators, NSF/TUES program staff, and administrators at academic institutions) to interactively mine, synthesize, and visualize data at a scale that is not possible with currently available tools. DIA2 is based upon a more narrowly scoped Interactive Knowledge Networks for Engineering Education Research (iKNEER) prototype that targeted the engineering education research community, expanding the functionality by an order of magnitude in scale; integrating newer approaches in data mining and visualization into a fully deployed system. The project has three major goals: (1) Empower the TUES community to leverage TUES investments by understanding the knowledge hidden within its networks; (2) Develop and apply cutting-edge, large-scale knowledge mining and visualization techniques for characterizing the portfolio of TUES and predecessor programs; and (3) Leverage social media optimization and integration to catalyze diffusion of TUES innovations, build a community and sustain the project impact. DIA2 enables users to explore massive amounts of data and make sense of it using a highly intuitive process. The system development approach combines theories of user-centered design, large-scale data mining, community formation, social network analysis, and interactive visualization. The project's evaluation plan includes both formative and summative approaches for documenting, testing, measuring, and sharing community outcomes, internal team working, and system performance.BROADER SIGNIFICANCEDIA2 offers a framework for understanding and characterizing the TUES program along with its predecessor programs. It makes data available to a large community of TUES users and allows them to analyze the portfolio to garner an understanding of how ideas are adopted by others in the community. It allows current and future PIs, NSF program officers and administrators at academic institutions to identify best practices and explore synergistic projects in their environments. Since DIA2 is a knowledge portal, it provides a unique opportunity to showcase work undertaken at underserved and underprivileged institutions in new and novel ways. The project team is employing a methodology that attempts to understand the needs of these communities, in order to better address the DIA2 system design requirements. Ultimately, DIA2 is focused on providing knowledge that will allow the community to increase the impact of NSF STEM investments that improve student learning.
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