Institution
Worcester Polytechnic Institute
Education•Worcester, Massachusetts, United States•
About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.
Topics: Computer science, Population, Data envelopment analysis, Nonlinear system, Finite element method
Papers published on a yearly basis
Papers
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TL;DR: In this article, a lean clay was stabilized with metakaolin-based geopolymer at different concentration (ranging from 3 to 15% of unstabilized soil at its optimum water content) to examine the feasibility of applying geopolymers in stabilizing soils.
304 citations
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TL;DR: The author argues that firms should balance the natural process of tight coupling with a deliberate effort at loose coupling, and draws implications for further research on the organization-environment interface.
Abstract: This article argues that tight linkages with customers present a paradox for the firm. The research question of this study is: What is the behavioral and cognitive process by which a firm establishes close links with its customers, and how can this process be both beneficial and detrimental? Existing theory and data from apparel retailers suggest that firms forge these tight links by enacting their customer environment. In the process of enactment, cognitions and actions reinforce each other and become increasingly focused. The tight coupling generated through enactment comes at the price of increased commitment and restricted vision. The author argues that firms should balance the natural process of tight coupling with a deliberate effort at loose coupling, and draws implications for further research on the organization-environment interface. Copyright © 2003 John Wiley & Sons, Ltd.
302 citations
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TL;DR: With increasing research on system integration for image‐guided therapy (IGT), there has been a strong demand for standardized communication among devices and software to share data such as target positions, images and device status.
Abstract: Background With increasing research on system integration for imageguided therapy (IGT), there has been a strong demand for standardized communication among devices and software to share data such as target positions, images and device status.
301 citations
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TL;DR: The results show that the ASSISTment system can do a reliably better job predicting student end-of-year exam scores by leveraging the interaction data, and the model based on only the interaction information makes better predictions than the traditional assessment model that uses only information about correctness on the test items.
Abstract: Secondary teachers across the United States are being asked to use formative assessment data (Black and Wiliam 1998a,b; Roediger and Karpicke 2006) to inform their classroom instruction. At the same time, critics of US government's No Child Left Behind legislation are calling the bill "No Child Left Untested". Among other things, critics point out that every hour spent assessing students is an hour lost from instruction. But, does it have to be? What if we better integrated assessment into classroom instruction and allowed students to learn during the test? We developed an approach that provides immediate tutoring on practice assessment items that students cannot solve on their own. Our hypothesis is that we can achieve more accurate assessment by not only using data on whether students get test items right or wrong, but by also using data on the effort required for students to solve a test item with instructional assistance. We have integrated assistance and assessment in the ASSISTment system. The system helps teachers make better use of their time by offering instruction to students while providing a more detailed evaluation of student abilities to the teachers, which is impossible under current approaches. Our approach for assessing student math proficiency is to use data that our system collects through its interactions with students to estimate their performance on an end-of-year high stakes state test. Our results show that we can do a reliably better job predicting student end-of-year exam scores by leveraging the interaction data, and the model based on only the interaction information makes better predictions than the traditional assessment model that uses only information about correctness on the test items.
298 citations
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22 Oct 1994TL;DR: This paper analyzes the initial phases of a large-scale custom software effort, the Worm Community System (WCS), a collaborative system designed for a geographically dispersed community of geneticists, and characterize these as levels of infrastructural complexity which challenge both users and developers.
Abstract: This paper analyzes the initial phases of a large-scale custom software effort, the Worm Community System (WCS), a collaborative system designed for a geographically dispersed community of geneticists. Despite high user satisfaction with the system and interface, and extensive user feedback and analysis, many users experienced difficulties in signing on and use, ranging from simple lack of resources to complex organizational and intellectual trade-offs. Using Bateson's levels of learning, we characterize these as levels of infrastructural complexity which challenge both users and developers. Usage problems may result from different perceptions of this complexity in different organizational contexts.
296 citations
Authors
Showing all 6336 results
Name | H-index | Papers | Citations |
---|---|---|---|
Andrew G. Clark | 140 | 823 | 123333 |
Ming Li | 103 | 1669 | 62672 |
Joseph Sarkis | 101 | 482 | 45116 |
Arthur C. Graesser | 95 | 614 | 38549 |
Kevin J. Harrington | 85 | 682 | 33625 |
Kui Ren | 83 | 501 | 32490 |
Bart Preneel | 82 | 844 | 25572 |
Ming-Hui Chen | 82 | 525 | 29184 |
Yuguang Fang | 79 | 572 | 20715 |
Wenjing Lou | 77 | 311 | 29405 |
Bernard Lown | 73 | 330 | 20320 |
Joe Zhu | 72 | 231 | 19017 |
Y.S. Lin | 71 | 304 | 16100 |
Kevin Talbot | 71 | 268 | 15669 |
Christof Paar | 69 | 399 | 21790 |