Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Population & Data envelopment analysis. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

Understanding organization-enterprise system fit: a path to theorizing the information technology artifact

Abstract: Packaged software applications such as enterprise systems are designed to support generic rather than specific requirements, and hence are likely to be an imperfect fit in any particular instance. Using critical realism as our philosophical perspective, we conducted a three-year qualitative study of misfits that arose from an enterprise system (ES) implementation. A detailed analysis of the observed misfits resulted in a richer understanding of the concept of fit and of the ES artifact itself. Specifically, we found six misfit domains (functionality, data, usability, role, control and organizational culture) and within each, two types of misfit (deficiencies and impositions). These misfit types correspond to two newly defined types of fit: fit as coverage and fit as enablement. Our analysis of fit also revealed a new conceptualization of the ES artifact, with implications for IT artifacts in general.

On the leakage of personally identifiable information via online social networks

Abstract: For purposes of this paper, we define "Personally identifiable information" (PII) as information which can be used to distinguish or trace an individual's identity either alone or when combined with other information that is linkable to a specific individual. The popularity of Online Social Networks (OSN) has accelerated the appearance of vast amounts of personal information on the Internet. Our research shows that it is possible for third-parties to link PII, which is leaked via OSNs, with user actions both within OSN sites and else-where on non-OSN sites. We refer to this ability to link PII and combine it with other information as "leakage". We have identified multiple ways by which such leakage occurs and discuss measures to prevent it.

A review of recent advances in learner and skill modeling in intelligent learning environments

Abstract: In recent years, learner models have emerged from the research laboratory and research classrooms into the wider world. Learner models are now embedded in real world applications which can claim to have thousands, or even hundreds of thousands, of users. Probabilistic models for skill assessment are playing a key role in these advanced learning environments. In this paper, we review the learner models that have played the largest roles in the success of these learning environments, and also the latest advances in the modeling and assessment of learner skills. We conclude by discussing related advancements in modeling other key constructs such as learner motivation, emotional and attentional state, meta-cognition and self-regulated learning, group learning, and the recent movement towards open and shared learner models.