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.

Context-Aware Attentive Knowledge Tracing

Abstract: Knowledge tracing (KT) refers to the problem of predicting future learner performance given their past performance in educational applications. Recent developments in KT using flexible deep neural network-based models excel at this task. However, these models often offer limited interpretability, thus making them insufficient for personalized learning, which requires using interpretable feedback and actionable recommendations to help learners achieve better learning outcomes. In this paper, we propose attentive knowledge tracing (AKT), which couples flexible attention-based neural network models with a series of novel, interpretable model components inspired by cognitive and psychometric models. AKT uses a novel monotonic attention mechanism that relates a learner's future responses to assessment questions to their past responses; attention weights are computed using exponential decay and a context-aware relative distance measure, in addition to the similarity between questions. Moreover, we use the Rasch model to regularize the concept and question embeddings; these embeddings are able to capture individual differences among questions on the same concept without using an excessive number of parameters. We conduct experiments on several real-world benchmark datasets and show that AKT outperforms existing KT methods (by up to $6%$ in AUC in some cases) on predicting future learner responses. We also conduct several case studies and show that AKT exhibits excellent interpretability and thus has potential for automated feedback and personalization in real-world educational settings.

Tactical supply chain planning models with inherent flexibility: definition and review

Abstract: Supply chains (SCs) can be managed at many levels. The use of tactical SC planning models with multiple flexibility options can help manage the usual operations efficiently and effectively, whilst improve the SC resiliency in response to inherent environmental uncertainties. This paper defines tactical SC flexibility and identifies tactical flexibility measures and options for development of flexible SC planning models. A classification of the existing literature of SC planning is introduced that highlights the characteristics of published flexibility inclusive models. Additional classifications from the reviewed literature are presented based on the integration of flexibility options used, solution methods utilized, and real world applications presented. These classifications are helpful for identifying research gaps in the current literature and provide insights for future modeling and research efforts in the field.

Theoretical Foundations of Information Visualization

Abstract: The field of Information Visualization, being related to many other diverse disciplines (for example, engineering, graphics, statistical modeling) suffers from not being based on a clear underlying theory. The absence of a framework for Information Visualization makes the significance of achievements in this area difficult to describe, validate and defend. Drawing on theories within associated disciplines, three different approaches to theoretical foundations of Information Visualization are presented here: data-centric predictive theory, information theory, and scientific modeling. Definitions from linguistic theory are used to provide an over-arching framework for these three approaches.