A "Cone of Uncertainty" has become ubiquitous in hurricane forecasting, encompassing the likeliest possible path that a storm might take as it approaches landfall. These forecasts are crucial because they help government agencies at all levels prepare even in these far-from-certain future conditions. Although individual institutions have…

Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important where the past is…

Sentiment Analysis is a field of Natural Language Processing which aims at classifying the author's sentiment in text. This paper first describes a sentiment analysis model for students' comments about professor performance. The model achieved impressive results for comments collected from student surveys conducted at a private university in…

The purpose of this study is to evaluate the implementation and impacts of the Building Assets, Reducing Risks (BARR) model in its first year of implementation in 66 schools across the U.S. and to document scale-up progress during the Investing in Innovation (i3) grant period (2017-2021). The impact evaluation included 21,529 9th grade students…

Schools face enormous challenges regarding how to operate efficiently and safely for the 2020-21 school year. As part of that response, some state leaders are asking the U.S. Department of Education to waive the annual federal testing and accountability requirements for 2021, which are key to understanding and addressing gaps in education among…