As part of our NSF funded collaborative project on Data Sharing within Engineering Education Community, we conducted an empirical study to better understand the current climate of data sharing and participants' future expectations of the field. We present findings of this mixed method study and discuss implications. Overall, we found strong…

In this work we introduce the system for adaptive practice of foundations of mathematics. Adaptivity of the system is primarily provided by selection of suitable tasks, which uses information from a domain model and a student model. The domain model does not use prerequisites but works with splitting skills to more concrete sub-skills. The student…

District and state data systems are constructed to ensure that individuals can access only the data that are appropriate for their role. Still, questions from the public about how these data systems work and how student privacy is protected have been increasing. A recurring concern is the feared existence of a "permanent record"--a…

Ecosystem health is deteriorating in many parts of the world due to direct and indirect anthropogenic pressures. Generating accurate, useful, and impactful models of past, current, and future states of ecosystem structure and function is a complex endeavor that often requires vast amounts of data from multiple sources and knowledge from…

Networks, such as social networks, are a universal solution for modeling complex problems in real time, especially in the Big Data community. While previous studies have attempted to enhance network processing algorithms, none have paved a path for the development of a persistent storage system. The proposed solution, GraphStore, provides an…

While the field of educational data mining (EDM) has generated many innovations for improving educational software and student learning, the mining of student data has recently come under a great deal of scrutiny. Many stakeholder groups, including public officials, media outlets, and parents, have voiced concern over the privacy of student data…

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now…

The Exploring Engagement Fund provides risk capital for arts nonprofits to experiment with innovative ideas about how to engage diverse Californians. In order to understand the variety of Californians engaged in arts experiences, this guide is intended to support current and future Fund grantees in collecting participant information. Exploring…

The latest data alert: By 2020, the amount of data generated daily will reach 40 zettabytes, or roughly 5,247 gigabytes for every person on earth. That's one of the findings in a new report published by IT industry analysts at IDC. The study casts doubt on the ability to capture the value of all this data, especially since schools barely tapped…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

This report describes the methodologies and results of the third follow-up Education Longitudinal Study of 2002 (ELS:2002/12) field test which was conducted in the summer of 2011. The field test report is divided into six chapters: (1) Introduction; (2) Field Test Survey Design and Preparation; (3) Data Collection Procedures and Results; (4) Field…

This publication provides an overview of the current federal opportunities to help states advance their data-related activities. Although not exhaustive, this list provides a starting point for federal policymakers to support states' work in this area.

Many traditional organic chemistry lab courses do not adequately help students to develop the professional skills required for creative, independent work. The overarching goal of the new organic chemistry lab series at Seattle University is to teach undergraduates to think, perform, and behave more like professional scientists. The conversion of…