Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…

Qualitative data offer advantages to evaluators, including rich information about stakeholders' perspectives and experiences. However, qualitative data analysis is labor-intensive and slow, conflicting with evaluators' needs to provide punctual feedback to their clients. In this method note, we contribute to the literature on rapid evaluation and…

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…

Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in…

Any librarian who has managed electronic resources has experienced the--for want of words--"joy" of gathering and analyzing usage statistics. Such statistics are important for evaluating the effectiveness of resources and for making important budgeting decisions. Unfortunately, the data are usually tedious to collect, inconsistently organized, of…

In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

Today, collecting, evaluating, and analyzing data--the basic concepts of scientific study--usually involves electronic probeware. Probeware combines sensors that collect data with software that analyzes it once it has been sent to a computer or calculator. Science inquiry has benefited greatly from the use of electronic probeware, providing…