Marketing analytics students who can communicate effectively with decision makers are in high demand. These "analytic unicorns" are hard to find. The Master of Science in Customer Analytics (MSCA) degree program at Xavier University seeks to fill that need. In this paper, we discuss the process of creating the MSCA program. We outline…

This discussion paper explores the possibilities and risks that data linkage presents for the vocational education and training (VET) sector. Along with a broad overview of the nature of data linkage, it highlights possible applications for data linkage in the VET sector and examines the key challenges associated with its use. A number of case…

In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

This case study describes an experience of using constructivist grounded theory to analyze data. The project investigated how high school students improved their approaches to learning mathematics. Over 4 months, students participated in processes which supported their learning while simultaneously generating data, including interactive writing,…

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…

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…

This article presents Python codes that can be used to extract data from Securities and Exchange Commission (SEC) filings. The Python program web crawls to obtain URL paths for company filings of required reports, such as Form 10-K. The program then performs a textual analysis and counts the number of occurrences of words in the filing that…

E-business, e-education, e-government, social media, and mobile services generate and capture trillions of bytes of data every second about customers, suppliers, employees, and other types of data. The growing quantity of big data is an important part of every sector in the global economy. However, there is a significant shortage of business data…

This paper aims to introduce an activity for teachers to assist in meeting learning outcomes as defined in the earth and environmental science units of the Australian Curriculum. The focus of the classroom tasks is on a global ocean feature referred to as El Niño. This phenomenon is part of the El Niño Southern Oscillation, which is largely…

Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS scores of 34 companies (clients) dealing with similar businesses in the US and Canada. With the given…

Reflecting the inter-connected reality of today's world, contemporary education is striving to keep up with the exponentially rapid changes that individuals around the globe are facing. Innovative educational proposals carry labels such as connective learning (Downes, 2006), e-learning 2.0 (Downes, 2005), education 2.0 (Carr et al., 2008), or…

The emerging large datasets have made efficient data processing a much more difficult task for the traditional methodologies. Invariably, datasets continue to increase rapidly in size with time. The purpose of this research is to give an overview of some of the tools and techniques that can be utilized to manage and analyze large datasets. We…

An increasingly common pattern is for newly-released web applications to succumb to a "Success Disaster". In this scenario, overloaded database machines and resultant high response times destroy a previously good user experience, just as a site is becoming popular. Unfortunately, the data independence provided by a traditional relational…

This paper describes a survey of data practices given to the Purdue College of Agriculture. Data practices are a concern for many researchers with new governmental funding mandates that require data management plans, and for the institution providing resources to comply with these mandates. The survey attempted to answer these questions: What are…