Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…

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,…

Most distance learning institutions collect vast amounts of learning data. Making sense of this 'Big Data' can be a challenge, in particular when data are stored at different data warehouses and require advanced statistical skills to interpret complex patterns of data. As a leading institute on learning analytics, the Open University UK instigated…

In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…

Challenging the "bridge metaphor" theme of this conference, this article contends that current practice-research integration strategies are more like research-to-practice "pipelines." The purpose of this article is to demonstrate the potential of clinical data-mining studies conducted by practitioners, practitioner-oriented PhD…

Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student…

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…

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…

Numeracy in schools is becoming an increasingly important part of mathematics learning and teaching. This is because educators want students to engage with mathematical concepts more deeply, use mathematics to make sense of their environment and make decisions that are based on the analysis of mathematical information. In order to be numerate,…

The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…

This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…

The interpretation of single-case data requires systematic visual analysis across and within conditions. Graphs are a vital component for analyzing and communicating single-case design data and a necessary tool for applied researchers and practitioners. Several articles have been published with task analyses for graphing data with the new versions…

The implementation of the Common Core State Standards (CCSS) over the coming years will provide an opportunity for K-12 and postsecondary educators to share and use data effectively to support alignment between the sectors and reduce the need for remedial education. This brief describes how these groups can work together to make the most of data…

Academic standards and performance outcomes are a major focus of the current Cycle 2 Australian Universities Quality Agency (AUQA) audits. AUQA has clearly stated that universities will need to provide "evidence of setting, maintaining, and reviewing institutional academic standards and outcomes" (2010, p. 27). To do this, universities…

In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…