This paper examines the concept of open-source data interoperability in the United States' K-12 education domain, specifically addressing the implications of interoperability for data justice. The term 'data justice' is a relatively recent coinage; the framing and meaning of this term are still evolving, and it has not yet been applied in the…

Meta-analysis is a widely used methodology to combine evidence from different sources examining a common research phenomenon, to obtain a quantitative summary of the studied phenomenon. In the medical field, multiple studies investigate the effectiveness of new treatments and meta-analysis is largely performed to generate the summary (average)…

For the appraisal of single-case intervention data, school psychologists have been encouraged to focus most, if not all, of their interpretive weight on the visual inspection of graphed data. However, existing software programs provide practitioners with limited features for systematic visual inspection. R (R Development Core Team, 2014) is a…

The quantitative evaluation of experimental data and their graphical presentation are integral to teaching and research in chemistry and the life sciences. Data are commonly fitted to physical models, which in all but the simplest cases are expressed as nonlinear mathematical functions. To facilitate data evaluation in both teaching and research…

Configural frequency analysis and log-linear modeling are presented as person-centered analytic approaches for the analysis of categorical or categorized data in multi-way contingency tables. Person-centered developmental psychology, based on the holistic interactionistic perspective of the Stockholm working group around David Magnusson and Lars…

Open data sharing promises to accelerate the pace of discovery in the developmental and learning sciences, but significant technical, policy, and cultural barriers have limited its adoption. As a result, most research on learning and development remains shrouded in a culture of isolation. Data sharing is the rare exception (Gilmore, 2016). Many…

Open Data is the name given to datasets which have been generated by international organisations, governments, NGOs and academic researchers, and made freely available online and openly-licensed. These datasets can be used by educators as Open Educational Resources (OER) to support different teaching and learning activities, allowing students to…

In low-resource settings, the prioritization of clinical care funding is often determined by immediate health priorities. As a result, investment directed towards the development of standards for clinical data representation and exchange are rare and accordingly, data management systems are often redundant. Open-source systems such as OpenMRS and…

Incorporating realistic data and research examples into quantitative (e.g., statistics and research methods) courses has been widely recommended for enhancing student engagement and comprehension. One way to achieve these ends is to use a data generator to emulate the data in published research articles. "MorseGen" is a free data generator that…

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…

The true power of comparative research around the impact and use of open educational resources is only just being realised, largely through the work done by the Hewlett-funded OER Research Hub, based at The Open University (UK). Since late 2012, the project has used a combination of surveys, interviews and focus groups to gather data about the use…

This work describes the design and construction of an open source, entity resolution system that enables users to assign and maintain persistent identifiers for master data items. Two key features of this system that are not available in current ER systems and that make persistent identification possible are (1) The capture and management of…

In various research areas, the availability of open datasets is considered as key for research and application purposes. These datasets are used as benchmarks to develop new algorithms and to compare them to other algorithms in given settings. Finding such available datasets for experimentation can be a challenging task in technology enhanced…

The authors describe the University of Central Florida's top-down/bottom-up action analytics approach to using data to inform decision-making at the University of Central Florida. The top-down approach utilizes information about programs, modalities, and college implementation of Web initiatives. The bottom-up approach continuously monitors…

Although the term data-driven decision making (DDDM) is relatively new (Moss, 2007), the underlying concept of DDDM is not. For example, the practices of formative assessment and computer-managed instruction have historically involved the use of student performance data to guide what happens next in the instructional sequence (Morrison, Kemp, &…