Realist synthesis techniques can be used to assess complex interventions by extracting and synthesizing configurations of contexts, mechanisms, and outcomes found in the literature. Our novel and multi-pronged approach to the realist synthesis of workplace harassment interventions describes our pursuit of theory to link macro and program level…

In this short thought-piece, I attempt to capture the type of freewheeling discussions I had with our late colleague, Mika Seppälä, a research mathematician from Helsinki. Mika, not being a psychometrician or learning scientist, was blissfully free from the design constraints that experts sometimes ingest, unwittingly. I also draw on delightful…

Recurrent event data arise frequently in various fields such as biomedical sciences, public health, engineering, and social sciences. In many instances, the observation of the recurrent event process can be stopped by the occurrence of a correlated failure event, such as treatment failure and death. In this article, we propose a joint scale-change…

Process mining methodologies are designed to uncover underlying business processes, deviations from them, and in general, usage patterns. One of the key limitations of these methodologies is that they struggle in cases in which there is no structured process, or when a process can be performed in many ways. Learning Management Systems are a…

Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…

Predicting the students' performance has become a challenging task due to the increasing amount of data in educational systems. In keeping with this, identifying the factors affecting the students' performance in higher education, especially by using predictive data mining techniques, is still in short supply. This field of research is usually…

Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…

The paper aims to present application of Educational Data Mining and particularly Case-Based Reasoning (CBR) for students profiling and further to design a personalised intelligent learning system. The main aim here is to develop a recommender system which should help the learners to create learning units (scenarios) that are the most suitable for…

This article is a response to an article written by Wang and Ma "An Examination of Plausible Score Correlation from the Trend in Mathematics and Science Study", published in the Athens Journal of Education. The purpose of this paper is to address issues with Wang's and Ma's suggestion to use analysis method for correlating plausible…

Founded on the need to help university students develop a greater academic metacognitive capacity, student-facing learning analytics are considered useful tools for making students overtly aware of their own learning processes, helping students to develop control over their learning, and subsequently supporting more effective learning. However,…

Longitudinal administrative data generated by public education systems in the United States have become increasingly available and have tremendous potential to inform policy research. While it is tempting to take the accuracy of administrative data for granted, there are reasons why researchers should approach these data with a degree of caution.…

Big international assessment organisations like Cambridge Assessment have long held considerable amounts of data. When text is produced digitally, we can do more with it. Surprisingly to many, there have been examples of automatic scoring of extended writing for around 20 years, though what works well in one context may not be applicable in all…

Background: As the state standards increase, along with the instructional rigor within developed curriculum and state accountability, the need to improve ineffective teachers and their practices in the classroom has become a national priority. The need for relevant professional development that meets both the instructional needs of the teacher and…

This article examines the concept of credible evidence in Extension evaluations with specific attention to the measures and measurement strategies used to collect and create data. Credibility depends on multiple factors, including data quality and methodological rigor, characteristics of the stakeholder audience, stakeholder beliefs about the…

This article demonstrates how a digital environment offers new opportunities for transforming qualitative data into quantitative data in order to use data mining and information visualization for mixed methods research. The digital approach to mixed methods research is illustrated by a framework which combines qualitative methods of multimodal…