This article reports on a rigorous approach developed for calibrating the Evidence-Based Adequacy Model to suit the Ontario K-12 public education context, and the actual calibrations made. The four-step calibration methodology draws from expert consultations and a review of the academic literature. Specific attention is given to the technical…

The field of Indigenous methodologies has grown strongly since Tuhiwai Smith's 1999 groundbreaking book "Decolonizing Indigenous Methodologies." For the most part however, there has been a marked absence of quantitative methodologies with the methods aligned with Indigenous methodologies predominantly qualitative. This article proposes…

Juxtaposed with the emerging body of literature about datafication in schooling, this paper examines the increasing encroachment of data into the Japanese education system, in particular, the use of data associated with standardised academic assessments for governance purposes. In so doing, we use the Japanese 'case' to expose the possible limits…

We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…

The archive is a cultural institution that creates a framework for the social and collective memory and as such is one of the collection of knowledge institutions that not only preserves and classifies "texts" but uses them to re-create collective memory and sometimes to invent cultural histories. Like all knowledge institutions, the…

Big qualitative data (Big Qual), or research involving large qualitative data sets, has introduced many newly evolving conventions that have begun to change the fundamental nature of some qualitative research. In this methodological essay, we first distinguish big data from big qual. We define big qual as data sets containing either primary or…

The teaching performance expectations and assignments that preservice art teachers currently address in field experiences and in their coursework are designed to help them meet the expectations of being a quality art educator in the 21st century. These assignments may be very different from the assignments that art educators had in their…

This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series…

Organizational relationships are complex. Employees do their work as individuals, but also as members of larger teams. They exist within various social networks, both within and spanning organizations. Multilevel theory is at the core of the organizational sciences, and unpacking multilevel relationships is fundamental to the challenges faced…

The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…

A classroom activity is presented, which can be used in teaching students statistics with an easily generated, large, real world data set. The activity consists of analyzing a video recording of an object. The colour data of the recorded object can then be used as a data set to explore variation in the data using graphs including histograms,…

Importance: The article raises a point of visual representation of big data, recently considered to be demanded for many scientific and real-life applications, and analyzes particulars for visualization of multi-dimensional data, giving examples of the visual analytics-related problems. Objectives: The purpose of this paper is to study application…

The Oregon Department of Education (ODE) partnered with 15 elementary schools to obtain and analyze student-level daily attendance records for 6,390 students. Schools ranged in size from just over 100 students to more than 600 students. Geographic locations also varied with 4 schools located in a city, 4 in a suburb, 4 in a town, and 3 in a rural…

Online learning is one of the most important and well-established machine learning models. Generally speaking, the goal of online learning is to make a sequence of accurate predictions "on the fly," given some information of the correct answers to previous prediction tasks. Online learning has been extensively studied in recent years,…

Predicting overall student performance and monitoring progress have attracted more attention in the past five years than before. Demographic data, high school grades and test result constitute much of the data used for building prediction models. This study demonstrates how data from a peer-assessment environment can be used to build student…