Practical guidance for navigating issues associated with combining mixed methods and case study research approaches is in short supply, particularly for novice researchers who may grapple with numerous decision points in planning and conducting such studies. This methodological discussion examines the decision-making process used in a…

According to the cliché, it is not what one says so much as how one says it. In the business world, those words ring particularly true. How one presents information can influence all forms of business decisions, from level of investment to expansion to downsizing and everything in between. This brings up significant questions relating to the…

As algorithmic decision-making and data collection become pervasive in higher education, how can educators make sense of the systems that shape life and learning in the twenty-first century? This paper outlines a systematic literature review that investigated gaps in the current framing of data and faculty development, and explores how these gaps…

This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…

This article describes the step-by-step process of how data science, marketing and communications, and higher education improved access and success for students. Over the last three years, strategic planning efforts helped develop a data-informed culture on campus. The work described within the playbook required time, energy, and a lot of…

This paper presents a case study that is part of a research studying how university statistics teachers integrate digital tools in their practice. The case study is of a teacher who claims to follow constructionist ideas for her teaching of statistics, using the R programming language. The teacher developed a series of activities with R, aiming to…

Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…

Although the number of countries conducting large-scale assessments has significantly increased over the past two decades, this has not necessarily led to the effective use of learning assessment data in policymaking and planning. To better understand the reasons for this, the UNESCO International Institute for Educational Planning (IIEP)…

Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…

Public school districts in Texas and policymakers need studies of efficiency in the production of College, Career, and Military Ready graduates to maximize resources in the House Bill 3 funding formula and improve ratings in the Texas public school accountability system. A replication of efficiency studies by Carter (2012) and Thompson (2017), the…

The purpose of this article is to describe the analytic process of a method of data collection known as Q Methodology. This method is an alternative method in collecting data especially suited to research on "points of views" (Coogan & Herrington, 2011, p. 24). The analytic process of Q methodology involves factor analysis, a…

This article examines how algorithms are shaping student learning in massive open online courses (MOOCs). Following the dramatic rise of MOOC platform organisations in 2012, over 4,500 MOOCs have been offered to date, in increasingly diverse languages, and with a growing requirement for fees. However, discussions of "learning" in MOOCs…

The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students' activities in a MOOC from the perspective of personal…

Statistics is one of the important branches of mathematics taught in schools, colleges and universities. It is also an important tool in public policy discussions. This paper focuses on the use of statistics in the latter context, rather than its use in adult mathematics education research. I review the key characteristics of the statistical…

Collecting multiple perspectives data (e.g. from related individuals) in a qualitative longitudinal design can provide rich understanding of the dynamics at play in complex relational systems, and the different perceptions of people involved. However, such approaches are inherently challenging due to the complexity and volume of data involved. So…