Effectively estimating student enrollment and recruiting students is critical to the success of any university. However, despite having an abundance of data and researchers at the forefront of data science, traditional universities are not fully leveraging machine learning and data mining approaches to improve their enrollment management…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

In March 2020, the coronavirus pandemic and attending shift to remote schooling initiated a dramatic impact on student learning, an impact that state and district leaders feel a sense of urgency to understand and address. These leaders are accustomed using state and district test data to shed light on student achievement and growth. But without…

As the education and workforce development community looks more and more to CTE to help ensure students are both college and career ready, understanding and using CTE data and research becomes increasingly important. This is the first in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE)…

We centrally consider the question of what interview data can be used to 'say' through a dialogue with advocates of the 'radical critique' of interview studies. We propose that while the critique has considerable utility in drawing to 'the social life of interviews' and the pervasiveness of notions of the 'romantic subject', it simultaneously goes…

Bayesian network is a probabilistic graphical model that has wide applications in various domains due to its peculiarity of knowledge representation and reasoning under uncertainty. This research aims at Bayesian network structure learning and how the learned model can be used for reasoning. Learning the structure of Bayesian network from data is…

One part of COVID-19's staggering impact on education has been to suspend or fundamentally alter ongoing education research projects. This article addresses how to analyze the simple but fundamental example of a multi-cohort study in which student assessment data for the final cohort are missing because schools were closed, learning was virtual,…

Purpose: Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches -- in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and…

The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term "actionable insight" means. This selective literature review provides a look into…

Data rules schools and ignorance is far from bliss. From assessment results to questioning educational claims, there is a growing need to understand the numbers used in education. Education data blogger and teacher Richard Selfridge (aka Jack Marwood) unravels the complexities of dealing with educational data and explains statistics in an…

Instructors may design and implement formative assessments on technology-enhanced platforms (e.g., online quizzes) with the intention of encouraging the use of effective learning strategies like active retrieval of information and spaced practice among their students. However, when students interact with unsupervised technology-enhanced learning…

Keystroke logging is used to automatically record writers' unfolding typing process and to get insight into moments when they struggle composing text. However, it is not clear which and how features from the keystroke log map to higher-level cognitive processes, such as planning and revision. This study aims to investigate the sensitivity of…

In this paper, we argue for a view of analysis as an embodied practice and review others' testimonies of carrying out multimodal ethnography. This review suggests that metaphors are key for communicating what happens to "us" in the course of the research and our subsequent sense-making practices. We identify four metaphors for…

When exposed to principal components analysis for the first time, students can sometimes miss the primary purpose of the analysis. Often the focus is solely on data reduction and what to do after the dimensions of the data have been reduced is ignored. The datasets discussed here can be used as an in-class example, a homework assignment, or a…

The purpose of this dissertation is to understand the impacts of social service data collection and use on the lives of young people and those that serve them, and to offer ways for youth, nonprofits, and funders to positively evolve these systems. It grew from three simple questions without clear answers: what's happening, how's it working, and…