The Vermont Agency of Education (AOE), through funding from a 4.9 million dollar grant from the U.S. Department of Education, is in the final stages of developing and implementing a Statewide Longitudinal Data System (SLDS) to support the work of the AOE and Vermont school districts. A significant portion of the federal award supports the creation…

State and local education agencies across the country face challenges related to understanding and managing their teaching staff to best help students learn. Statewide longitudinal data systems (SLDSs) offer valuable information about teacher labor markets that can be used to analyze supply and demand, inform budget and staffing decisions, and…

Recently, research has highlighted the potential of Massive Open Online Courses (MOOCs) for education, as well as their drawbacks, which are well known. Several studies state that the main limitations of the MOOCs are low completion and high dropout rates of participants. However, MOOCs suffer also from the lack of participant engagement,…

The present study uses a text data mining approach to automatically discover learner interests in open learning environments. We propose a method to construct learner interests automatically from the combination of learner generated content and their dynamic interactions with other learning resources. We develop a learner-topic model to discover…

Over the past 20 years, many colleges and universities have made significant progress in building data warehouses and implementing business intelligence tools to provide better access to administrative data that were previously locked away in enterprise systems. However, the data architectures from the 1990s and 2000s are aging as new technologies…

The study of earthquakes can help students build connections between theoretical analysis and real-world applications. However, units on earthquakes typically struggle to bridge that gap between theory and application. Traditional class activities focus on measuring earthquakes, such as triangulating epicenters by analyzing P and S wave arrival…

To evaluate interim progress toward the State-identified Measurable Result (SIMR), states require access to high-quality data from local education agencies (LEAs) and early intervention service providers. In a review of 2017 Phase III State Systemic Improvement Plans (SSIP), 43 Part C states noted limitations or concerns related to data and…

The expansion of big data and analytics has led to the diffusion of institutional research functions across campus departments. In this new environment, IR professionals expect to lead and coordinate various institutional analyses. This article presents a four-quadrant framework to facilitate the dynamics between data analysis and decision-making.

Education researchers are increasingly interested in applying data mining approaches, but to date, there has been no overarching exposition of their methodological advantages and disadvantages to the field. This is partly because the use of data mining in education research is relatively new, so its value and consequences are not yet well…

This article explores the history of digital testing technology. Using an organisation that pioneered the use of international large-scale assessments -- the International Association for the Evaluation of Educational Achievement (IEA) -- I discuss the role of computers, punched cards, answer cards and scanning machines as an example of…

The pervasive role of digital technologies in adult learning and education (ALE) was a prominent theme throughout the deliberations of the Seventh International Conference on Adult Education (CONFINTEA VII) held June 15-17, 2022 in Morocco. CONFINTEA VII embodied the worldwide interest in digital technologies through the use of a hybrid format…

The power of sport to affect social change is widely acknowledged. However, little empirical research has explored the use of sport in engaging young people in global education. This article fills the gap by exploring the role of sport using experiential learning tools as delivery methodology for global education in the context of Central Europe…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

Many education researchers have advocated grounding abstract mathematical and scientific concepts in students' lived experiences, environmental interactions, and perceptions. This dissertation explores the causal effects of various grounding strategies in instructional settings, specifically on the topic of statistical sampling. The first chapter…

Background: Data storytelling is an interdisciplinary practice that uses visual and narrative elements to engage an audience with data. Students need more opportunities across school curriculum to consider the connections between data and social and environmental contexts. Few studies have investigated how to support teachers in co-designing for…