Expanding access to high-quality, affordable early childhood services is key to state efforts to support families' well-being, ensure that children are ready to succeed in school, and sustain a strong economy. Right now, early childhood data is typically housed in different, disconnected state and local systems. State leaders seeking to provide…

For states to build statewide longitudinal data systems that empower people with access to information about education and workforce pathways, state leaders must consider the human capacity they already have, and must develop, to support this work. Building the human capacity required to manage, analyze, and protect data means investing in and…

As California State University (CSU) launches its Pregnant and Parenting Students Initiative to increase graduation rates for parenting students at its campuses and works to implement the Greater Accessibility, Information, Notice, and Support (GAINS) for Student Parents Act, an exciting window of opportunity has opened for student voice to inform…

The COVID-19 pandemic uniquely affected nearly all the subject matter in a typical principles of macroeconomics class. Fluctuations in the basic macroeconomic data in the COVID era were staggering and offer new teaching opportunities. In addition, because the recession was primarily driven by supply side shocks, the entire episode offers a unique…

Stories are more than they seem. Stories can connect humans with other humans, more-than-human things, animals, places and times. And stories can disrupt dominant ways of knowing and being in the world (Ranco & Haverkamp, 2022). Re-telling stories of connection and disruption in research, this paper shares four short autoethnographic musings,…

Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…

"Transforming the School Counseling Profession" is an introduction that conveys how the roles of the professional school counselor fit together comprehensively. Using easy-to-understand language and illustrated with numerous applied examples, case studies and vignettes, it connects theory to practice with real examples of practitioners…

We consider Bayesian estimation of a hierarchical linear model (HLM) from partially observed data, assumed to be missing at random, and small sample sizes. A vector of continuous covariates C includes cluster-level partially observed covariates with interaction effects. Due to small sample sizes from 37 patient-physician encounters repeatedly…

International organisations have measured adult learning participation since the 1990s, using surveys like the Adult Education Survey (AES) and the Programme for the International Assessment of Adult Competencies (PIAAC). These surveys employ a 'triadic' classification of learning activities -- formal (FAE), non-formal (NFE) and informal learning…

In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…

Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). In our practice as academic developers, we are frequently asked for advice on whether this use for GenAI is reliable, valid, and ethical. Since this is a new field, we have not been able to…

We are at a critical moment for assessment in schools. Teachers are called to navigate advances in classroom assessment research, top-down assessment policies, and lingering effects of the COVID-19 pandemic on teaching and learning. Embedded in this context are also systemic challenges to teachers' assessment practice. This paper analyses these…

Misleading data visualizations have become a significant issue in our information-rich world due to their negative impact on informed decision-making. Consequently, it is crucial to understand the factors that make viewers vulnerable to misleading data visualizations and to explore effective instructional supports that can help viewers combat the…

The purpose of this study is to investigate the current state of graduate level business analytics education in the United States. The goal of this research is twofold. The first goal is to understand how higher education institutions are addressing the growing demand for analysts and data-savvy managers in the job market. To achieve this aim, the…

This study demonstrates how to evaluate a university-wide online course designed to support student transition into university by using Propensity Score Matching (PSM) and Doubly Robust Estimation (DRE). Using data from seven academic years, from 2016/17 to 2022/23, with more than 28,000 students, we examine whether enrolment in this optional…