The purpose of this study was to explore how evaluators justify using story-based methodologies when examining causality. The two primary research questions of the study included: 1) what arguments are made by evaluators to justify the credibility of story-based causal methodologies to evaluation stakeholders; and 2) from the perspective of…

Teachers in the United States are increasingly tasked with using data to inform their classroom instruction both through federal policies, such as the Every Student Succeeds Act (ESSA, 2016), and state policies requiring the use of teacher-determined data-driven goals for performance evaluations (MA 603 CMR 35.07). Many teachers, however, report…

The education landscape in the United States has been changing rapidly in recent decades: student populations have become more diverse; there has been an explosion of data sources; there is an intensified focus on diversity, equity, inclusion, and accessibility; educators and policy makers at all levels want more and better data for evidence-based…

Mandatory community college student fees have risen steadily over the past 20 years, outpacing the growth of tuition by a substantial margin. To date, research on postsecondary fees has been limited to public four-year colleges and universities, even as community college fees are growing faster and affecting students who are likely more price…

Research Context: In educational research, "context effects" are often of inferential interest to researchers as well as of evaluative interest to policymakers. While student education outcomes likely depend on individual-level influences like individual academic achievement, school contexts may also make a difference. Such questions are…

This paper shows a method for integrating computer programming into a standard physical chemistry laboratory sequence to augment student data analysis abilities and allow them to carry programming skills forward to other courses. The Python programming language is used, taking advantage of the pedagogical benefits of Jupyter notebooks, primarily…

Data science programming presents many challenges for programmers entering the field. Roughly, data science programming can be broken up into several activities: data wrangling, analysis, modeling, or visualization. Data wrangling is an important first step that involves cleaning and shaping tabular data--or dataframes--into a form amenable for…

The purpose of this study is to evaluate the performance of three commonly used model fit indices when measurement invariance is tested in the context of multiple-group CFA analysis with categorical-ordered data. As applied researchers are increasingly aware of the importance of testing measurement invariance, as well as Likert-type scales are…

Advances in state education data systems are helping schools understand and meet the needs of learners from early education through college and the workforce. Each state has adhered to key principles for protecting student data privacy. In the report "Lessons in Data Privacy for Education Leaders. Policy Guide," (ED625423) leading…

This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…

Fisheries scientists make sure that fish populations ("fisheries") are managed properly, neither over- or under-utilized, to maintain long-term economic and ecological stability. Scientists collect data and conduct surveys to determine fish populations, and then make recommendations about how many fish may be caught by commercial and…

Increasingly, learning in science and mathematics is considered in terms of induction into the multimodal language practices of the disciplinary community. A strong strand of research in this tradition has involved students being challenged to invent multimodal language forms, and their ideas refined through structured guidance. Often, however,…

More aggregate data on school performance is available than ever before, opening up new possibilities for applied researchers interested in assessing the effectiveness of school-level interventions quickly and at a relatively low cost by implementing comparative interrupted times series (CITS) designs. We examine the extent to which effect…

Arguably one of the most valuable tools for investigating pupil behaviour in an educational environment is systematic classroom observation. Classroom observation is often cited as having the potential to enable research of the learning process in action. Low inference classroom observation instruments are designed to record a sequence of data…

The purpose of this study is to contribute to the establishment of metrics that can be used by libraries to analyze, anticipate, and plan for resource allocation for specialized print-based collections within an academic library. In the context of transactions associated with the circulation of library materials, that is checkouts, renewals, and…