Clustered data structures are common in many areas of educational and psychological research (e.g., students clustered in schools, patients clustered by clinician). In the course of conducting research, questions are often administered to obtain scores reflecting latent constructs. Multilevel measurement models (MLMMs) allow for modeling…

Auxiliary Tanabe-Sugano diagrams are presented. They enable a rapid and reliable graphical derivation of Dq/B and C/B crystal field parameter ratios from spectroscopic data. Using these values, one can calculate Dq and B by employing the original Tanabe-Sugano diagrams. Subsequently, C can also be calculated irrespective of the value C/B fixed in…

Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…

Open data has potential value as a material for use in learning activities. However, approaches to harnessing this are not well understood or in mainstream use in education. In this research, early adopters from a diverse range of educational projects and teaching settings were interviewed to explore their rationale for using open data in…

Following a high-quality early care and pre-K experience, the kindergarten-through-third-grade years set the foundation upon which future learning builds; and strengthening this continuum creates opportunities for later success. Key components of a quality experience in K-3 include school readiness and transitions, kindergarten requirements,…

Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…

Evidence-based and student-centered instructional methods hold the promise of transforming undergraduate STEM education and simultaneously solving the dual challenge of STEM workforce needs and inequities within STEM. The Learning Assistant (LA) Model was created to reform curriculum, recruit teachers, and inform discipline-based education…

The increasing volume of information and the intense pace of its circulation are changing the ways universities access, use, analyze, and provide data. Many have championed the use of large-scale databases to track student admissions and retention, faculty productivity, student wellness, and other phenomena that shape our understandings of higher…

Libraries remain one of the last places on campus where the purging of usage data is encouraged and "tracking" is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of privacy and debate the feasibility of student-generated library data for planning and assessment. Using a study…

Monitoring, evaluation, and research activities generate important data, but they often fail to change policies or programs. In addition, local program staff and partners often feel disconnected from these activities, which undermines their ownership of data and results. To bridge the gaps between monitoring, evaluation, and research and to give…

Response-to-intervention (RtI) is a multi-tiered framework designed to prevent academic difficulties by facilitating robust, research-based instruction and providing targeted or individualized short-term interventions for students at-risk per periodic screening and progress monitoring data. The cornerstone of RtI is data-based decision-making to…

Transforming spoken words into written text in qualitative research is a vital step in familiarizing and immersing oneself in the data. We share a three-step approach of how data transcription facilitated an interpretative act of analysis in a study using qualitative data collection methods on the barriers and facilitators of HIV testing and…

There has been an increasing interest in learning analytics (LA) research especially in higher education (HE) in recent years. In this study, we conducted a systematic focused review of research, from 2016 to present, on using analytics in HE (specifically system- or user-generated data) to understand in what way such analytics has been…

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…

This article draws on a new materialist paradigm to explore bricolaging data from an early childhood research project through an immanent ethical lens. This lens enables the researcher to stretch towards non-hierarchical relationships in between subjects and objects, thinking and doing. A bricoleur explores and builds different…