Data reflects a series of decisions made by people--and those decisions affect the story that data tells, what it captures, and how it can and should be used to inform decision-making. Because of this, mistrust in data is often the result of incomplete information and a lack of context. This resource breaks down what it means to build trust in…

Data collection and analyzation practices for English language development services are scarcely found in research, but needed in the subgroup of minority students commonly known as English language learners (Wiseman & Bell, 2021). Wiseman and Bell (2021) identified ELLs as one of the most under-documented student subgroups in the American…

A revised version of a traditional physical chemistry laboratory experiment has been developed to enhance student discussion in the laboratory and to improve students' connections between physical chemistry concepts and real molecular systems. In this experiment, students explore the keto-enol tautomerization of 2,4-pentanedione. However, unlike…

In undergraduate research settings, students are likely to encounter anomalous data, that is, data that do not meet their expectations. Most of the research that directly or indirectly captures the role of anomalous data in research settings uses post-hoc reflective interviews or surveys. These data collection approaches focus on recall of past…

Technological advances, artificial intelligence innovations, and widespread computing have all combined to necessitate a new generation of knowledge workers where data becomes a ubiquitous part of decision making (Sutton, 2006). Teaching today's students through the application of this "new" knowledge to long-established fields…

This guide is designed to help district and school site leaders assess the professional learning needs of elementary school teachers to implement research-based recommendations for the instruction of English learner students. It comprises two tools--the Teacher Self-Reflection Tool and the Classroom Observation Tool--and outlines a 10-step process…

"Big data" prompts a whole lexicon of terms--data flow; analytics; data mining; data science; smart you name it (cars, houses, cities, wearables, etc.); algorithms; learning analytics; predictive analytics; data aggregation; data dashboards; digital tracks; and big data brokers. New terms are being coined frequently. Are we paying…

In this summary article, six recommendations for the design, implementation, and interpretation of educational evaluations are presented and discussed. These recommendations are based on common "threads" that run through most, if not all, of the papers included in this special issue. The recommendations concern (1) the need for awareness…

This article discusses critical methodological design decisions for collecting, interpreting, and synthesizing empirical evidence during the design, deployment, and operational quality-control phases for automated scoring systems. The discussion is inspired by work on operational large-scale systems for automated essay scoring but many of the…

Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…

The concept of data based decision making has been in the forefront of educational reform for decades. Despite the fact that data could better inform the educational decisions teachers make, some educators lack understanding of data and assessment. This could lead to misinterpretation and poor use of the scores. The purpose of this literature…

As state and local education agencies increasingly focus on serving educators with their data systems, a common challenge has arisen: identifying the critical knowledge, skills, and behaviors needed by teachers and administrators to use data effectively. Many states are creating data literacy and data use training programs for pre- and in-service…

Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

As a university lecturer, I find that a frequent question raised by Masters students concerns the methodology chosen for research and the rationale required in dissertations. This paper unpicks some of the philosophical coherence that can inform choices to be made regarding methodology and a well-thought out rationale that can add to the rigour of…