Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help…

R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

In this article, we describe a large-scale living learning community (LLC) for undergraduate students of any major or background. Our students are united by a desire to learn data science skills and to apply those skills in a specific academic discipline or a corporate partner project. We provide explanations of why an LLC is beneficial; the…

Despite evidence supporting the importance of school climate, little is known about how practitioners understand and use data from climate surveys to guide schoolwide improvement. The expanded use of school climate surveys underscores the importance of understanding how schools and districts are utilizing this evidence both to drive improvement…

The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…

In a randomized trial that collects text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by human raters. An impact analysis can then be conducted to compare treatment and control groups, using the hand-coded scores as a measured outcome. This…

A significant number of U.S. students are unable to read proficiently by fourth grade, and over two billion dollars are spent each year on students who repeat a grade due to reading problems. The purpose of this basic qualitative study was to examine novice elementary teachers' perspectives of their self-efficacy in using adaptive instructional…

From 2010 onwards, most US states have aligned their education standards by adopting the Common Core State Standards (CCSS) for math and English Language Arts. The CCSS did not target other subjects such as science and social studies. We estimate spillovers of the CCSS on student achievement in non-targeted subjects in models with state and year…

Partnership models have been effective across many areas of higher education such as involving students as teaching and learning consultants, in course design and redesign, and as co-instructors. However, there are few systems-level (i.e., entire programs or institutions) examples of partnership work and virtually none in systems-level assessment.…

The current data-centric business environment has seen an increasing demand for business students with knowledge and skills in the area of business analytics. This article presents the design and implementation of a foundation business analytics (BA) course for undergraduate business students who aspire to become data-literate professionals or…

In this comparative study, I examine principal data use in two sets of districts. One set of three districts has a district-wide focus on using data to improve instruction, and the other set, also with three districts, has a district-wide focus on analyzing disaggregated data by student demographic groups. Data sources include interviews with…

In addition to providing a set of techniques to analyze educational data, I claim that data science as a field can provide broader insights to education research. In particular, I show how the bias-variance tradeoff from machine learning can be formally generalized to be applicable to several prominent educational debates, including debates around…

The purpose of study was gain insight into pre-service teachers' experiences in using classroom data to make learning and teaching decisions. The qualitative study is based on the reflections and recommendations of three pre-service teachers' that participated in a data-driven decision-making intervention whilst on an immersive 10-week…

While universities routinely use student data to monitor and predict student performance, there has been limited engagement with student and staff views, social and ethical issues, policy development, and ethical guidance. We reviewed peer-reviewed and grey-literature articles of 2007 to 2018 describing the perspectives of staff and students in…

This article explores how making data playable, i.e. developing exploratory co-creation techniques that use elements of play and games to interpret small to mid-sized datasets beyond the current focus on visual evidence, can help a) promote creative data literacy in higher education, and b) expand existing definitions of data literacy. The article…