Multiple studies show that outcomes, whether they be better degree completion rates or successful short-term workforce training, are negatively affected by inadequate funding (Kahlenberg, 2015). To bolster their case for underfunding, researchers and college advocacy groups produce studies that rely on an important federal dataset--the Integrated…

Digital phenotyping is defined as the "moment-by-moment quantification of the individual level human phenotype in situ using data from personal digital devices". The passive data collected by smartphone devices, including GPS, accelerometer and communication logs, can provide insights on users' behaviors that could be related to various…

This guide is designed for use by school, district, and state education agency staff to improve the effectiveness of efforts to collect and use discipline data, including reporting accurate and timely data to the federal government. It explains the importance of collecting discipline data, identifies key considerations for agencies implementing…

In this paper, we investigate an interesting question that came up when reading a problem in a school textbook: What happens to the variance of a dataset in the case of changing one single data point, and why? Some of the answers are not surprising but here we find the full answer and demonstrate the understanding of it suitable for school…

Evaluators have been slow to "plug" into the digital world, let alone engage with the strategic implications of the Big Data revolution for the evaluation discipline. Yet, Big Data holds enormous promise for extending the reach and improving the quality of evaluation practice. Equally, systematic recourse to evaluation would greatly…

Multilevel modeling is commonly used with clustered data, and much emphasis has been placed specifically on the multilevel linear model (MLM). When modeling clustered ordinal data, a multilevel ordinal model with cumulative logit link assuming proportional odds (i.e., multilevel cumulative logit model) is typically used. Depending on the research…

From Fall 2019 through Spring 2020, The Hunt Institute released a series of policy briefs, "Attainment for All: Postsecondary Pathways," that highlighted scalable state-level strategies to boost postsecondary attainment rates among specific student subpopulations including high school graduates, first-generation students, and adult…

Data collection and analysis (DCA) skills apply mathematical knowledge, such as counting, sorting, and classifying, to investigations of real-world questions. This pursuit lays the foundation for learners to develop flexible problem-solving skills with data. This pilot study tested a preschool intervention intended to support teachers in promoting…

Purpose: This paper establishes the attitude of Australian livestock farmers toward the use of mobile applications (apps) in farmer extension, training and on-farm decision making. It also determines levels of technology adoption of smartphones and agriculture app use, as well as identifies factors that may influence app adoption. Methodology: A…

Background: This study describes a method for harmonizing data collected with different tools to compute a rating of compliance with national recommendations for school physical activity (PA) and nutrition environments. Methods: We reviewed questionnaire items from 84 elementary schools that participated in the Childhood Obesity Research…

The tremendous growth of educational institutions' electronic data provides the opportunity to extract information that can be used to predict students' overall success, predict students' dropout rate, evaluate the performance of teachers and instructors, improve the learning material according to students' needs, and much more. This paper aims to…

Collecting data on lesbian, gay, bisexual, transgender, queer-plus (LGBTQ+) issues and the experiences of LGBTQ+ young people is essential both for enforcing civil rights protections and advancing racial, gender, and disability justice outcomes in K-12 education systems across the country. The absence of this data: (1) Is a barrier to full…

With improving technology and monitoring efforts, the availability of scientific data is rapidly expanding. The tools that scientists and engineers use to analyse data are changing in response. At the same time, science education standards have shifted to emphasize the importance of students making sense of data in science classrooms. However, it…

Research data management is essential for high-quality reproducible research, yet relatively little is known about how research data management is practiced by graduate students in Civil and Environmental Engineering (CEE). Prior research suggests that faculty in CEE delegate research data management to graduate students, prompting this…

In this paper, we introduce Notice, Wonder, Feel, Act, and Reimagine (NWFAR) to promote social justice in data science (DS) education. NWFAR draws on intersectional feminist DS to scaffold critical perspectives towards systems of power and oppression and attend to students' experiences in designs for learning. NWFAR adds three practices that are…