This chapter describes examples of Trade Adjustment Assistance Community College and Career Training-funded innovations that resulted in statewide systemic change, including approaches to accelerate adult credential attainment, new approaches to data collection and analysis, enhanced individualized student support, and stronger industry alignment.

The purpose of these guidelines is to support the execution of cost analysis and cost-effectiveness analysis of educational programs. The steps involved in conducting a cost analysis are presented in four stages with explicit examples used throughout: designing your cost analysis, collecting cost data using the ingredients method, analyzing cost…

The Powerful Learning with Computational Thinking report explains how the Digital Promise team works with districts, schools, and teachers to make computational thinking ideas more concrete to practitioners for teaching, design, and assessment. We describe three powerful ways of using computers that integrate well with academic subject matter and…

Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…

Chapters cover the essential character traits and skills that are necessary to become an effective researcher, walk through the main steps for completing a research project from start to finish, and discuss considerations when building a career and research program. Rather than the nitty-gritty of research methods, authors Joshua N. Hook, Don E.…

Recent and rapid technological advances have given rise to an explosive growth of data, along with low-cost solutions for accessing, collecting, managing, and analyzing data. Despite the advances in technology and the availability of data, social work organizations routinely encounter data-related problems that have an impact on their…

Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…

Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…

There is a growing consensus that the ability to understand and process visual information should be part of the second language (L2) listening construct; however, the findings of studies exploring the use of visuals in L2 listening assessment contexts remain inconclusive. To better understand the underlying reasons for these inconclusive results,…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Experiential learning opportunities have been proven effective in teaching applied and complex subjects such as business analytics. Current business analytics pedagogy tends to focus heavily on the modeling phase with students often lacking a comprehensive understanding of the entire analytics process including dealing with real-life data that are…

Measurement systems give colleges a structure for collecting, sharing, and acting on data. The guidebook and tools presented here help faculty, staff, college leadership, and policymakers understand and use measurement systems--and specifically use data to improve completion rates, close institutional performance gaps, and facilitate economic…

Background: New technology and increased collaboration have revolutionized how scientists work with data. This creates a need to identify new aspects of working with scientific data that are important for K-12 students to learn. Purpose: To address this need, we conducted a study with practicing scientists and K-12 science teachers. The purpose of…

The study explored the social perceptions of young children's use of smart devices in South Korea using big data methodologies. Big data methodologies allowed to uncover underlying thoughts and feelings about young children's use of smart devices that had not been discovered in existing studies. The study extracted raw data from three different…

The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the…