Household expenditure data is at the core of efforts to measure living standards, inequality and financial protection against illness. Currently it is mainly derived from recall-based surveys that are time consuming and prone to measurement errors. Diaries are often used as an alternative approach, however this results in fatigue and low…

The amount of grey literature and 'softer' intelligence from social media or websites is vast. Given the long lead-times of producing high-quality peer-reviewed health information, this is causing a demand for new ways to provide prompt input for secondary research. To our knowledge, this is the first review of automated data extraction methods or…

An important course in the computer science discipline is 'Data Structures and Algorithms' (DSA). "The coursework" lays emphasis on experiential learning for building students' programming and algorithmic reasoning abilities. Teachers set up a repertoire of formative programming exercises to engage students with different programmatic…

This paper provides a theoretical and conceptual analysis of educational technology (Ed-Tech) including its role in the administration and organization of schools, colleges, and universities; teachers' pedagogical practices; and students' learning. During and since the pandemic period, education has relied more heavily than ever on technological…

In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and…

Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS…

Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency…

This study aims to design and develop a Cashless Payment System with Automatic Identification and Data Collection (AIDC) technology in an educational institution in the Province of Nueva Ecija, Philippines to understand the processes and activities undertaken to develop the project. It utilizes a descriptive and developmental method of research…

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…

In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…

Longitudinal studies are commonly used in the social and behavioral sciences to answer a wide variety of research questions. Longitudinal researchers often collect data anonymously from participants when studying sensitive topics to ensure that accurate information is provided. One difficulty gathering longitudinal anonymous data is that of…

Among the great challenges posed to democracy today is the use of technology, data, and automated systems in ways that threaten the rights of the American public. Too often, these tools are used to limit our opportunities and prevent our access to critical resources or services. These problems are well documented. In America and around the world,…

Laboratory report assignments for non-major and introductory classes can be challenging because the students are unfamiliar with the type of technical writing required and the subject matter. These issues for the student make the grading for the instructor difficult and time consuming. Determining the level of detail to require, the format, and…

Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…

The authors present a pedagogical primer on the highly controversial business strategies of data mining and automated prediction. They provide a summary that allows business professors and students the opportunity to better understand the privacy and ethical issues that arise from high-tech, Internet-based organizations implementing programs to…