Information security and information privacy, while related, encompass different details, especially for higher education institutions. Data security, focused on protecting data from malicious attacks, does not go as far as data privacy, focused on how data is shared, used, and communicated with others. Prior literature and research suggest higher…

Educators and researchers have long contemplated the most effective ways to provide feedback to students, to build sustainable feedback practices, and to establish feedback literacy. While a considerable amount of research, theory, and practical approaches exist to support the effect of formative feedback practices, less research exists on the…

With the growing desire to incorporate data science and informatics into STEM curricula, there is an opportunity to integrate research-based software and tools (e.g., Python) within existing pedagogical methods to craft new, accessible learning experiences. We show how the open-source Jupyter Book software can achieve this goal by creating a…

Generalizability theory is a modern, powerful, and broad framework used to assess the reliability, or dependability, of measurements. While there exist classic works that explain the basic concepts and mathematical foundations of the method, there is currently a lack of resources addressing computational resources for those researchers wishing to…

A data party is an engaging way to involve stakeholders in program evaluation. We explain the use of a data party for engaging 4-H program stakeholders (e.g., staff and volunteers) in data interpretation and helping them understand, embrace, and use program evaluation information to make data-driven decisions about their programs. We present two…

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…

The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose…

Expanded learning intermediaries are nonprofit organizations dedicated to making after-school and summer programs better and more accessible for children and youth. They do this by coordinating efforts and resources in a given community, knitting programs together into a cohesive system, helping individual programs function at a high level, and…

Many articles have been published in gifted education in recent years. This study aims to provide a comprehensive review of the evolution of academic studies in gifted education. In this context, the structural topic modeling (STM) method was used to analyze the topics and trends in the field. STM is a machine learning technique that utilizes…

Many of the decisions made related to student progress and intervention selection rely on data. In their roles, paraeducators often implement academic interventions; therefore, they must be prepared to monitor students' progress accurately and reliably. This pilot randomized control trial tested the effects of a remote training package on…

Background: Data missingness can bias interpretation and outcomes resulting from data use. We describe data missingness in the longest-standing US-based youth fitness surveillance system (2006/07-2019/20). Methods: This observational study uses the New York City FITNESSGRAM (NYCFG) database from 1,983,629 unique 4th-12th grade students (9,147,873…

Background: In recent years, there has been generalized concern in all countries about increasing the younger population's level of financial literacy. However, there is still little evidence on the key factors explaining financial literacy, as the existing literature is inconclusive about this issue. This paper focuses on exploring whether…

This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…

State and local education agencies continue to make an effort to systematically assess school climate through student surveys. These assessments typically collect data from individual students about their perceptions of different components of the school and their relationship to individuals in the school and aggregate those responses to the…

"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…