E-learning has become an emerging approach to delivering knowledge and information to students. It presents significant challenges to sharing and understanding learners' knowledge, inquiries, interest, and needs. Educational organizations are expected to apply the appropriate practice to address knowledge-sharing challenges in the e-learning…

The focus of this study was to assess the skill requirements for data analytics positions and to understand data analysis employment expectations for new graduates. Furthermore, this work seeks to highlight issues relevant to curriculum management in university degree programs. 786 job postings were analyzed for domain-related, soft skills, as…

Considering the salience of emotions in their work, special educators should think of them as an important source of data to inform and improve their practice. Special educators' emotions and emotional labor are a rich and accessible form of data that can directly inform their delivery of high-quality instruction. Although special educators…

This paper investigates changes in the promissory visions articulated in education reforms around the world. We use structural topic modeling to inductively analyze the content of 9,268 reforms from 215 countries and territories during the period 1970-2018 using the World Education Reform Database. Our findings reveal a decline in traditional…

Public educational systems and institutions have increased their adoption of proprietary educational platforms offered by large private corporations. Platforms now critically mediate content creation and storage, interaction and communication, record-keeping and institutional memory. This platformization of education has led to significant risks…

The growing use of analytics has increased the demand for more highly data literate graduates. Awareness of ambiguity in data has been suggested as a new data literacy skill. Here, we describe a student-centered semester-long project that can be used to teach this skill in an introductory analytics or database course. The project requires students…

This article describes an activity and resource from The New York Times that can be used to help learners cultivate critical statistical literacy. Critical statistical literacy involves understanding, interpreting, and questioning statistical information to make informed decisions (Casey et al., 2023; Franklin et al., 2015; Weiland, 2017). It is a…

The implementation of Multi-Tiered System of Supports (MTSS) has been successful in multiple elementary systems across the United States. Providing three tiers of support for students struggling academically, social-emotionally, and behaviorally in the classroom setting and created success for many students until they reach the secondary level,…

The implementation of Multi-Tiered System of Supports (MTSS) has been successful in elementary systems across the United States. For secondary schools, the implementation of MTSS has not been as successful. Secondary teachers often note difficulties include understanding data from different sources, what sources are available, and how it applies…

Graph Signal Processing (GSP) plays a crucial role in addressing the growing need for information processing across networks, especially in tasks like supervised classification. However, the success of GSP in such tasks hinges on accurately identifying the underlying relational structures, which are often not readily available and must be inferred…

The application of corpus to language instruction encouraged the use of data-driven learning (DDL). It is assisted by computer technology, and uses authentic language data as the basis for language instruction. Previously conducted studies have paid little attention to the use of corpus tools in speaking instruction. Thus, this study aimed to…

Data harmonization is an emerging approach to strategically combining data from multiple independent studies, enabling addressing new research questions that are not answerable by a single contributing study. A fundamental psychometric challenge for data harmonization is to create commensurate measures for the constructs of interest across…

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…