This story begins with the assumption that I, the White female researcher, would elicit 'better' data from White participants. I told my Black female professor, 'I'm gonna use this White face!' This became a metaphor to describe my entry into the site and the various interactions that took place there. I conclude that the way that my racial…

California does not have a statewide data system that tracks student progress through K-12 and higher education and into the workforce. As a result, educators and policymakers cannot answer critical questions about student progress, which limits their ability to make evidence-based changes to support better and more equitable opportunities for…

Working with practicing teachers, this article demonstrates, through the facilitation of a statistical activity, how to introduce and investigate the unique qualities of the statistical process including: formulate a question, collect data, analyze data, and interpret data.

In recent years and especially over the past 12 months, with the COVID-19 pandemic and the unrest after the death of George Floyd, community colleges have been making efforts to view and rethink their missions through an equity lens. These efforts have included turning this prism toward institutional operations like student services, human…

Nowadays, Massive Open Online Courses (MOOCs) have obtained a rapid development and drawn much attention from the areas of learning analytics and artificial intelligence. There are lots of unstructured data being generated in online reviews area. The learning behavioral data become more and more diverse, and they prompt the emergence of big data…

As a research methodology, qualitative research method infuses an added advantage to the exploratory capability that researchers need to explore and investigate their research studies. Qualitative methodology allows researchers to advance and apply their interpersonal and subjectivity skills to their research exploratory processes. However, in a…

Australian early childhood education still labours with the achievement of universal access and the production of comprehensive and consistent data to underpin a national evidence base. In this article, we attend to the processes led by numbers whereby new practices of quantification, rationalization and reporting are introduced and mastered in a…

Various types of structured data collected by learning management systems such as Moodle have been used to improve student learning outcomes. Learning analytics refers to an assortment of data analysis methods used for this task. These methods typically do not consider unstructured data such as blogs, discussions, e-mail, and course messages.…

"Education data science" is an emerging methodological field which possesses the algorithm-driven technologies required to generate insights and knowledge from educational big data. This article consists of an analysis of the Lytics Lab, Stanford University's laboratory for research and development in learning analytics, and the Center…

Career Technology Education (CTE) program evaluations have been mostly completed for compliance and monitoring purposes. Hence, they have limited use in establishing program effectiveness or for program improvement. Moreover, engaging in program evaluations can be time consuming and costly, especially for programs that have not been evaluated in…

Although millions of students have access to varieties of learning resources on Massive Open Online Courses (MOOCs), they are usually limited to receiving rapid feedback. Providing guidance for students, which enhances the interaction with students, is a promising way to improve learning experience. In this paper, we consider to show students the…

State tests lack the sensitivity and frequency to reflect ongoing academic improvement of students who are well below grade-level proficiency standards. As a result, some states are using screening and progress-monitoring data, collected as part of a multi-tiered system of supports (MTSS) model, to evaluate early student-level progress toward SiMR…

With the spread of the COVID-19 pandemic, many universities adopted a hybrid learning model as a substitute for a traditional one. Predicting students' performance in hybrid environments is a complex task because it depends on extracting and analyzing different types of data: log data, self-reports, and face-to-face interactions. Students must…

Pre-service teachers (PSTs) often lack the self-efficacy necessary to effectively implement STEM education into their classrooms. Undergraduate research experiences (URE) can help fill this void by providing opportunities for PSTs to engage with STEM content and K-12 students in a field-based research context. This case study details the impact a…

Purpose: This paper aims to offer practical guidance on teaching about digital extremism -- defined here as the intersection of digital disinformation campaigns with political extremism -- by highlighting four pedagogical challenges: the danger of unintentionally "redpilling" students; the slippery slope to false equivalency and…