This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…

This study seeks to understand the big-data analytics readiness of four-year public and private higher education institutions (HEIs) in North Carolina. The higher education landscape has been experiencing unprecedented challenges including declines in enrollment, graduation rates, and student retention rates. Coupled with cuts in funding at the…

As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

The interaction of quantitative and qualitative methodology in the mixed methods research (MMR) is analysed in a context of distinctions of the meanings between the terms typically used for description, combination, and integration. The interaction in the phases that precede the results, and their interpretation is considered. As an indicator of…

Evidence-based policymaking can transform the delivery of education services, restore public trust in schools, and improve outcomes for students. It can cut through the noise of political and cultural divisions and give decision makers clarity on how to prioritize the use of limited resources. And it can help build a shared understanding of where…

This work aims to elaborate a governance composite index for research laboratories in public university. This index is composed by an indicator of responsible liberalism associating effectiveness and ethics, to which are added an organizational management indicator and a strategic management indicator. To achieve the above aim, several methods are…

Solving problems in educational settings, as in daily-life scenarios, involves constantly assessing one's own confidence in each considered solution. Metacognitive research has exposed cues that may bias confidence judgments (e.g., familiarity with question terms). Typically, metacognitive research methodologies require examining misleading cues…

Students need "critical data literacy" skills to help make sense of the multitude of information available to them, especially as it relates to high-stakes issues of social justice. The authors describe two curriculum modules they developed--one on income equality, one on immigration--that help students learn to analyze data in order to…

During the last decades, a large body of research has contributed to knowledge on the teacher-student relationship (TSR). However, more research is needed regarding TSR as constructed in interaction and on developing methods for investigating such processes. This paper outlines a method for detailed, close interpretation and analysis of TSR,…

Based on our experience developing and delivering a highly successful data visualization course within a Master of Science in Business Analytics program, we present a taxonomy for data visualization courses and recommend content and pedagogical features for each type of data visualization course therein. We also discuss the interdependence between…

Students' knowledge of data analysis determines the quality of the research they report but they tend to perceive courses on statistics or data analysis as challenging and unappealing. The present study aimed to investigate the correlation between biology education students' attitudes toward statistics and their proficiency in determining various…

The purpose of this study was to develop and measure the usability of the software prototype of formative assessment in the LMS. This study was applied in terms of research objective and mixed method (qualitative-quantitative) in terms of data collection in which an exploratory sequential mixed methods design was used. In addition, in order to…

This paper interrogates whether technical democracy is well-suited to contend with possible technical controversies, including the increasing prevalence of EdTech in public schooling. Drawing across Habermasian 'deliberative democracy' that seeks consensus-derived resolution, as well as more agonistic approaches that embrace conflict as the means…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

The massive amount of text related to education provides rich information to support education in many aspects. In the meantime, the vast yet increasing volume of text makes it impossible to analyze manually. Text mining is a powerful tool to automatically analyze large-scaled texts and generate insights from the texts. However, many educational…