States' commitments to tackling long standing inequities have been stifled by missing data, long delays, insufficient data-analysis tools, and the excessive reporting burden placed on states and institutions. If states hope to achieve their completion and equity goals, they need access to data that does not leave them guessing--so they can…

We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…

Effectively estimating student enrollment and recruiting students is critical to the success of any university. However, despite having an abundance of data and researchers at the forefront of data science, traditional universities are not fully leveraging machine learning and data mining approaches to improve their enrollment management…

Massive online Open Courses (MOOCs) make extensive use of videos. Students interact with them by pausing, seeking forward or backward, replaying segments, etc. We can reasonably assume that students have different patterns of video interactions, but it remains hard to compare student video interactions. Some methods were developed, such as Markov…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

The purpose of this study was to evaluate the relationship of pre-entrance factors and the success of students in an Associate of Applied Science (A.A.S.) degree nursing program at a community college in East Tennessee. The criterion variable was success in the nursing program. Success was defined as academic success in all nursing courses and…

Probabilistic reasoning underpins much of middle school students' future work in data analysis and inferential statistics. Unfortunately for many middle school students, probabilistic reasoning is not intuitive. One specific area in which students seem to struggle is determining the probability of compound events (Moritz and Watson 2000). Research…

Purpose: This paper explores the challenges of conducting qualitative research from ELT (English Language Teaching) Ph.D. candidates' perspectives. Design/methodology/approach: The participants of the study consisted of 30 Iranian Ph.D. students majoring in ELT. The semi-structured interview was employed to investigate the heart of experiences,…

Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…

The use of large, open-source data sets is ubiquitous in scientific research. Scientists--ranging from meteorologists to chemists to epidemiologists--are researching and investigating critical questions using data that they have not themselves collected. To contribute to the growing effort to bring data science into classrooms, the authors have…

Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…

With the impactful nature of the COVID-19 pandemic, this manuscript describes a teaching case for COVID-19 vaccinations to develop students' knowledge of analytics and supply chain management. The experiential learning activity is developed in the context of an undergraduate upper-level course on descriptive analytics and data visualization. The…

The development of digital technologies has created a market need for specialists working with the big data that is necessary for making management decisions. This study aims to identify the skills structure of the data analyst profession (DAP) in Russia. The authors used a program code written in Python to examine relevant vacancies extracted…

The Organization of Economic, Cooperation and Development's Programme for International Student Assessment (OECD's PISA) is explored as a site of science as an actor managing a social life. Its calculations form at the interstices of multiple historical lines as a comparative reason about nations, societies, and populations. That reason is…

Drawing upon the growing datafication of contemporary schooling, our purpose in this article is to use topological thinking as an analytical device to better understand the professionals and practices within emergent data infrastructures. We address this by attending to an influential national (and subnational) data infrastructure of school…