During the past decade, digital transformation enabled by big data and analytics emerged as a key theme in the business world. It promises to continue be a theme of major importance in the 2020s. Digital transformation comes at the cost of grappling with and analyzing the ever-growing volume of data. Data visualization techniques are seen as a…

The paper critiques key international teaching excellence and higher education outcomes frameworks for their lack of attention to epistemic equality. It subsequently argues that adequate 'datafication' of these frameworks, to demonstrate the extent to which universities offer teaching experiences which promote intellectual equivalence of all…

Today, modern educational models are concerned with the development of the teacher-student experience and the potential opportunities it presents. User-centric analyses are useful both in terms of the socio-technical perspective on data usage within the educational domain and the positive impact that data-driven methods have. Moreover, the use of…

Research productivity plays an important role in the prestige and reputation among higher education institutions. However, the time spent to do research among Filipino academics is the most pressing issue since they can barely meet the requirement for research productivity. Further, the lack of time for data gathering aggravated the drawbacks for…

The Science of Learning and Readiness (SoLaR) project seeks to demonstrate to Defense and other Government stakeholders the "art of the possible" for high-quality distributed learning and to create a practical guide for how to infuse such qualities into the broader Department of Defense (DoD) distributed learning ecosystem. This report…

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…

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…

In March 2020, the coronavirus pandemic and attending shift to remote schooling initiated a dramatic impact on student learning, an impact that state and district leaders feel a sense of urgency to understand and address. These leaders are accustomed using state and district test data to shed light on student achievement and growth. But without…

As the education and workforce development community looks more and more to CTE to help ensure students are both college and career ready, understanding and using CTE data and research becomes increasingly important. This is the first in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE)…

Instructors may design and implement formative assessments on technology-enhanced platforms (e.g., online quizzes) with the intention of encouraging the use of effective learning strategies like active retrieval of information and spaced practice among their students. However, when students interact with unsupervised technology-enhanced learning…

Keystroke logging is used to automatically record writers' unfolding typing process and to get insight into moments when they struggle composing text. However, it is not clear which and how features from the keystroke log map to higher-level cognitive processes, such as planning and revision. This study aims to investigate the sensitivity of…

In this paper, we argue for a view of analysis as an embodied practice and review others' testimonies of carrying out multimodal ethnography. This review suggests that metaphors are key for communicating what happens to "us" in the course of the research and our subsequent sense-making practices. We identify four metaphors for…

When exposed to principal components analysis for the first time, students can sometimes miss the primary purpose of the analysis. Often the focus is solely on data reduction and what to do after the dimensions of the data have been reduced is ignored. The datasets discussed here can be used as an in-class example, a homework assignment, or a…