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)…

Purpose: Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches -- in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and…

The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term "actionable insight" means. This selective literature review provides a look into…

Data rules schools and ignorance is far from bliss. From assessment results to questioning educational claims, there is a growing need to understand the numbers used in education. Education data blogger and teacher Richard Selfridge (aka Jack Marwood) unravels the complexities of dealing with educational data and explains statistics in an…

What is the link between neuroscience and education? Can one measure the phenomenon of learning and make predictions by charting student performance? How does the knowledge of neuroscience inform educators to objectively and effectively meet the unique needs of all learners and address discrepancies in subsets of student population? Questions like…

The American School Counselor Association (ASCA) calls on school counselors to take part in collaborative work experiences using data to address problems of practice. School counselors experience professional isolation leading to underperformance (Elliot et al., 2004; Stone-Johnson, 2015). School structures that lack collaborative experiences for…