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Cho, Eunsoon; Cho, Young Hoan; Grant, Michael M.; Song, Donggil; Huh, Yeol – TechTrends: Linking Research and Practice to Improve Learning, 2020
The Korean Society for Educational Technology (KSET) hosted its second panel discussion partnering with the Association for Educational Communications and Technology (AECT) at the 2019 AECT Convention in Las Vegas, Nevada. A total of four panelists, two from Korea and two from the U.S., participated in the discussion on the trends of educational…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Telecommunications
Ariyachandra, Thilini – Information Systems Education Journal, 2020
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…
Descriptors: Skill Development, Undergraduate Students, Data Analysis, Data Use
Hayes, Aneta; Cheng, Jie – Teaching in Higher Education, 2020
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…
Descriptors: Educational Quality, Data Collection, Data Analysis, Teacher Effectiveness
Okoye, Kingsley; Arrona-Palacios, Arturo; Camacho-Zuñiga, Claudia; Hammout, Nisrine; Nakamura, Emilia Luttmann; Escamilla, Jose; Hosseini, Samira – International Journal of Educational Technology in Higher Education, 2020
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…
Descriptors: Data Collection, Data Analysis, Student Attitudes, Student Evaluation of Teacher Performance
Dapiton, Ethelbert P.; Canlas, Ranie B. – European Journal of Educational Research, 2020
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…
Descriptors: College Faculty, Data Analysis, Productivity, Reputation
Craig, Scotty D.; Li, Siyuan; Prewitt, Deborah; Morgan, Laurie A.; Schroeder, Noah L. – Advanced Distributed Learning Initiative, 2020
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…
Descriptors: Distance Education, Educational Technology, Learning Analytics, Data Collection
Complete College America, 2020
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…
Descriptors: Postsecondary Education, Partnerships in Education, Data Analysis, Data Use
Clavié, Benjamin; Gal, Kobi – International Educational Data Mining Society, 2020
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…
Descriptors: Student Behavior, Electronic Learning, Metadata, Prediction
Aulck, Lovenoor; Nambi, Dev; West, Jevin – International Educational Data Mining Society, 2020
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…
Descriptors: Resource Allocation, Scholarships, Artificial Intelligence, Data Analysis
Eaton, Sarah Elaine – Online Submission, 2020
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…
Descriptors: Data Collection, Minority Group Students, Racial Bias, Student Behavior
Marion, Scott – National Center for the Improvement of Educational Assessment, 2020
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…
Descriptors: Educational Opportunities, Equal Education, Data Collection, COVID-19
Marjorie Cohen; Steve Klein; Cherise Moore – Career and Technical Education Research Network, 2020
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)…
Descriptors: Vocational Education, Units of Study, Data Use, Training Objectives
Link, Michael – Quality Assurance in Education: An International Perspective, 2018
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…
Descriptors: Sampling, Data Collection, Trend Analysis, Data
Jørnø, Rasmus Leth; Gynther, Karsten – Journal of Learning Analytics, 2018
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…
Descriptors: Data Analysis, Learning, Educational Research, Definitions
Selfridge, Richard – SAGE Publications Ltd (UK), 2018
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…
Descriptors: Evaluation, Data Analysis, Numbers, Graphs

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