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Alturki, Sarah; Alturki, Nazik; Stuckenschmidt, Heiner – Journal of Information Technology Education: Innovations in Practice, 2021
Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students' academic achievement early using Educational Data Mining (EDM). This study aims to predict students' final grades and identify honorary students at…
Descriptors: Data Collection, Data Analysis, Grade Prediction, Academic Achievement
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Tebeck, Claudette – Science Teacher, 2021
School closures in the wake of the COVID-19 pandemic led to kids asking pertinent questions about why they were not in school, especially some students suffering financial hardship. Virtual classrooms became the mundane venues for students to piece together the pandemic puzzle and unpack unseen inequities. This article examines disparities that…
Descriptors: COVID-19, Pandemics, Racial Differences, Science Instruction
National College Attainment Network, 2021
Tracking and using data to inform decisions pays off for college success programs on multiple levels. Having data allows program staff to monitor the progress of individual students and tailor support to their particular needs. It enables staff to understand the effectiveness of program activities and make improvements as necessary. Most…
Descriptors: College Programs, Success, Data Collection, Data Analysis
Justin B. Doromal; Erica Greenberg; Elli Nikolopoulos; Eve Mefferd; Heather Sandstrom; Rachel Lamb; Victoria Nelson; Timothy Triplett – Urban Institute, 2024
Early childhood educators play essential roles in providing stable and high-quality child care for young children and supporting their development and growth. As is also true nationwide, historically low wages in the District of Columbia have led to challenges in compensating and retaining qualified early childhood educators, and in turn, building…
Descriptors: Program Implementation, Early Childhood Education, Educational Equity (Finance), Educational Finance
Sauder, Adrienne E.; Gilson, Cindy M. – Gifted Child Quarterly, 2023
There is a growing body of literature around digital research, specifically regarding data collection and how to pivot research designs to be more conducive to online and virtual research, but little in the way of how to analyze data remotely. In this article, we share firsthand experiences from a qualitative study utilizing Google apps, Zoom, and…
Descriptors: Academically Gifted, Gifted Education, Qualitative Research, Data Collection
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Flippin, Michelle – Teaching and Learning in Communication Sciences & Disorders, 2023
Language sample analysis (LSA) is valuable clinical tool and an important component of comprehensive language assessment. However, LSA is underutilized in real-world practice. SLPs have identified time constraints, insufficient training, and lack of confidence in LSA skills as barriers to regular LSA implementation. Communication science and…
Descriptors: Student Attitudes, Language Tests, Sampling, Language Impairments
Paschall, Katherine; Connors, Maia – Child Trends, 2023
Child Trends and Start Early have partnered to better understand what early childhood systems builders need to build and support more equitable systems. The briefs in this series, called Conversation Starters, define a new framework for early childhood systems that center families' experiences and raise key considerations and next steps for…
Descriptors: Young Children, Early Childhood Education, Family Involvement, Equal Education
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
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Knight, Jim; Faggella-Luby, Michael – Learning Professional, 2022
Data is so deeply woven into the fabric of people's lives that it is next to impossible to imagine what a data-free life would be like. But despite the centrality of data in everyone's personal lives, when people talk about data in schools, their comments are often negative. The authors of this article believe "data" should not be a…
Descriptors: Coaching (Performance), Teacher Effectiveness, Instructional Effectiveness, Data Use
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Kopacz, Maria A. – Communication Teacher, 2022
Audience analysis is essential for creating successful messages across communication fields. The audience persona is an effective tool for understanding the characteristics and needs of a target audience. Through this unit activity, students experience the process of persona development, build skills in data collection and analysis, and gain…
Descriptors: Audience Awareness, Data Analysis, Data Collection, Skill Development
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Imamoglu, Mehmet; Erbas, Cagdas; Dikmen, Cemal Hakan – Online Submission, 2022
The purpose of this study was to examine the studies related to augmented reality applications in sports science and to discuss the results based on this. Articles selected for analysis were found through searches journals in the Web of Science database from 1975 to 2018 were examined and searched using the keywords ("physical education"…
Descriptors: Trend Analysis, Educational Trends, Simulated Environment, Physical Education
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Kayleigh K. Hyde; Marlena N. Novack; Nicholas LaHaye; Chelsea Parlett-Pelleriti; Raymond Anden; Dennis R. Dixon; Erik Linstead – Review Journal of Autism and Developmental Disorders, 2019
Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Clinical Diagnosis, Intervention
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Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
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Bridges, Eileen – Journal of Marketing Education, 2021
This article looks back over the past two decades to describe how teaching of undergraduate marketing research has (or has not) changed. Sweeping changes in technology and society have certainly affected how marketing research is designed and implemented--but how has this affected teaching of this important topic? Although the purpose of marketing…
Descriptors: Marketing, Undergraduate Students, Educational Change, Teaching Methods
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Hartong, Sigrid; Piattoeva, Nelli – Critical Studies in Education, 2021
This paper contributes to a growing body of research on the increasing datafication of schooling, which has become a salient topic in comparative education and education policy research. Specifically, we address the rising scholarly concern about the meaning of (comparing) contexts as bounded localities facing an increasingly fluid and generative…
Descriptors: Data Analysis, Comparative Education, Educational Policy, Standardized Tests
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