Publication Date
| In 2026 | 0 |
| Since 2025 | 603 |
| Since 2022 (last 5 years) | 4040 |
| Since 2017 (last 10 years) | 10297 |
| Since 2007 (last 20 years) | 25774 |
Descriptor
Source
Author
Publication Type
Education Level
Audience
| Practitioners | 2919 |
| Researchers | 1806 |
| Teachers | 1758 |
| Policymakers | 1607 |
| Administrators | 1185 |
| Students | 321 |
| Media Staff | 307 |
| Community | 264 |
| Parents | 114 |
| Counselors | 79 |
| Support Staff | 36 |
| More ▼ | |
Location
| United States | 1496 |
| Canada | 1404 |
| Australia | 1401 |
| California | 1309 |
| Texas | 915 |
| New York | 819 |
| United Kingdom | 781 |
| Florida | 715 |
| Illinois | 618 |
| North Carolina | 555 |
| Pennsylvania | 528 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 13 |
| Meets WWC Standards with or without Reservations | 21 |
| Does not meet standards | 24 |
Pongchanun Luangpaiboon; Chiramet Phinkrathok; Walailak Atthirawong; Pasura Aungkulanon – SAGE Open, 2024
The education faculty aims to assess departmental effectiveness by analyzing the relationship between service levels, output variables, and input variables. This objective is coupled with the formulation of faculty development strategies tailored to enhance efficiency while accommodating individual professionals' unique requirements and…
Descriptors: Decision Making, College Faculty, Simulation, Efficiency
Seyma Birinci – ProQuest LLC, 2024
The purpose of this study was to explore how teachers engaged in data use for instructional decision making. A grounded theory research design was used to analyze interviews of 10 special education teachers. Special education teachers were asked to complete an online survey and were interviewed with questions to reveal their experiences with…
Descriptors: Individualized Instruction, Decision Making, Data Use, Special Education Teachers
Ian Greener – International Journal of Social Research Methodology, 2024
This paper argues for three aspects of tolerance with respect to QCA research: tolerance with respect to different approaches to QCA; producing QCA research with tolerance (work that is resistant to criticism); and for QCA researchers to be clear about the tolerance of the solutions they present -- especially in terms of calibration and truth…
Descriptors: Qualitative Research, Research Methodology, Comparative Analysis, Research Design
Bronwen Cowie; Suzanne Trask; Frances Edwards – British Educational Research Journal, 2024
The need to make evidence and implications of educational research widely available has prompted a burgeoning interest in knowledge mobilisation, which is a set of strategies supporting the active and intentional dissemination of research knowledge. For this, it is important to consider who might be the intended audience and end-users of this…
Descriptors: Teacher Researchers, Information Dissemination, Action Research, Educational Research
Cristobal Salinas Jr.; Diana Cervantes – Journal of Cases in Educational Leadership, 2024
The term Latinx has received increasing levels of pushback from different entities outside and within higher education. Despite the term's wide popularity in academic spaces, higher education practitioners often utilize it without understanding whom it simultaneously includes and excludes, and whom the term refers to. Such practice perpetuates the…
Descriptors: Hispanic Americans, Definitions, Language Usage, Higher Education
Bin Tan; Hao-Yue Jin; Maria Cutumisu – Computer Science Education, 2024
Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…
Descriptors: Computation, Thinking Skills, Artificial Intelligence, Student Evaluation
Mouna Denden; Ahmed Tlili; Nian-Shing Chen; Mourad Abed; Mohamed Jemni; Fathi Essalmi – Interactive Learning Environments, 2024
Gamification has gained an increasing attention from researchers and practitioners in various domains including education as it can increase learners' engagement and motivation. However, little is known about how educational gamification experiences can be influenced by learners' characteristics. Therefore, this study provides a systematic…
Descriptors: Gamification, Educational Games, Educational Research, Data Collection
Cuilan Qiao; Yuqing Chen; Qing Guo; Yunwei Yu – International Journal of STEM Education, 2024
In the era defined by the fourth paradigm of science research, the burgeoning volume of science data poses a formidable challenge. The established data-related requisites within science literacy now fall short of addressing the evolving needs of researchers and STEM students. Consequently, the emergence of science data literacy becomes imperative.…
Descriptors: Scientific Literacy, Data, STEM Education, Majors (Students)
Natsumi Ueda; Adrianna Kezar – Cogent Education, 2024
Leadership programs for college students have significantly expanded over the past decades. However, there remains a lack of systematic synthesis regarding pedagogical practices employed in these programs. This article aims to fill this research gap by presenting a systematic review of empirical studies examining pedagogies in formal leadership…
Descriptors: Literature Reviews, College Students, Student Leadership, Leadership Training
Annina Heini; Krzysztof Kredens – International Journal of Social Research Methodology, 2024
This article reports on our experience of collecting language data from informants in video-conferencing settings under a research design originally developed with face-to-face interactions in mind. We had set out to investigate whether individual stylistic features persist in different modes of textual production and designed a complex set of…
Descriptors: Data Collection, Sociolinguistics, Distance Education, COVID-19
Tsubasa Minematsu; Atsushi Shimada – International Association for Development of the Information Society, 2024
In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…
Descriptors: Educational Technology, Technology Uses in Education, Error Patterns, Sentences
Hiromichi Hagihara; Mikako Ishibashi; Yusuke Moriguchi; Yuta Shinya – Developmental Science, 2024
Scale errors are intriguing phenomena in which a child tries to perform an object-specific action on a tiny object. Several viewpoints explaining the developmental mechanisms underlying scale errors exist; however, there is no unified account of how different factors interact and affect scale errors, and the statistical approaches used in the…
Descriptors: Measurement, Error of Measurement, Meta Analysis, Data Analysis
Children's Bureau, Office of the Administration for Children & Families, 2024
The National Youth in Transition Database (NYTD) snapshots offer a glimpse of National and State trends for young people who are receiving Independent Living Services through state child welfare programs. This Outcomes Data Snapshot shows statistical trends about who those young people are, their experiences and outcomes for those both in care and…
Descriptors: Transitional Programs, Daily Living Skills, Independent Living, Statistical Data
Hongwen Guo; Matthew S. Johnson; Daniel F. McCaffrey; Lixong Gu – ETS Research Report Series, 2024
The multistage testing (MST) design has been gaining attention and popularity in educational assessments. For testing programs that have small test-taker samples, it is challenging to calibrate new items to replenish the item pool. In the current research, we used the item pools from an operational MST program to illustrate how research studies…
Descriptors: Test Items, Test Construction, Sample Size, Scaling
Emily J. Barnes – ProQuest LLC, 2024
This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…
Descriptors: Artificial Intelligence, Higher Education, Models, Prediction

Peer reviewed
Direct link
