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Sean M. Baser; William B. Walker Jr.; Matt T. Dean; Mónica Maldonado – State Higher Education Executive Officers, 2025
State regulators are the central authority in higher-education oversight, charged with ensuring consumer protection and quality assurance within the regulatory triad. Yet gaps remain in the understanding of regulatory renewal processes, their real-world implementation, and the capacity challenges these agencies face. To address this, State Higher…
Descriptors: Higher Education, State Regulation, Governance, Accountability
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Juliette Woodrow; Sanmi Koyejo; Chris Piech – International Educational Data Mining Society, 2025
High-quality feedback requires understanding of a student's work, insights into what concepts would help them improve, and language that matches the preferences of the specific teaching team. While Large Language Models (LLMs) can generate coherent feedback, adapting these responses to align with specific teacher preferences remains an open…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Attitudes, Preferences
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Seyed Parsa Neshaei; Richard Lee Davis; Paola Mejia-Domenzain; Tanya Nazaretsky; Tanja Käser – International Educational Data Mining Society, 2025
Deep learning models for text classification have been increasingly used in intelligent tutoring systems and educational writing assistants. However, the scarcity of data in many educational settings, as well as certain imbalances in counts among the annotated labels of educational datasets, limits the generalizability and expressiveness of…
Descriptors: Artificial Intelligence, Classification, Natural Language Processing, Technology Uses in Education
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Osei Ampadu; Kaitlin Hanak; Laura D'Antonio – National Center for Education Statistics, 2025
This documentation is for the Provisional File Version 1a of the School-Level Finance Survey (SLFS) for school year (SY) 2021-22, fiscal year 2022 (FY 22) conducted by the National Center for Education Statistics (NCES). It contains a brief description of the data collection in conjunction with information required to understand and access the…
Descriptors: Educational Finance, School Surveys, Data Collection, Elementary Schools
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Gabrielle Lam; Isgard Hueck; Christian Rivera; Patricia Widder – Biomedical Engineering Education, 2025
Biomedical engineering is a rapidly evolving field, with the pace of evolution spurred by technological advancements, the increasing complexity of human health challenges, and globalization of the workforce. It is timely for biomedical engineering educators to explore afresh the competencies that graduates need at present, but more importantly,…
Descriptors: Biomedicine, Engineering Education, College Graduates, Futures (of Society)
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Sara Dada – American Journal of Evaluation, 2025
Realist evaluations, a form of theory-driven evaluation, aim to explain how, why, for whom, and to what extent a complex health intervention works (or does not work). Realist evaluations are often "methods-flexible" and encourage the appropriate use of a range of evidence types that provide explanatory value. However, there is a lack of…
Descriptors: Planning, Data Collection, Evaluation Methods, Realism
Soulafa Al Khatib – Sage Research Methods Cases, 2025
This Case Study examines the challenges of positionality in researching female leadership in education. It is based on research that investigated the leadership styles that female school principals in the United Arab Emirates adopted based on the influence of female gender and national culture. The research adopted a mixed-method approach and was…
Descriptors: Data Collection, Leadership Styles, Women Administrators, Principals
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Ahmad Slim; Chaouki Abdallah; Elisha Allen; Michael Hickman; Ameer Slim – International Educational Data Mining Society, 2025
Curricular design in higher education significantly impacts student success and institutional performance. However, academic programs' complexity--shaped by pass rates, prerequisite dependencies, and course repeat policies--creates challenges for administrators. This paper presents a method for modeling curricular pathways including development of…
Descriptors: Curriculum Design, Integrated Curriculum, Data Analysis, Monte Carlo Methods
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Epameinondas Panagopoulos; Ioannis Kamarianos – Open Journal for Educational Research, 2025
This paper emphasizes the divergences in quantitative and qualitative methodological approaches when exploring trust relationships in school units. We focus on how participants responded and how the results were interpreted. This study, based on such design, questionnaires, and semi-structured interviews to understand trust among teachers and…
Descriptors: Statistical Analysis, Qualitative Research, Research Methodology, Trust (Psychology)
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Alnuaman Alamin; Ahmed Tlili; Guoxiang Wu – Review of Education, 2025
Nomadic communities face major challenges in providing education for their children due to their lifestyle. These challenges have been shaped by various cultural, ethnic and political factors. This requires personalised interventions to maintain education for nomadic students in different regions. However, little is known in the literature about…
Descriptors: Foreign Countries, Migrants, Access to Education, Barriers
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Eric Landers; Caitlin Criss; Kathryn L. Haughney; Cynthia C. Massey; Stephanie Devine; Karin Fisher – Georgia Educational Researcher, 2025
New pathways are needed to recruit high-quality special education graduates to meet the urgent teacher shortage. As a result, the researchers were awarded a grant from the CEEDAR Technical Assistance Center at the University of Florida to conduct a pilot study on special education teacher recruitment. The pilot study examined the correlation of…
Descriptors: Special Education, Special Education Teachers, Teacher Recruitment, Social Media
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Chang Cai; Shengxin Hong; Min Ma; Haiyue Feng; Sixuan Du; Minyang Chow; Winnie Li-Lian Teo; Siyuan Liu; Xiuyi Fan – Education and Information Technologies, 2025
Analyzing the teaching and learning environment (TLE) through student feedback is essential for identifying curricular gaps and improving teaching practices. However, traditional feedback analysis methods, particularly for qualitative data, are often time-consuming and prone to human bias. Large Language Models (LLMs) offer a promising solution by…
Descriptors: Educational Environment, Feedback (Response), Measures (Individuals), Natural Language Processing
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Xiuling He; Leyao Zhang; Yangyang Li; Xiong Xiao; Haojie Wang; Di Wu – Education and Information Technologies, 2025
With the development of mobile Internet and digital technologies, online education platforms transcend time and space constraints to provide ubiquitous learning environments. However, high dropout rates and low pass rates pose a great challenge. Predicting student performance enables early identification of academic failure tendencies,…
Descriptors: Prediction, Online Courses, Electronic Learning, Data Use
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Daiki Matsumoto; Atsushi Shimada; Yuta Taniguchi – International Association for Development of the Information Society, 2025
Predicting learner actions and intentions is crucial for providing personalized real-time support and early intervention in programming education. This approach enables proactive, context-aware assistance that is difficult for human instructors to deliver by foreseeing signs of potential struggles and misconceptions, or by inferring a learner's…
Descriptors: Prediction, Programming, Coding, Models
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Louch, Michelle E.; Pry, Michael – Information Systems Education Journal, 2020
According to the cliché, it is not what one says so much as how one says it. In the business world, those words ring particularly true. How one presents information can influence all forms of business decisions, from level of investment to expansion to downsizing and everything in between. This brings up significant questions relating to the…
Descriptors: Ethics, Data, Deception, Data Analysis
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