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Chenguang Pan; Zhou Zhang – International Educational Data Mining Society, 2024
There is less attention on examining algorithmic fairness in secondary education dropout predictions. Also, the inclusion of protected attributes in machine learning models remains a subject of debate. This study delves into the use of machine learning models for predicting high school dropouts, focusing on the role of protected attributes like…
Descriptors: High School Students, Dropouts, Dropout Characteristics, Artificial Intelligence
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Anna McDougall; Douglas McKee; George Orlov – Journal of Economic Education, 2025
While the field of economics lacks diversity, there is little consensus on the underlying causes of or most effective solutions to this problem. The authors of this article combine data from the Integrated Postsecondary Education Data System (IPEDS) with data from their own survey of U.S. economics departments to identify institution and…
Descriptors: Student Diversity, Economics Education, Departments, Undergraduate Students
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Tahlia Lasczik; Alexandra Lasczik; Amy Cutter-Mackenzie-Knowles – International Journal of Art & Design Education, 2025
The rise in the number of young people disengaged from mainstream schooling is reaching critical proportions. This paper explores a child-framed participatory inquiry known as The Walking A/r/tography Project, which sought to challenge, empower and engage youth at risk in one Special Assistance Secondary School in Southeast Queensland through…
Descriptors: Foreign Countries, Secondary School Students, Student Projects, Student Research
Victoria L. Bernhardt – Eye on Education, 2025
With the 5th Edition of Data Analysis for Continuous School Improvement, best-selling Victoria Bernhardt has written the go-to-resource for data analysis in your school! By incorporating collaborative structures to implement, monitor, and evaluate the vision and continuous improvement plan, this book provides a framework to show learning…
Descriptors: Learning Analytics, Data Analysis, Educational Improvement, Evaluation Methods
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Corrie Wilder; Shannon Calderone – Impacting Education: Journal on Transforming Professional Practice, 2025
This study explores the integration of generative artificial intelligence (AI) into qualitative research within a higher education context. Through a collaborative self-study, a doctoral candidate and their dissertation supervisor examined the application of Google's Gemini 1.5 to analyze interview data from a dissertation of practice (DiP)…
Descriptors: Technology Integration, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Robert M. Johnstone – Educational Considerations, 2025
This article explores utilizing a post-graduation success lens to help community college leaders frame the challenges of achieving equitable improvement for their students. Specifically, it posits that providing and exploring customized labor market data presented in an accessible format can help institutional leaders provide a "true…
Descriptors: Community College Students, College Graduates, Outcomes of Education, Success
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Candace Walkington; Matthew Bernacki; Elizabeth Leyva; Brooke Istas – Journal for Research in Mathematics Education, 2025
Algebra has been identified as a gatekeeper to careers in STEM, but little research exists on how algebra appears for practitioners in the workplace. Surveys and interviews were conducted with 77 STEM practitioners from a variety of fields, examining how they reported using algebraic functions in their work. Survey and interview reports suggest…
Descriptors: Algebra, Mathematics, Computation, Mathematical Formulas
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Xavier Ochoa; Xiaomeng Huang; Yuli Shao – Journal of Learning Analytics, 2025
Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…
Descriptors: Learning Analytics, Artificial Intelligence, Computer Software, Scores
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Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
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Nathan Jones; Lindsey Kaler; Jessica Markham; Josefina Senese; Marcus A. Winters – Educational Researcher, 2025
Students with and without disabilities may be educated across various service delivery models (SDMs): general education, cotaught, pull-out, and self-contained. Still, evidence for their relative effectiveness at scale remains limited. Using longitudinal administrative data from Indiana, we measured the effect of different SDMs on test scores,…
Descriptors: Students with Disabilities, Teaching Methods, Students, Instructional Effectiveness
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Krista Bixler; Marjorie Ceballos – Leadership and Policy in Schools, 2025
Instructional leadership is a complex dimension, which requires that principals possess expertise in goal setting, leading the instructional program, and creating the conditions for a successful school environment. Effective instructional leaders manage the instructional program by planning, coordinating, and evaluating the work of teachers and…
Descriptors: Principals, Instructional Leadership, Artificial Intelligence, Educational Technology
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Qixuan Wu; Hyung Jae Chang; Long Ma – Journal of Advanced Academics, 2025
It is very important to identify talented students as soon as they are admitted to college so that appropriate resources are provided and allocated to them to optimize and excel in their education. Currently, this process is labor-intensive and time-consuming, as it involves manual reviews of each student's academic record. This raises the…
Descriptors: Electronic Learning, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Ge Bai – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…
Descriptors: Student Centered Learning, English Instruction, College Instruction, College Students
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Denise McWilliams; Ash Mady; Cindi Smatt – Journal of Information Systems Education, 2025
Efficient and profitable business operations today rely on the use of advanced technologies. This is particularly evident in managing family farms in the competitive broiler chicken industry. Farmers raising broiler chickens from chick to optimum weight in five weeks require investments in and use of smart farming technologies employing the…
Descriptors: Internet, Farm Management, Animals, Artificial Intelligence
Joanna Rosak-Szyrocka, Editor; Shashi Kant Gupta, Editor; Muhammad Shahbaz, Editor; Markus A. Launer, Editor – Routledge, Taylor & Francis Group, 2025
"Enhancing Smart Universities with Emotional Intelligence" investigates the successful blending of technology innovations and human beings' emotional intelligence within higher education institutions in the midst of digital transformation. Today's "smart" universities improve student experiences, expedite administrative…
Descriptors: Universities, Electronic Learning, Emotional Intelligence, Technological Literacy
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