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Swygart-Hobaugh, Mandy; Anderson, Raeda; George, Denise; Glogowski, Joel – College & Research Libraries, 2022
We present findings from an exploratory quantitative content analysis case study of 156 doctoral dissertations from Georgia State University that investigates doctoral student researchers' methodology practices (used quantitative, qualitative, or mixed methods) and data practices (used primary data, secondary data, or both). We discuss the…
Descriptors: Doctoral Dissertations, Doctoral Students, Research Methodology, Data Collection
Christopher Cleveland; Jessica Markham – Annenberg Institute for School Reform at Brown University, 2024
Students with disabilities represent 15% of U.S. public school students. Individualized Education Programs (IEPs) inform how students with disabilities experience education. Very little is known about the aspects of IEPs as they are historically paper-based forms. In this study, we develop a coding taxonomy to categorize IEP goals into 10 subjects…
Descriptors: Individualized Education Programs, Special Needs Students, Special Education, Taxonomy
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Haim, Aaron; Gyurcsan, Robert; Baxter, Chris; Shaw, Stacy T.; Heffernan, Neil T. – International Educational Data Mining Society, 2023
Despite increased efforts to assess the adoption rates of open science and robustness of reproducibility in sub-disciplines of education technology, there is a lack of understanding of why some research is not reproducible. Prior work has taken the first step toward assessing reproducibility of research, but has assumed certain constraints which…
Descriptors: Conferences (Gatherings), Educational Research, Replication (Evaluation), Access to Information
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Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
Mindorff, David – ProQuest LLC, 2023
Practical work involving laboratory experiments is agreed upon to be an essential component of secondary science education. Practical work encompasses a broad range of activity types. The different forms of practical work are not equal in terms of cognitive demand and learning benefit. Inquiry-based investigations provide experience of cognitive…
Descriptors: Secondary Education, Science Education, Biology, Information Retrieval
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Knox, Jeremy – Learning, Media and Technology, 2023
This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…
Descriptors: Ethics, Artificial Intelligence, Social Justice, Governance
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Christine M. White; Stephanie A. Estrera; Christopher Schatschneider; Sara A. Hart – Grantee Submission, 2024
Researchers in the education sciences, like those in other disciplines, are increasingly encountering requirements and incentives to make the data supporting empirical research available to others. However, the process of preparing and sharing research data can be daunting. The present article aims to support researchers who are beginning to think…
Descriptors: Data, Educational Research, Information Dissemination, Incentives
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Mert Sen; Sevval Nur Sen; Tugrul Gökmen Sahin – Shanlax International Journal of Education, 2023
Today, the use of software in qualitative research analysis is rapidly becoming widespread among researchers. Researchers manage large data sets using features such as editing data, transcribing, creating codes, and searching within data. However, while the data analysis uses software in a format, the analysis of the essence of the data is done by…
Descriptors: Artificial Intelligence, Computer Software, Qualitative Research, Data Analysis
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Shen, Jian; Luo, Qiang – Best Evidence in Chinese Education, 2022
The development of school education depends on the quality of the education provided, and it is a key metric for assessing the effectiveness of schools in developing talent. Building specialized, intelligent education quality monitoring (EQM) databases is crucial for speeding EQM progress in the big data era. This article examines the development…
Descriptors: Educational Quality, Quality Assurance, Databases, Foreign Countries
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Lee, Chia-An; Huang, Nen-Fu; Tzeng, Jian-Wei; Tsai, Pin-Han – IEEE Transactions on Learning Technologies, 2023
Massive open online courses offer a valuable platform for efficient and flexible learning. They can improve teaching and learning effectiveness by enabling the evaluation of learning behaviors and the collection of feedback from students. The knowledge map approach constitutes a suitable tool for evaluating and presenting students' learning…
Descriptors: Artificial Intelligence, MOOCs, Concept Mapping, Student Evaluation
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Tiffany Tseng; Matt J. Davidson; Luis Morales-Navarro; Jennifer King Chen; Victoria Delaney; Mark Leibowitz; Jazbo Beason; R. Benjamin Shapiro – ACM Transactions on Computing Education, 2024
Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect…
Descriptors: Artificial Intelligence, Models, Data Processing, Design
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Han, Yuting; Wilson, Mark – Applied Measurement in Education, 2022
A technology-based problem-solving test can automatically capture all the actions of students when they complete tasks and save them as process data. Response sequences are the external manifestations of the latent intellectual activities of the students, and it contains rich information about students' abilities and different problem-solving…
Descriptors: Technology Uses in Education, Problem Solving, 21st Century Skills, Evaluation Methods
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Lindgren, Chris Aaron – Written Communication, 2021
Coding has typically been understood as an engineering practice, where the meaning of code has discrete boundaries as a technology that does precisely what it says. Multidisciplinary code studies reframed this technological perspective by positing code as the latest form of writing, where code's meaning is always partial and dependent on…
Descriptors: Coding, Data Processing, Data Analysis, Programming
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Patrick P. Weis; Wilfried Kunde – Cognitive Research: Principles and Implications, 2023
With ubiquitous computing, problems can be solved using more strategies than ever, though many strategies feature subpar performance. Here, we explored whether and how simple advice regarding when to use which strategy can improve performance. Specifically, we presented unfamiliar alphanumeric equations (e.g., A + 5 = F) and asked whether counting…
Descriptors: Information Retrieval, Information Technology, Computers, Data Processing
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Shawna Cox; Aaron Gilary; Svetlana Mosina; Jennifer Rhea; Dillon Simon; Teresa Thomas; Chenping Zhang; Maura Spiegelman – National Center for Education Statistics, 2024
The National Center for Education Statistics (NCES) sponsors the National Teacher and Principal Survey (NTPS) on behalf of the U.S. Department of Education in order to collect data on public and private schools, principals, and teachers in the United States. The U.S. Census Bureau conducts the survey for NCES. The NTPS provides data on the…
Descriptors: Teachers, Principals, Elementary Secondary Education, Administrators
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