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Leo Van Audenhove; Lotte Vermeire; Wendy Van den Broeck; Andy Demeulenaere – Information and Learning Sciences, 2024
Purpose: The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as…
Descriptors: Data Analysis, Data Collection, Information Literacy, Foreign Countries
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Nicolas Frölich; Karl Sebastian Schellhammer – International Journal of Mathematical Education in Science and Technology, 2024
Introductory undergraduate statistics courses widely focus on statistical concepts or software-based data analysis. Despite the fact that the analysis of real data has shown to enhance students' engagement, the step of data collection is often neglected. Once students know the challenges of data collection, they are more aware of potential…
Descriptors: Undergraduate Students, Statistics, Business Administration Education, Economics Education
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Natasha Arthars; Kate Thompson; Henk Huijser; Steven Kickbusch; Samuel Cunningham; Gavin Winter; Roger Cook; Lori Lockyer – Australasian Journal of Educational Technology, 2024
Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…
Descriptors: Formative Evaluation, Cooperative Learning, College Students, Student Evaluation
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Jamie S. Wylie; Rebecca J. Namenek Brouwer; Derek M. Jones; Geeta K. Swamy – Journal of Research Administration, 2024
Research-intensive institutions rely on specialized central offices to support research administrators and investigators through various processes and requirements. This helps researchers successfully and compliantly conduct and manage research. However, when these support offices communicate their processes and resources from disparate locations,…
Descriptors: Research Administration, Research Tools, Research Universities, Web Sites
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Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
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Kristabel Stark; Jessica Koslouski – TEACHING Exceptional Children, 2024
Considering the salience of emotions in their work, special educators should think of them as an important source of data to inform and improve their practice. Special educators' emotions and emotional labor are a rich and accessible form of data that can directly inform their delivery of high-quality instruction. Although special educators…
Descriptors: Special Education, Special Education Teachers, Psychological Patterns, Emotional Intelligence
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Tel Amiel – Prospects, 2024
Public educational systems and institutions have increased their adoption of proprietary educational platforms offered by large private corporations. Platforms now critically mediate content creation and storage, interaction and communication, record-keeping and institutional memory. This platformization of education has led to significant risks…
Descriptors: Open Education, Educational Technology, Higher Education, Governance
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Hussain, Sadiq; Gaftandzhieva, Silvia; Maniruzzaman, Md.; Doneva, Rositsa; Muhsin, Zahraa Fadhil – Education and Information Technologies, 2021
Educational data mining helps the educational institutions to perform effectively and efficiently by exploiting the data related to all its stakeholders. It can help the at-risk students, develop recommendation systems and alert the students at different levels. It is beneficial to the students, educators and authorities as a whole. Deep learning…
Descriptors: Regression (Statistics), Academic Achievement, Learning Analytics, Models
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Meylan, Stephan C.; Griffiths, Thomas L. – Cognitive Science, 2021
Language research has come to rely heavily on large-scale, web-based datasets. These datasets can present significant methodological challenges, requiring researchers to make a number of decisions about how they are collected, represented, and analyzed. These decisions often concern long-standing challenges in corpus-based language research,…
Descriptors: Data Analysis, Data Collection, Word Frequency, Prediction
Seda Sakar; Sema Tan – Gifted Child Quarterly, 2025
Many articles have been published in gifted education in recent years. This study aims to provide a comprehensive review of the evolution of academic studies in gifted education. In this context, the structural topic modeling (STM) method was used to analyze the topics and trends in the field. STM is a machine learning technique that utilizes…
Descriptors: Gifted Education, Educational Trends, Educational Research, Research Methodology
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Kary Zarate; Veronica Kang; Daniel M. Maggin – Preventing School Failure, 2025
Many of the decisions made related to student progress and intervention selection rely on data. In their roles, paraeducators often implement academic interventions; therefore, they must be prepared to monitor students' progress accurately and reliably. This pilot randomized control trial tested the effects of a remote training package on…
Descriptors: Paraprofessional School Personnel, Training, Data Collection, Reading Fluency
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Melissa A. Gallagher; Jennifer E. Scholla – Mathematics Teacher: Learning and Teaching PK-12, 2025
Adaptive teachers use student data to guide instruction. Learn about using an anecdotal record form to support adaptive teaching. In this article, the authors describe how teachers can use learning trajectories to make adaptive decisions to meet the needs of their students. They provide an example using the U .S. Math Recovery Council's learning…
Descriptors: Mathematics Instruction, Learning Trajectories, Developmentally Appropriate Practices, Student Needs
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Ulrike Krein – Leadership and Policy in Schools, 2025
In the context of digital transformation processes in schools, the introduction of technology is often discussed in terms of the individualization and optimization of teaching, learning and school management. However, it is often neglected that technologies are preconfigured and provide socio-material offers that invite certain actions and thus…
Descriptors: Educational Technology, Technology Uses in Education, Technology Integration, School Administration
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Mostafa M. Samy; Mohamed A. Metwally; Mahmoud Ashry; Wael M. Elmayyah – Measurement: Interdisciplinary Research and Perspectives, 2025
Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…
Descriptors: Engines, Power Technology, Data Collection, Data Interpretation
Joshua Bleiberg; Tuan D. Nguyen – Annenberg Institute for School Reform at Brown University, 2025
Educator labor markets vary considerably across the country and can change quickly during recessions. We use data from the Quality Workforce Indicators (QWI) on educators in Elementary and Secondary Schools from 2000-01 to 2022-23. We demonstrate how to transform the quarter-level data in the QWI to construct valid educator labor market measures.…
Descriptors: Elementary School Teachers, Secondary School Teachers, Faculty Mobility, Teacher Burnout
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