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Xing, Wanli; Lee, Hee-Sun; Shibani, Antonette – Educational Technology Research and Development, 2020
Constructing scientific arguments is an important practice for students because it helps them to make sense of data using scientific knowledge and within the conceptual and experimental boundaries of an investigation. In this study, we used a text mining method called Latent Dirichlet Allocation (LDA) to identify underlying patterns in students…
Descriptors: Persuasive Discourse, Science Instruction, Scientific Concepts, Logical Thinking
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Olsen, Jennifer K.; Sharma, Kshitij; Rummel, Nikol; Aleven, Vincent – British Journal of Educational Technology, 2020
The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated specific advantages of multiple modalities versus a single modality, especially combined…
Descriptors: Cooperative Learning, Learning Analytics, Data Use, Data Collection
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Nasir, Murtaza; Dag, Ali; Young, William A., II; Delen, Dursun – Decision Sciences Journal of Innovative Education, 2020
We are experiencing a significant shift in management practices--moving from intuition, experience, and gut-feeling driven decision-making to one that is driven by data, evidence, and computational sciences. This shift, which is often called the "analytics revolution," is not only changing the business landscape from a practical…
Descriptors: Job Skills, Business Administration, Labor Market, Decision Making
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Renz, André; Hilbig, Romy – International Journal of Educational Technology in Higher Education, 2020
The ongoing datafication of our social reality has resulted in the emergence of new data-based business models. This development is also reflected in the education market. An increasing number of educational technology (EdTech) companies are entering the traditional education market with data-based teaching and learning solutions, and they are…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Data Collection
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Bowen, G. Michael; Bartley, Anthony – Science Activities: Projects and Curriculum Ideas in STEM Classrooms, 2020
School science is often very different from "real world" science. One important difference, and possibly the main one, is that in school science the relationships between variables have often been sanitized -- essentially "cleaned up" -- so that there is very little (and often no) variation in the data from the relationship…
Descriptors: Science Instruction, Data, Science Activities, Authentic Learning
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Jia, Weichen; Peng, Jun; Cai, Na – Knowledge Management & E-Learning, 2020
Citespace, a visualization-based analysis tool, has been used to analyze the literature data by visualizing the patterns and potential trends of a field. Previous studies show that when used for analyzing the literature in Chinese, Citespace could only conduct very basic analysis, different from its use in analyzing the literature data in English.…
Descriptors: Visualization, Data Analysis, Trend Analysis, Chinese
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Bartholomew, Scott R.; McGraw, Tim; Fauber, Daphne; Charlesworth, Jon; Weitlauf, John – Technology and Engineering Teacher, 2020
Technological advances, artificial intelligence innovations, and widespread computing have all combined to necessitate a new generation of knowledge workers where data becomes a ubiquitous part of decision making (Sutton, 2006). Teaching today's students through the application of this "new" knowledge to long-established fields…
Descriptors: Sanitation, Water, Agriculture, High School Students
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Sabaityte, Jolanta; Davidaviciene, Vida; Karpoviciute, Roberta – World Journal on Educational Technology: Current Issues, 2020
For a competitive organisation, it is important to invest in employee's education to keep their knowledge up to date and ensure continuous growth in terms of employees' competence and skills. Continuous learning is considered as one of the success factors for the organisation, since this ensures constant growth of employees' competence that…
Descriptors: Data Analysis, Data Collection, Professional Continuing Education, Competence
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Rubleske, Joseph; Fletcher, Travis; Westerfeld, Brett – Journal of Instructional Pedagogies, 2020
Electronic sports (e-sports) can be defined as digital games played competitively for an audience (Hodge et al., 2017). With a global consumer base of roughly 450 million people and projected 2019 revenues of US$1.1 billion, the e-sports industry continues to grow (Pannekeet, 2019). Behind this growth is a thriving ecosystem which includes…
Descriptors: Computer Games, Athletics, Data Collection, Data Analysis
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Ponomarenko, Alexey N.; Svirina, Ekaterina M. – Statistics Education Research Journal, 2020
Typically, training in Russia for professionals includes school, university, and postgraduate education. People make their choice regarding university or job after school, and they choose jobs after university. These are very sensitive matters. Help in making the right choice is a real asset. The Russian Association of Statisticians (RASt) is an…
Descriptors: Foreign Countries, Statistics, Mathematics Education, Professional Associations
Makkonen, Reino; White, Melissa Eiler – WestEd, 2020
This knowledge brief is part of a continuing series designed to inform California education leaders about new research findings on key state policy topics. It summarizes recent findings on improving the access to, and the use of, teacher workforce data in California, and focuses on the importance of instituting a statewide teacher data system that…
Descriptors: Data Use, Data Collection, Decision Making, State Policy
Carolyn A. Wiley – ProQuest LLC, 2020
As federal guidelines have increased reporting demands on all sectors of education (United States Department of Education [USDOE], 2015) and state reporting requirements have expanded as legislatures call for performance-based funding (National Conference of State Legislatures, 2015), the need for institutional research offices has become the norm…
Descriptors: Institutional Research, Organizational Change, Data, Data Use
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Pustulka, Paula; Bell, Justyna; Trabka, Agnieszka – Field Methods, 2019
This article addresses methodological issues related to the consequences of researchers' range of insider identities that emerge over the course of completing subsequent stages of qualitative migration research projects. Taking on a temporal approach to the insider status evolving over the course of field entry, data collection, data analysis, and…
Descriptors: Migration, Social Science Research, Interviews, Researchers
Perez, Zeke, Jr.; von Zastrow, Claus – Education Commission of the States, 2023
Data governance is a core obligation for leaders and staff across any agency that collects, stores or uses individuals' data. It ensures that individuals' personal information is protected, and can support the continuous improvement of data quality and use, particularly when it includes well-defined processes, structure and responsibilities.…
Descriptors: Governance, Data Use, Privacy, Information Management
Barrett, Sharon Kebschull – Public Impact, 2023
When Dr. Tina Lupton and Dr. Timisha Barnes-Jones joined the Winston-Salem/Forsyth County Schools, Opportunity Culture implementation was happening in the midst of COVID. Lupton, the executive director of professional learning, and Barnes-Jones, the area superintendent for a network of 15 transformation schools, used their experience in other…
Descriptors: Superintendents, Educational Cooperation, Educational Opportunities, School Culture
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