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Showing 1 to 15 of 78 results Save | Export
Kathryn Gray – ProQuest LLC, 2024
Graph data, especially large graph data, come up in many domains, such as social networks, the map of science, biological data, and even knitting! This presents a problem when we consider visualizing these structures. Layouts must be chosen carefully so that the structure of the graph is visible. Some graphs are large enough and connected enough…
Descriptors: Visualization, Graphs, Layout (Publications), Readability
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Zeynab (Artemis) Mohseni; Italo Masiello; Rafael M. Martins – Education and Information Technologies, 2024
There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…
Descriptors: Elementary School Students, Data, Individual Development, Learning Trajectories
Ruediger, Dylan – ITHAKA S+R, 2021
Ithaka S+R's Research Support Services program's most recent project, "Supporting Big Data Research," focused specifically on the rapidly emerging use of big data in research across disciplines and fields. As part of this study, they partnered with librarians from more than 20 colleges and universities, who then conducted over 200…
Descriptors: Colleges, Universities, Data Analysis, Data Collection
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Fincham, Ed; Gasevic, Dragan; Jovanovic, Jelena; Pardo, Abelardo – IEEE Transactions on Learning Technologies, 2019
Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature that has extracted invaluable information from such sources, it suffers from a number of shortcomings. For instance, it has been shown that surveys often provide insight into students' perceptions about learning rather…
Descriptors: Study Habits, Learning Strategies, Independent Study, Educational Research
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Mikroyannidis, Alexander; Gómez-Goiri, Aitor; Smith, Andrew; Domingue, John – Interactive Learning Environments, 2020
The main challenges commonly associated with acquiring practical network engineering skills are the requirements for access to specialised and up-to-date network equipment, as well as the high costs associated with obtaining and maintaining this equipment. The PT Anywhere initiative addresses these challenges by offering a mobile environment for…
Descriptors: Computer Science Education, Computer Networks, Data Analysis, Engineering
SungYong, Um – ProQuest LLC, 2016
Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among…
Descriptors: Electronic Publishing, Electronic Journals, Ecology, Computer System Design
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Han, Kwan Hee; Hwang, Boram; Jeon, Jeonghwan – Innovations in Education and Teaching International, 2015
The university's website is a useful tool in disseminating information to current and future college students and is supportive of the university's administrative activities. However, as the university's website began including more and more information and the design of it has become gradually more complex, it has become hard to find desired…
Descriptors: Web Sites, Navigation (Information Systems), Universities, Departments
Lewkow, Nicholas; Zimmerman, Neil; Riedesel, Mark; Essa, Alfred – International Educational Data Mining Society, 2015
Next generation digital learning environments require delivering "just-in-time feedback" to learners and those who support them. Unlike traditional business intelligence environments, streaming data requires resilient infrastructure that can move data at scale from heterogeneous data sources, process the data quickly for use across…
Descriptors: Electronic Learning, Data Analysis, Higher Education, Elementary Secondary Education
Bodily, Robert; Graham, Charles R.; Bush, Michael D. – Educational Technology, 2017
This article describes the crossroads between learning analytics and learner engagement. The authors do this by describing specific challenges of using analytics to support student engagement from three distinct perspectives: pedagogical considerations, technological issues, and interface design concerns. While engaging online learners presents a…
Descriptors: Learner Engagement, Online Courses, Educational Opportunities, Barriers
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Goldschmidt, Ronaldo; Fernandes de Souza, Isabel; Norris, Monica; Passos, Claudio; Ferlin, Claudia; Cavalcanti, Maria Claudia; Soares, Jorge – Informatics in Education, 2016
The use of computers as teaching and learning tools plays a particularly important role in modern society. Within this scenario, Brazil launched its own version of the "One Laptop per Child" (OLPC) program, and this initiative, termed PROUCA, has already distributed hundreds of low-cost laptops for educational purposes in many Brazilian…
Descriptors: Data Collection, Data Analysis, Computer Uses in Education, Foreign Countries
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Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Themes in Science and Technology Education, 2016
Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…
Descriptors: Predictive Measurement, Decision Support Systems, Academic Achievement, Exit Examinations
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Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Drane, Daniel, III – ProQuest LLC, 2017
This study uses a sequential, mixed method, action research, quantitative to qualitative research design. The purpose of this study was to develop a useful standardized hiring process at a state medical college that brings clarity to the hiring process and policies. Two conceptual frameworks guided the innovations in this study--communities of…
Descriptors: Medical Schools, Personnel Selection, Database Management Systems, Human Resources
Rihák, Jirí – International Educational Data Mining Society, 2015
In this work we introduce the system for adaptive practice of foundations of mathematics. Adaptivity of the system is primarily provided by selection of suitable tasks, which uses information from a domain model and a student model. The domain model does not use prerequisites but works with splitting skills to more concrete sub-skills. The student…
Descriptors: Mathematics Achievement, Mathematics Skills, Models, Reaction Time
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Angeli, Charoula; Valanides, Nicos – Educational Technology Research and Development, 2013
The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI)…
Descriptors: College Students, Computer System Design, Cognitive Style, Immigration
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