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Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use
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Villanueva Manjarres, Andrés; Moreno Sandoval, Luis Gabriel; Salinas Suárez, Martha Janneth – Digital Education Review, 2018
Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…
Descriptors: Information Retrieval, Data Analysis, Educational Environment, Research Methodology
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Schwendimann, Beat A.; Rodriguez-Triana, Maria Jesus; Vozniuk, Andrii; Prieto, Luis P.; Boroujeni, Mina Shirvani; Holzer, Adrian; Gillet, Denis; Dillenbourg, Pierre – IEEE Transactions on Learning Technologies, 2017
This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning…
Descriptors: Literature Reviews, Educational Research, Data Analysis, Data Processing
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Stapel, Martin; Zheng, Zhilin; Pinkwart, Niels – International Educational Data Mining Society, 2016
The number of e-learning platforms and blended learning environments is continuously increasing and has sparked a lot of research around improvements of educational processes. Here, the ability to accurately predict student performance plays a vital role. Previous studies commonly focused on the construction of predictors tailored to a formal…
Descriptors: Teaching Methods, Academic Achievement, Electronic Learning, Mathematics Instruction
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Antoniadou, Victoria; Dooly, Melinda – Research-publishing.net, 2017
This chapter aims to answer some of the questions that emerge when carrying out educational ethnography in a blended learning environment. The authors first outline how Virtual Ethnography (VE) has been developed and applied by other researchers. Then, to better illustrate the approach, they describe a doctoral research project that implemented…
Descriptors: Ethnography, Blended Learning, Educational Environment, Educational Research
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Moore, Emily, Ed.; Dooly, Melinda, Ed. – Research-publishing.net, 2017
This handbook has been conceived as a guide for young researchers embarking on the exciting journey of investigating different aspects of plurilingual education. The text can also serve to review ideas previously encountered, and perhaps as a means of interrogating research methodologies in plurilingual contexts for those who already have ample…
Descriptors: Qualitative Research, Research Methodology, Multilingualism, Guides
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Ting, Choo-Yee; Ho, Chiung Ching – British Journal of Educational Technology, 2015
This paper presents the dataset collected from student interactions with INQPRO, a computer-based scientific inquiry learning environment. The dataset contains records of 100 students and is divided into two portions. The first portion comprises (1) "raw log data", capturing the student's name, interfaces visited, the interface…
Descriptors: Inquiry, Educational Environment, Scientific Methodology, Interaction
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Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
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Rupp, André A.; Nugent, Rebecca; Nelson, Brian – Journal of Educational Data Mining, 2012
In recent years the educational community has increasingly embraced digital technologies for the purposes of developing alternative learning environments, providing diagnostic feedback, and fostering the development of so-called 21st-century skills. This special issue is dedicated to bridging recent work from the disciplines of educational and…
Descriptors: Electronic Learning, Psychometrics, Educational Environment, Educational Technology
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Huebner, Richard A. – Research in Higher Education Journal, 2013
Educational data mining (EDM) is an emerging discipline that focuses on applying data mining tools and techniques to educationally related data. The discipline focuses on analyzing educational data to develop models for improving learning experiences and improving institutional effectiveness. A literature review on educational data mining topics…
Descriptors: Educational Research, Data Processing, Data Analysis, Organizational Change
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Levy, Sharona T.; Wilensky, Uri – Computers & Education, 2011
This study lies at an intersection between advancing educational data mining methods for detecting students' knowledge-in-action and the broader question of how conceptual and mathematical forms of knowing interact in exploring complex chemical systems. More specifically, it investigates students' inquiry actions in three computer-based models of…
Descriptors: Test Content, Mathematical Models, Prior Learning, Data Processing
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Mathies, Charles; Valimaa, Jussi – Tertiary Education and Management, 2013
Recent changes in European higher education have accompanied a strong desire and need by national ministries to have comparable data across institutions and a growing recognition from campus leaders that effective planning and decision-making requires reliable institutional data and analyses. This has induced changes and restructuring of duties…
Descriptors: Higher Education, Institutional Evaluation, Governance, Data Analysis
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Zur, Ayala; Eisikovits, Rivka A. – International Journal of Qualitative Studies in Education (QSE), 2011
The study presents a phenomenologically based research procedure, whose intent is to examine people's school experience and the meaning they ascribe to "school." Participants in this investigative endeavor are instructed to sketch an "ideal school," present their plan in a visual-schematic manner, and provide an oral and written description of…
Descriptors: Research Tools, Educational Experience, Educational Environment, Phenomenology
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Alinaghi, Tannaz; Bahreininejad, Ardeshir – International Journal of Distance Education Technologies, 2011
The increasing advances of new Internet technologies in all application domains have changed life styles and interactions. E-learning and collaborative learning environment systems are originated through such changes and aim at providing facilities for people in different times and geographical locations to cooperate, collaborate, learn and work…
Descriptors: Electronic Learning, Educational Environment, Questioning Techniques, Responses
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