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Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
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Machado, Crystiano José Richard; Maciel, Alexandre Magno Andrade; Rodrigues, Rodrigo Lins – International Journal of Distance Education Technologies, 2019
Discussion forums in learning management systems (LMS) have been shown to promote student interaction and contribute to the collaborative practice in the teaching-learning process. By evaluating the postings, teachers can identify students with learning difficulties. However, due to the large volume of posts that are generated on a daily basis in…
Descriptors: Discussion Groups, Integrated Learning Systems, Learning Problems, Content Analysis
Yan, Yilin – ProQuest LLC, 2018
The development in information science has enabled an explosive growth of data, which attracts more and more researchers to engage in the field of big data analytics. Noticeably, in many real-world applications, large amounts of data are imbalanced data since the events of interests occur infrequently. Classification of imbalanced data is an…
Descriptors: Information Science, Information Retrieval, Multimedia Materials, Data
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – Grantee Submission, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Sequential Learning, Data Collection, Information Retrieval, Evaluation Methods
Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman – Online Submission, 2015
The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…
Descriptors: Science Achievement, Mathematics Achievement, Information Retrieval, Data Analysis
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Michalski, Greg V. – Community College Journal of Research and Practice, 2014
Excessive course attrition is costly to both the student and the institution. While most institutions have systems to quantify and report the numbers, far less attention is typically paid to each student's reason(s) for withdrawal. In this case study, text analytics was used to analyze a large set of open-ended written comments in which students…
Descriptors: Student Attrition, Withdrawal (Education), Data Analysis, Models
Lu, Kun – ProQuest LLC, 2012
The performance of information retrieval systems varies significantly by test topics. Even for those systems that have performed well on average, the results for some difficult topics are still poor. Previous studies have revealed that different optimization techniques should be used for those difficult topics. However, a prerequisite of the…
Descriptors: Information Retrieval, Information Systems, Difficulty Level, Predictor Variables
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – International Educational Data Mining Society, 2015
The field of EDM has focused more on modeling student knowledge than on investigating what sequences of different activity types achieve good learning outcomes. In this paper we consider three activity types, targeting sense-making, induction and refinement, and fluency building. We investigate what mix of the three types might be most effective…
Descriptors: Information Retrieval, Data Analysis, Learning Activities, Grade 4
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman – Journal of Education in Science, Environment and Health, 2015
The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…
Descriptors: Science Achievement, Information Retrieval, Data Analysis, Middle School Students
Shafat, Gabriel; Levin, Ilya – International Association for Development of the Information Society, 2012
This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…
Descriptors: Foreign Countries, Information Seeking, Online Searching, Search Strategies
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Kuo, Fan-Ray; Hwang, Gwo-Jen; Chen, Szu-Chuang; Chen, Sherry Y. – Educational Technology & Society, 2012
Enhancing students' problem-solving abilities has been recognized as an important and challenging issue for technology-enhanced learning. Thus, previous research has attempted to address this issue by developing various mechanisms, among which a cognitive apprenticeship model can particularly enhance students' abilities. However, it is not clear…
Descriptors: Apprenticeships, Cognitive Style, Problem Solving, Cooperative Learning
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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Carmo, Mafalda, Ed. – Online Submission, 2017
This book contains a compilation of papers presented at the International Conference on Education and New Developments (END 2017), organized by the World Institute for Advanced Research and Science (W.I.A.R.S.). Education, in our contemporary world, is a right since we are born. Every experience has a formative effect on the constitution of the…
Descriptors: Educational Quality, Models, Vocational Education, Outcomes of Education
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