Journal ArticleDOI
Data mining in education
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TLDR
Key milestones and the current state of affairs in the field of EDM are reviewed, together with specific applications, tools, and future insights.Abstract:
Applying data mining DM in education is an emerging interdisciplinary research field also known as educational data mining EDM. It is concerned with developing methods for exploring the unique types of data that come from educational environments. Its goal is to better understand how students learn and identify the settings in which they learn to improve educational outcomes and to gain insights into and explain educational phenomena. Educational information systems can store a huge amount of potential data from multiple sources coming in different formats and at different granularity levels. Each particular educational problem has a specific objective with special characteristics that require a different treatment of the mining problem. The issues mean that traditional DM techniques cannot be applied directly to these types of data and problems. As a consequence, the knowledge discovery process has to be adapted and some specific DM techniques are needed. This paper introduces and reviews key milestones and the current state of affairs in the field of EDM, together with specific applications, tools, and future insights. © 2012 Wiley Periodicals, Inc.read more
Citations
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Proceedings ArticleDOI
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C‐BEAM: A confidence‐based evaluation of MCQs for providing feedback to instructors
Abdul Aleem,Manoj Madhava Gore +1 more
TL;DR: A novel Confidence‐Based Evaluation Approach for MCQs (C‐BEAM) is proposed that curb the use of probabilistic prediction and association rule mining methods are applied to the evaluation data generated from C‐ BEAM method for discovering association rules.
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Classification and Prediction of Students’ GPA Using K-Means Clustering Algorithm to Assist Student Admission Process
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References
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Journal ArticleDOI
Educational Data Mining: A Review of the State of the Art
TL;DR: The most relevant studies carried out in educational data mining to date are surveyed and the different groups of user, types of educational environments, and the data they provide are described.
Journal ArticleDOI
Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge
TL;DR: An effort to model students' changing knowledge state during skill acquisition and a series of studies is reviewed that examine the empirical validity of knowledge tracing and has led to modifications in the process.
Journal ArticleDOI
Educational data mining: A survey from 1995 to 2005
TL;DR: This paper surveys the application of data mining to traditional educational systems, particular web- based courses, well-known learning content management systems, and adaptive and intelligent web-based educational systems.
Proceedings ArticleDOI
The State of Educational Data Mining in 2009: A Review and Future Visions
Ryan S. Baker,Kalina Yacef +1 more
TL;DR: This paper reviewed the history and current trends in the field of EDM and discussed trends and shifts in the research conducted by this community, and discussed the increased emphasis on prediction, the emergence of work using existing models to make scientific discoveries, and the reduction in the frequency of relationship mining within the EDM community.
Journal ArticleDOI
Data mining in course management systems: Moodle case study and tutorial
TL;DR: This work describes the full process for mining e-learning data step by step as well as how to apply the main data mining techniques used, such as statistics, visualization, classification, clustering and association rule mining of Moodle data.
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