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Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
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Bradshaw, Laine; Levy, Roy – Educational Measurement: Issues and Practice, 2019
Although much research has been conducted on the psychometric properties of cognitive diagnostic models, they are only recently being used in operational settings to provide results to examinees and other stakeholders. Using this newer class of models in practice comes with a fresh challenge for diagnostic assessment developers: effectively…
Descriptors: Data Interpretation, Probability, Classification, Diagnostic Tests
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Martínez Abad, Fernando; Chaparro Caso López, Alicia A. – School Effectiveness and School Improvement, 2017
In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…
Descriptors: Foreign Countries, Data Collection, Statistical Analysis, Evaluation Methods
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Boaduo, Nana Adu-Pipim – Educational Research and Reviews, 2011
Two basic data sources required for research studies have been secondary and primary. Secondary data collection helps the researcher to provide relevant background to the study and are, in most cases, available for retrieval from recorded sources. Primary data collection requires the researcher to venture into the field where the study is to take…
Descriptors: Research Problems, Writing Research, Research Methodology, Data Collection
Humphrey, Pamela A. – ProQuest LLC, 2010
The purpose of this study is to explore and describe the process of alliance creation and maintenance between U.S. institutions of higher education and enterprises in Hong Kong. The methodology is a qualitative case study in which administrators from U.S. universities offering programs in Hong Kong and administrators from organizations in Hong…
Descriptors: Colleges, Foreign Countries, Data Analysis, Content Analysis
Castellano, Katherine E.; Ho, Andrew D. – Council of Chief State School Officers, 2013
This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…
Descriptors: Guides, Models, Academic Achievement, Achievement Gains
Swenson, Sandra Signe – ProQuest LLC, 2010
Professionally developed and freely accessible through the Internet, scientific data maps have great potential for teaching and learning with data in the science classroom. Solving problems or developing ideas while using data maps of Earth phenomena in the science classroom may help students to understand the nature and process of science. Little…
Descriptors: Majors (Students), Public Colleges, Maps, Internet