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Korchi, Adil; Dardor, Mohamed; Mabrouk, El Houssine – Education and Information Technologies, 2020
Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…
Descriptors: Learning Analytics, Data, Computation, Mathematics
Young, Nicholas T.; Caballero, Marcos D. – Journal of Educational Data Mining, 2021
We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…
Descriptors: Prediction, Models, Learning Analytics, Mathematics
Thrall, Elizabeth S.; Lee, Seung Eun; Schrier, Joshua; Zhao, Yijun – Journal of Chemical Education, 2021
Techniques from the branch of artificial intelligence known as machine learning (ML) have been applied to a wide range of problems in chemistry. Nonetheless, there are very few examples of pedagogical activities to introduce ML to chemistry students in the chemistry education literature. Here we report a computational activity that introduces…
Descriptors: Undergraduate Students, Artificial Intelligence, Man Machine Systems, Science Education
Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
de León, Sara C.; Jiménez, Juan E.; García, Eduardo; Gutiérrez, Nuria; Gil, Verónica – Learning Disability Quarterly, 2021
The main purpose of this study was to validate the curriculum-based measure "Indicadores de Progreso de Aprendizaje en Matemáticas" (IPAM [Indicators of Basic Early Math Skills]) in a local, Spanish-speaking context. This tool has been designed to identify first-grade students at risk for mathematics learning disabilities. The IPAM…
Descriptors: Mathematics Skills, Curriculum Based Assessment, Grade 1, Elementary School Students
Mbaye, Baba – International Association for Development of the Information Society, 2018
The significant amount of information available on the web has led to difficulties for the learner to find useful information and relevant resources to carry out their training. The recommender systems have achieved significant success in the area of e-commerce, they still have difficulties in formulating relevant recommendations on e-learning…
Descriptors: Information Systems, Electronic Learning, Referral, Information Sources
Silva, Valtemir A.; Bittencourt, Ig Ibert; Maldonado, Jose C. – IEEE Transactions on Learning Technologies, 2019
Question classification is a key point in many applications, such as Question Answering (QA, e.g., Yahoo! Answers), Information Retrieval (IR, e.g., Google search engine), and E-learning systems (e.g., Bloom's tax. classifiers). This paper aims to carry out a systematic review of the literature on automatic question classifiers and the technology…
Descriptors: Questioning Techniques, Classification, Man Machine Systems, Information Retrieval
von Davier, Matthias – ETS Research Report Series, 2016
This report presents results on a parallel implementation of the expectation-maximization (EM) algorithm for multidimensional latent variable models. The developments presented here are based on code that parallelizes both the E step and the M step of the parallel-E parallel-M algorithm. Examples presented in this report include item response…
Descriptors: Psychometrics, Mathematics, Models, Statistical Analysis
Chiu, Chia-Yi; Köhn, Hans-Friedrich; Wu, Huey-Min – International Journal of Testing, 2016
The Reduced Reparameterized Unified Model (Reduced RUM) is a diagnostic classification model for educational assessment that has received considerable attention among psychometricians. However, the computational options for researchers and practitioners who wish to use the Reduced RUM in their work, but do not feel comfortable writing their own…
Descriptors: Educational Diagnosis, Classification, Models, Educational Assessment
Ding, Shuai – ProQuest LLC, 2013
The inverted index is the main data structure used by all the major search engines. Search engines build an inverted index on their collection to speed up query processing. As the size of the web grows, the length of the inverted list structures, which can easily grow to hundreds of MBs or even GBs for common terms (roughly linear in the size of…
Descriptors: Search Engines, Internet, Indexes, Information Retrieval
Wimmer, Hayden – ProQuest LLC, 2013
A large body of literature exists on evolutionary computing, genetic algorithms, decision trees, codified knowledge, and knowledge management systems; however, the intersection of these computing topics has not been widely researched. Moving through the set of all possible solutions--or traversing the search space--at random exhibits no control…
Descriptors: Knowledge Management, Management Systems, Mathematics, Computation
Salman, Raied – ProQuest LLC, 2012
The dissertation deals with clustering algorithms and transforming regression problems into classification problems. The main contributions of the dissertation are twofold; first, to improve (speed up) the clustering algorithms and second, to develop a strict learning environment for solving regression problems as classification tasks by using…
Descriptors: Classification, Mathematics, Regression (Statistics), Problem Solving
Lan, Liang – ProQuest LLC, 2012
In my dissertation, I will present my research which contributes to solve the following three open problems from biomedical informatics: (1) Multi-task approaches for microarray classification; (2) Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray…
Descriptors: Data Collection, Mathematics, Computation, Classification
Kuksa, Pavel – ProQuest LLC, 2011
Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…
Descriptors: Data Analysis, Computation, Mathematics, Methods
Wilkerson-Jerde, Michelle Hoda – Educational Technology Research and Development, 2014
There are increasing calls to prepare K-12 students to use computational tools and principles when exploring scientific or mathematical phenomena. The purpose of this paper is to explore whether and how constructionist computer-supported collaborative environments can explicitly engage students in this practice. The Categorizer is a…
Descriptors: Computation, Classification, Computer Uses in Education, Cooperative Learning
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