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Associating students and teachers for tutoring in higher education using clustering and data mining

https://doi.org/10.1002/cae.21839
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Developing and assessing college student teamwork skills
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Applying Data Mining Techniques to Identify Success Factors in Students Enrolled in Distance Learning: A Case Study
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Data Mining: Practical Machine Learning Tools and Techniques
inferredcites →https://doi.org/10.1016/j.chb.2017.01.047openalex-snapshot
Evaluating the effectiveness of educational data mining techniques for early prediction of students' academic failure in introductory programming courses
inferredcites →https://doi.org/10.1016/j.eswa.2006.04.005openalex-snapshot
Educational data mining: A survey from 1995 to 2005
inferredcites →https://doi.org/10.1016/j.eswa.2012.02.063openalex-snapshot
Data mining techniques and applications – A decade review from 2000 to 2011
inferredcites →https://doi.org/10.1016/j.eswa.2013.08.042openalex-snapshot
Educational data mining: A survey and a data mining-based analysis of recent works
inferredcites →https://doi.org/10.1075/nlp.12openalex-snapshot
Literary Detective Work on the Computer
inferredcites →https://doi.org/10.1109/cw.2016.27openalex-snapshot
Classification Algorithms to Predict Students' Extraversion-Introversion Traits
inferredcites →https://doi.org/10.1109/educon.2010.5492460openalex-snapshot
Developing global teamwork skills: The Runestone project
inferredcites →https://doi.org/10.1109/icelete.2013.6644359openalex-snapshot
Clustering moodle data as a tool for profiling students
inferredcites →https://doi.org/10.1109/nuicone.2013.6780070openalex-snapshot
An optimized farthest first clustering algorithm
inferredcites →https://doi.org/10.1109/tsmcc.2010.2053532openalex-snapshot
Educational Data Mining: A Review of the State of the Art
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.14689/ejer.2014.54.12openalex-snapshot
Early Prediction of Students’ Grade Point Averages at Graduation: A Data Mining Approach
inferredcites →https://doi.org/10.4324/9780203761212openalex-snapshot
Mentoring and Tutoring by Students
inferredcites →https://doi.org/10.7763/ijcte.2015.v7.923openalex-snapshot
Identifying Hidden Patterns in Students' Feedback through Cluster Analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Skill‐based education through fuzzy knowledge modeling for e‐learning
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A Systematic Review of Educational Data Mining
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Multi-fair Capacitated Students-Topics Grouping Problem
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Clustering IoT Data Using Machine Learning Methods: A Survey
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Student’s Employability Concern for Colleges and Universities
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A Review of Clustering Models in Educational Data Science Toward Fairness-Aware Learning
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A two-phase machine learning approach for predicting student outcomes
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Variance-based differential evolution algorithm with an optional crossover for data clustering
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A new validity clustering index-based on finding new centroid positions using the mean of clustered data to determine the optimum number of clusters
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Knowledge discovery through higher education census data
inferred← citeshttps://doi.org/10.1109/fie43999.2019.9028400openalex-snapshot
Clustering Analysis of Student Learning Outcomes Based on Education Data
inferred← citeshttps://doi.org/10.22662/ijasc.2022.4.3.007openalex-snapshot
Cluster Analysis of Learning Management System (LMS) Performance : A Diagnostic Assessment
inferred← citeshttps://doi.org/10.2478/amns-2025-0531openalex-snapshot
Extraction and analysis of individual features of students’ ideological and political education based on big data clustering algorithm
inferred← citeshttps://doi.org/10.3233/jifs-179793openalex-snapshot
Modeling of performance evaluation of educational information based on big data deep learning and cloud platform
inferred← citeshttps://doi.org/10.32628/cseit25113331openalex-snapshot
A Systematic Review on Artificial Intelligence Trends in Education
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Atributos relevantes del trabajo en equipo basados en la percepción de estudiantes de posgrado y su efecto para generar aprendizaje
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Predicting Academic Success of College Students Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.5944/educxx1.21302openalex-snapshot
¿Qué necesita el alumnado de la tutoría universitaria? Validación de un instrumento de medida a través de un análisis multivariante
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