The theory of learning styles applied to distance learning

RD Costa, GF Souza, RAM Valentim… - Cognitive Systems …, 2020‏ - Elsevier
Distance Education (DE) associated with the use of Virtual Learning Environments (VLE) as
interaction tools between the student and the educator has become a large research niche …

Active methodology, educational data mining and learning analytics: A systematic map** study

TL de ANDRADE, SJ Rigo, JLV Barbosa - Informatics in Education, 2021‏ - ceeol.com
Distance Learning has enabled educational practices based on digital platforms, generating
massive amounts of data. Several initiatives use this data to identify dropout contexts, mainly …

Predicting Master's students' academic performance: an empirical study in Germany

S Alturki, L Cohausz, H Stuckenschmidt - Smart Learning Environments, 2022‏ - Springer
The tremendous growth in electronic educational data creates the need to have meaningful
information extracted from it. Educational Data Mining (EDM) is an exciting research area …

[PDF][PDF] Dropout prediction and reduction in distance education courses with the learning analytics multitrail approach.

WL Cambruzzi, SJ Rigo, JLV Barbosa - J. Univers. Comput. Sci., 2015‏ - researchgate.net
Distance Education courses are present in large number of educational institutions. Virtual
Learning Environments development contributes to this wide adoption of Distance …

Educational Data Mining for Dropout Prediction: Trends, Opportunities, and Challenges

MP Colpo, TT Primo, MS de Aguiar… - Revista Brasileira de …, 2024‏ - journals-sol.sbc.org.br
Atualmente, enfrentamos prejuízos acadêmicos, sociais e econômicos associados à evasão
estudantil. Vários estudos têm aplicado técnicas de mineração de dados a conjuntos de …

WAVE: an architecture for predicting dropout in undergraduate courses using EDM

LMB Manhães, SMS da Cruz, G Zimbrão - Proceedings of the 29th …, 2014‏ - dl.acm.org
Predicting the academic progress of student is an issue faced by many public universities in
emerging countries. Although, those institutions stores large amounts of educational data …

Educational data mining: An application of regressors in predicting school dropout

RLS do Nascimento, RB das Neves Junior… - Machine Learning and …, 2018‏ - Springer
School dropout is one of the great challenges for the educational system. Educational data
mining seeks to study and contribute with results that aim to hidden problems and find …

Algorithm applied: attracting MSEs to business associations

J Moraes, JL Schaefer, JNC Schreiber… - Journal of Business & …, 2020‏ - emerald.com
Purpose This paper aims to propose a structured model based on a data mining algorithm
that can calculate, based on business association (BA) attributes, the probability of micro …

A comparative study between clustering methods in educational data mining

JLC Ramos, RED e Silva, JCS Silva… - IEEE Latin America …, 2016‏ - ieeexplore.ieee.org
This paper aims to describe the analysis of data from the Moodle's database of a beginner
class in Distance Education of a Federal University using distinct educational data mining …

Forecasting students' performance through self-regulated learning behavioral analysis

RL Rodrigues, JLC Ramos, JCS Silva… - International Journal of …, 2019‏ - igi-global.com
The increasing use of the Learning Management Systems (LMSs) is making available an
ever-growing, volume of data from interactions between teachers and students. This study …