Educational big data: Predictions, applications and challenges
Educational big data is becoming a strategic educational asset, exceptionally significant in
advancing educational reform. The term educational big data stems from the rapidly growing …
advancing educational reform. The term educational big data stems from the rapidly growing …
Prediction of student academic performance based on their emotional wellbeing and interaction on various e-learning platforms
Predicting student performance is crucial in higher education, as it facilitates course
selection and the development of appropriate future study plans. The process of supporting …
selection and the development of appropriate future study plans. The process of supporting …
[PDF][PDF] Systematic review of predicting student's performance in academics
Data mining (DM) gaining popularity due to its advantages in the educational environment.
Most of the educational institution, now a day applied these techniques to make …
Most of the educational institution, now a day applied these techniques to make …
[PDF][PDF] Supervised data mining approach for predicting student performance
Data mining approach has been successfully implemented in higher education and emerge
as an interesting area in educational data mining research. The approach is intended for …
as an interesting area in educational data mining research. The approach is intended for …
Educational data mining: Student performance prediction in academic
At present data mining techniques become very popular among the data analyst. It became
an effective tool for finding the uncovered information from a big database. Due to this …
an effective tool for finding the uncovered information from a big database. Due to this …
Predicting students at risk of academic failure using ensemble model during pandemic in a distance learning system
Predicting students at risk of academic failure is valuable for higher education institutions to
improve student performance. During the pandemic, with the transition to compulsory …
improve student performance. During the pandemic, with the transition to compulsory …
Modelos predictivos de riesgo académico en carreras de computación con minería de datos educativos
EA Franco, REL Martínez… - Revista de Educación a …, 2021 - revistas.um.es
Los problemas de bajo rendimiento académico y rezago son recurrentes en instituciones
educativas de nivel superior, especialmente al inicio de los estudios universitarios. En el …
educativas de nivel superior, especialmente al inicio de los estudios universitarios. En el …
Validation of a Digital Tool for Diagnosing Mathematical Proficiency.
P Junpeng, M Marwiang, S Chiajunthuk… - International Journal of …, 2020 - ERIC
This study was aimed to validate a digital tool for diagnosing mathematical proficiency in the
Number and Algebra strand of 1,504 Thai seventh-grade students. Researchers employed a …
Number and Algebra strand of 1,504 Thai seventh-grade students. Researchers employed a …
Testing the impact of novel assessment sources and machine learning methods on predictive outcome modeling in undergraduate biology
R Bertolini, SJ Finch, RH Nehm - Journal of Science Education and …, 2021 - Springer
High levels of attrition characterize undergraduate science courses in the USA. Predictive
analytics research seeks to build models that identify at-risk students and suggest …
analytics research seeks to build models that identify at-risk students and suggest …
A novel methodology using RNN+ LSTM+ ML for predicting student's academic performance
In the profession of education, predicting students' academic success is an essential
responsibility. This study introduces a novel methodology for predicting students' pass or fail …
responsibility. This study introduces a novel methodology for predicting students' pass or fail …