Predicting academic performance: a systematic literature review

A Hellas, P Ihantola, A Petersen, VV Ajanovski… - … companion of the 23rd …, 2018 - dl.acm.org
The ability to predict student performance in a course or program creates opportunities to
improve educational outcomes. With effective performance prediction approaches …

A review of research on machine learning in educational technology

C Korkmaz, AP Correia - Educational Media International, 2019 - Taylor & Francis
The purpose of this review is to investigate the trends in the body of research on machine
learning in educational technologies, published between 2007 and 2017. The criteria for …

Neural-fuzzy with representative sets for prediction of student performance

LH Son, H Fujita - Applied Intelligence, 2019 - Springer
In this paper, a new method for handling the Multi-Input Multi-Output Student Academic
Performance Prediction (MIMO SAPP) problem is proposed. The MIMO SAPP aims to predict …

Predicting students at risk of academic failure using ensemble model during pandemic in a distance learning system

H Karalar, C Kapucu, H Gürüler - International Journal of Educational …, 2021 - Springer
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 …

Fuzzy-based active learning for predicting student academic performance using autoML: a step-wise approach

M Tsiakmaki, G Kostopoulos, S Kotsiantis… - Journal of Computing in …, 2021 - Springer
Predicting students' learning outcomes is one of the main topics of interest in the area of
Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning …

Meta-analysis of student performance assessment using fuzzy logic

N Amelia, AG Abdullah, Y Mulyadi - Indonesian Journal of Science …, 2019 - ejournal.kjpupi.id
The assessment system generally requires transparency and objectivity to assess student
performance in terms of abstraction. Fuzzy logic method has been used as one of the best …

An extensive study and comparison of the various approaches to object detection using deep learning

U Subbiah, DK Kumar, SK Thangavel… - … on Smart Electronics …, 2020 - ieeexplore.ieee.org
Smart spaces are specialized environments developed to enable the automatic monitoring
of events in a monitored setting. Smart surveillance uses deep learning for object detection …

A comprehensive adaptive system for e-learning of foreign languages

V Bradac, B Walek - Expert systems with applications, 2017 - Elsevier
The article presents a proposal, design and implementation of a new approach to adaptive e-
learning systems. First, a proposal of a model is presented. This model aims at introducing …

A fuzzy model for reasoning and predicting student's academic performance

MO Hegazi, B Almaslukh, K Siddig - Applied Sciences, 2023 - mdpi.com
Evaluating students' academic performance is crucial for assessing the quality of education
and educational strategies. However, it can be challenging to predict and evaluate …

Data augmentation and deep neuro-fuzzy network for student performance prediction with MapReduce framework

AJ Baruah, S Baruah - International Journal of Automation and Computing, 2021 - Springer
The main aim of an educational institute is to offer high-quality education to students. The
system to achieve better quality in the educational system is to find the knowledge from …