Student performance analysis and prediction in classroom learning: A review of educational data mining studies
Student performance modelling is one of the challenging and popular research topics in
educational data mining (EDM). Multiple factors influence the performance in non-linear …
educational data mining (EDM). Multiple factors influence the performance in non-linear …
A review on predicting student's performance using data mining techniques
AM Shahiri, W Husain - Procedia Computer Science, 2015 - Elsevier
Predicting students performance becomes more challenging due to the large volume of data
in educational databases. Currently in Malaysia, the lack of existing system to analyze and …
in educational databases. Currently in Malaysia, the lack of existing system to analyze and …
Predicting academic performance of students from VLE big data using deep learning models
The abundance of accessible educational data, supported by the technology-enhanced
learning platforms, provides opportunities to mine learning behavior of students, addressing …
learning platforms, provides opportunities to mine learning behavior of students, addressing …
Enhancing prediction of student success: Automated machine learning approach
H Zeineddine, U Braendle, A Farah - Computers & Electrical Engineering, 2021 - Elsevier
Students' success has recently become a primary strategic objective for most institutions of
higher education. With budget cuts and increasing operational costs, academic institutions …
higher education. With budget cuts and increasing operational costs, academic institutions …
Early segmentation of students according to their academic performance: A predictive modelling approach
The early classification of university students according to their potential academic
performance can be a useful strategy to mitigate failure, to promote the achievement of …
performance can be a useful strategy to mitigate failure, to promote the achievement of …
Connecting the dots–A literature review on learning analytics indicators from a learning design perspective
Background During the past decade, the increasingly heterogeneous field of learning
analytics has been critiqued for an over‐emphasis on data‐driven approaches at the …
analytics has been critiqued for an over‐emphasis on data‐driven approaches at the …
Utilizing multimodal data through fsQCA to explain engagement in adaptive learning
Investigating and explaining the patterns of learners' engagement in adaptive learning
conditions is a core issue towards improving the quality of personalized learning services …
conditions is a core issue towards improving the quality of personalized learning services …
Predicting student performance using sequence classification with time-based windows
A growing number of universities worldwide use various forms of online and blended
learning as part of their academic curricula. Furthermore, the recent changes caused by the …
learning as part of their academic curricula. Furthermore, the recent changes caused by the …
Implementing a learning analytics intervention and evaluation framework: What works?
Substantial progress in learning analytics research has been made in recent years to predict
which groups of learners are at risk. In this chapter, we argue that the largest challenge for …
which groups of learners are at risk. In this chapter, we argue that the largest challenge for …
EMT: Ensemble meta‐based tree model for predicting student performance
In recent decades, predicting the performance of students in the academic field has revealed
the attention by researchers for enhancing the weaknesses and provides support for future …
the attention by researchers for enhancing the weaknesses and provides support for future …