… The literature review is presented in Section II. It is followed … an ensemble of machine learning
and deep learning models. … identify students with potential difficulties as early as possible, …

… review where studies using ensemble learning techniques for … and 85% failure prediction
accuracy and provided a potential … employs machine learning models to improve the prediction …

… the combinational incremental ensemble of classifiers for student performance prediction. In
… Saurabh Pal [26] proposed a predictive model to identify the possible student dropouts by …

… its implications and suggests possible future directions. … can be used to predict student dropout
and compare the results with … feature analysis study is recommended to help the agents of …

… It can potentially benefit the competitive educational domain to … machine learning algorithms
[40] and ensemble algorithm are recommended to optimize the result for predicting student …

… devotion, bad actions could be recommended and therefore undesirable and inappropriate
… recommender system, using different machine learning algorithms, is proposed for predicting …

… placed on predicting, as early as possible, vulnerable students who … Yet, the review of the
literature in this area shows a lack of … This implies that our Ensemble Model resulting from the …

… [4] built a graduate recommender system for students aspiring … the forecast of every individual
network, it has the potential to … machine learning algorithms to the proposed method in …

… of the student performance model, we used ensemble methods … Researchers in machine
learning, pattern recognition, and … to improve and provide the best learning resources possible. …

… The author discussed the rule-based approach, lexicon-based approach, machine
learning approach and hybrid approach for performing sentiment analysis. Collell et al. (2018) …