2022
DOI: 10.3390/su14106199
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Predicting Student Outcomes in Online Courses Using Machine Learning Techniques: A Review

Abstract: Recent years have witnessed an increased interest in online education, both massive open online courses (MOOCs) and small private online courses (SPOCs). This significant interest in online education has raised many challenges related to student engagement, performance, and retention assessments. With the increased demands and challenges in online education, several researchers have investigated ways to predict student outcomes, such as performance and dropout in online courses. This paper presents a comprehen… Show more

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Cited by 38 publications
(21 citation statements)
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“…It seems likely that network analysis modelling has not investigated enough for solving educational data related problems. Indeed, network view and especially link prediction methods may be used for several research problems in educational data mining such as learner consultation and performance prediction which has been comprehensively checked out by machine learning methods (Alhothali et al, 2022 ).…”
Section: Discussionmentioning
confidence: 99%
“…It seems likely that network analysis modelling has not investigated enough for solving educational data related problems. Indeed, network view and especially link prediction methods may be used for several research problems in educational data mining such as learner consultation and performance prediction which has been comprehensively checked out by machine learning methods (Alhothali et al, 2022 ).…”
Section: Discussionmentioning
confidence: 99%
“…According to Alhothali et al (2022), MOOC and SPOC are the primary forms of online courses used in online education. Present research of online courses focus primarily on the delivery style of the courses, students' motivation, and how to design and evaluate the quality of online courses and students' performance and dropout in online courses ( Ruiz-Palmero et al, 2022;Martin et al, 2019;Bao, 2021).…”
Section: Literature Reviewmentioning
confidence: 99%
“…The present research of online courses focus primarily on the delivery style of the courses, their motivation, and how to design and evaluate the quality of online courses and students' performance and dropout in online courses (Ruiz-Palmero et al, 2020;Alhothali et al, 2022;Martin et al, 2019;Bao, 2021). Previous study has looked into the elements that influence adoption of online learning and online courses Ifinedo, 2016;Yang et al, 2019;Yin et al, 2015).…”
Section: Introductionmentioning
confidence: 99%
“…Many previous studies focused on developing prediction models and evaluating results using the ML technique, with little attention focused on comprehending classi cation models for understanding predictive features [6][7][8][9][10][11][12][13][14][15][16][17][18]. Understanding the black-box output of a machine-learning model was crucial for computing and examining the in uence of features on individual and overall predictions, as well as evaluating useful features and investigating their interpretability and characteristics.…”
Section: Barnabásmentioning
confidence: 99%
“…It is the eld of revealing new and meaningful results from data. ML in education has evolved into a powerful tool for uncovering hidden patterns in educational data and forecasting students' academic performance [6,7]. Previous researchers [8] developed machine learning approaches to predict the nal test grades of undergraduate students.…”
Section: Introductionmentioning
confidence: 99%