A Comparative Analysis of Dropout Prediction in Massive Open Online Courses
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RESEARCH ARTICLE-SYSTEMS ENGINEERING
A Comparative Analysis of Dropout Prediction in Massive Open Online Courses 1 Mehmet Sahin ¸
Received: 27 April 2020 / Accepted: 11 November 2020 © King Fahd University of Petroleum & Minerals 2020
Abstract Massive open online courses (MOOCs) provide a valuable learning platform for global learners. They are extensively utilized by an increasing number of people from all over the world due to their remarkable features, including unlimited enrollment, the lack of location requirements, free access to a high number of courses, and structural similarity to traditional lectures. However, high dropout rates negatively affect their educational effectiveness. In this regard, as a trending research topic in recent years, the prediction of dropout rates in MOOCs has become a critical issue in terms of planning for the future and taking precautions. This study proposes a practical prediction approach for the student dropout problem of MOOCs. In this regard, an adaptive neuro-fuzzy inference system (ANFIS) is utilized for the prediction of dropout rates in MOOCs for the first time in this study. The proposed approach uses the capabilities of both neural networks and fuzzy inference systems; thus, it provides highly accurate predictions. The performance of the proposed ANFIS approach is benchmarked against various models developed based on several machine learning methods, including the decision tree, logistic regression, support vector machine, ensemble learning, and K-nearest neighbor methods. The results reveal that the proposed approach provides higher statistical accuracy than its benchmarks, meaning that the proposed approach can be used effectively for MOOCs. Keywords Distance learning · Data science applications in education · Massive open online courses · ANFIS · Machine learning
1 Introduction As an advanced version of distance education or longdistance learning, massive open online courses (MOOCs) rose to prominence based on the promise of providing quality education for learners from all backgrounds. The MOOC concept consists of the following characteristics: they are massive, with no limit on enrollment; they are open, with no restrictions on who may attend, no matter where they are from; they are online, with learning activities that are accessible over the web; and they contain courses, which are learning activities in a defined study area [1]. MOOCs have made an influential contribution to the learning environment. In their 8 years of existence, the number of learners enrolled in MOOCs, excluding those in China, reached 110 million in 2019. The top two MOOC providers are Coursera and
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Mehmet Sahin ¸ [email protected] Department of Industrial Engineering, Iskenderun Technical University, 31200 Iskenderun, Turkey
edX, with 45 and 25 million students, respectively [2]. Generally, MOOCs require no fee for taking courses offered by well-known schools or require a nominal fee if they award a certificate [3]. Despite their convenience, flexibility, affordab
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