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Massive Open Online Courses (MOOCs) are attracting the attention of people all over the world. Regardless the platform, numbers of registrants for online courses are impressive but in the same time, completion rates are disappointing.…

Information Retrieval · Computer Science 2017-10-11 Tom Rolandus Hagedoorn , Gerasimos Spanakis

With the development of MOOCs massive open online courses, increasingly more subjects can be studied online. Researchers currently show growing interest in the field of MOOCs, including dropout prediction, cheating detection and achievement…

Information Retrieval · Computer Science 2019-08-06 Shaojie Qu , Kan Li , Zheyi Fan , Sisi Wu , Xinyi Liu , Zhiguo Huang

The high level of attrition and low rate of certification in Massive Open Online Courses (MOOCs) has prompted a great deal of research. Prior researchers have focused on predicting dropout based upon behavioral features such as student…

Computers and Society · Computer Science 2018-09-05 Niki Gitinabard , Farzaneh Khoshnevisan , Collin F. Lynch , Elle Yuan Wang

With an expansive and ubiquitously available gold mine of educational data, Massive Open Online courses (MOOCs) have become the an important foci of learning analytics research. The hope is that this new surge of development will bring the…

Human-Computer Interaction · Computer Science 2014-07-29 Tanmay Sinha

Predictive models of student success in Massive Open Online Courses (MOOCs) are a critical component of effective content personalization and adaptive interventions. In this article we review the state of the art in predictive models of…

Computers and Society · Computer Science 2018-04-23 Josh Gardner , Christopher Brooks

Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left…

Computers and Society · Computer Science 2022-05-03 Vinitra Swamy , Mirko Marras , Tanja Käser

Real-time and open online course resources of MOOCs have attracted a large number of learners in recent years. However, many new questions were emerging about the high dropout rate of learners. For MOOCs platform, predicting the learning…

Computers and Society · Computer Science 2018-08-07 Zhemin Liu , Feng Xiong , Kaifa Zou , Hongzhi Wang

The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent…

Computers and Society · Computer Science 2016-05-10 Zhiyun Ren , Huzefa Rangwala , Aditya Johri

We study student behavior and performance in two Massive Open Online Courses (MOOCs). In doing so, we present two frameworks by which video-watching clickstreams can be represented: one based on the sequence of events created, and another…

Social and Information Networks · Computer Science 2015-10-06 Christopher G. Brinton , Swapna Buccapatnam , Mung Chiang , H. V. Poor

The birth of massive open online courses (MOOCs) has had an undeniable effect on how teaching is being delivered. It seems that traditional in class teaching is becoming less popular with the young generation, the generation that wants to…

Computers and Society · Computer Science 2020-12-03 Sepinoud Azimi , Carmen-Gabriela Popa , Tatjana Cucić

Millions of people have enrolled and enrol (especially in the Covid-19 pandemic world) in MOOCs. However, the retention rate of learners is notoriously low. The majority of the research work on this issue focuses on predicting the dropout…

Human-Computer Interaction · Computer Science 2020-08-13 Ahmed Alamri , Zhongtian Sun , Alexandra I. Cristea , Gautham Senthilnathan , Lei Shi , Craig Stewart

Understanding why students stopout will help in understanding how students learn in MOOCs. In this report, part of a 3 unit compendium, we describe how we build accurate predictive models of MOOC student stopout. We document a scalable,…

Computers and Society · Computer Science 2014-08-15 Colin Taylor , Kalyan Veeramachaneni , Una-May O'Reilly

This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data. While a variety of feature extraction techniques have been explored extensively for such purposes, to our…

Machine Learning · Computer Science 2020-02-07 Byungsoo Jeon , Namyong Park

While Massive Open Online Course (MOOCs) platforms provide knowledge in a new and unique way, the very high number of dropouts is a significant drawback. Several features are considered to contribute towards learner attrition or lack of…

Human-Computer Interaction · Computer Science 2020-08-14 Ahmed Alamri , Mohammad Alshehri , Alexandra I. Cristea , Filipe D. Pereira , Elaine Oliveira , Lei Shi , Craig Stewart

In order to obtain reliable accuracy estimates for automatic MOOC dropout predictors, it is important to train and test them in a manner consistent with how they will be used in practice. Yet most prior research on MOOC dropout prediction…

Artificial Intelligence · Computer Science 2017-02-22 Jacob Whitehill , Kiran Mohan , Daniel Seaton , Yigal Rosen , Dustin Tingley

Massive Open Online Courses (MOOCs) are emerging as a popular alternative to traditional education, offering learners the flexibility to access a wide range of courses from various disciplines, anytime and anywhere. Despite this…

Computers and Society · Computer Science 2025-03-04 Alireza Gharahighehi , Achilleas Ghinis , Michela Venturini , Frederik Cornillie , Celine Vens

In this work, we explore video lecture interaction in Massive Open Online Courses (MOOCs), which is central to student learning experience on these educational platforms. As a research contribution, we operationalize video lecture…

Human-Computer Interaction · Computer Science 2014-09-18 Tanmay Sinha , Patrick Jermann , Nan Li , Pierre Dillenbourg

The increasing availability of learning activity data in Massive Open Online Courses (MOOCs) enables us to conduct a large-scale analysis of learners' learning behavior. In this paper, we analyze a dataset of 351 million learning activities…

Information Retrieval · Computer Science 2024-08-07 Xin Zhou , Aixin Sun , Jie Zhang , Donghui Lin

Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs, this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may…

Computers and Society · Computer Science 2019-04-17 Adithya Sheshadri , Niki Gitinabard , Collin F. Lynch , Tiffany Barnes , Sarah Heckman

Digital learning environments generate a precise record of the actions learners take as they interact with learning materials and complete exercises towards comprehension. With this high quantity of sequential data comes the potential to…

Computers and Society · Computer Science 2016-08-18 Steven Tang , Joshua C. Peterson , Zachary A. Pardos
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