To address three issues identified in previous research this study proposes a clustering-based MOOC dropout identification method and an early prediction model based on deep learning. The MOOC learning behavior of self-paced students was analyzed, and two well-known MOOC datasets were used for analysis and validation. The findings are as follows:…

This study takes the value-based adoption model and CIE model of the learning process as the theoretical basis and combines them to explore the influencing factors and mechanisms of learners' online interaction and perceived value. Based on the questionnaire survey data of 81 learners' potential factors and their 45,166 real-time behavior data on…

On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…

The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…

Almost in every aspect of life, classification and categorization make it easier for humans to analyze complex structures and systems. In games, the classification of the players based on their demographics, behaviors, expectations and preferences of the game is important to increase players' motivation and satisfaction. Likewise, knowing the…

By assessing student engagement with learning tasks along with students' understanding of subject matter before and during teaching, teachers are able to shift their teaching approaches through improvisational pedagogical reasoning in real time. However, if a teacher does not know how to respond to students' cues, their capacity to effectively…

Previous studies had identified the potential link between achievement goal and students' technology use. However, the literature on this topic is extremely scarce. The purpose of this study was to investigate the antecedents to technology use among undergraduates via an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model…

The purpose of this study is to explore students' backtracking patterns in using a digital textbook, reveal the relationship between backtracking behaviors and academic performance as well as learning styles. This study was carried out for 2 semesters on 102 university students and they are required to use a digital textbook system called DITeL to…

The use of Instagram is becoming increasingly popular among students. Excessive Instagram use (EIU) has become a growing problem that can impact students' lives psychosocially. This study applied uses and gratifications theory (UGT) to explore the impact of social gratification, content gratification, and entertainment along with social presence,…

Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…

Technological mediums such as dynamic environments with drag-and-drop features have been considered promising agents in helping students explore and generate conjectures about mathematical concepts. This study investigated the dragging modalities sixth and seventh-grade students use in solving proportional problems in a dynamic geometry…

In the era of COVID-19 and right after the announcement of it as a pandemic and threat to humanity by the World Health Organization, most educational activities were globally forced to shut down their traditional teaching/learning activities. This is one of the biggest and most vital changes of educational settings which have led to migration to…

One of the phenomena that lecturers who switched to online distance learning during COVID-19 reported is the refusal of students to turn on their cameras during online classes. This study aimed to examine the factors that predict the opening of cameras in class. The study examined this issue regarding three types of predictors: resistance factors,…

The published literature on lecture capture technologies is often conflicting and sometimes controversial. A common thread among many studies is the impact of recorded lectures on student satisfaction, attendance and performance; however, many of these studies fail to acknowledge the wider context and the many and varied ways in which capture…

With the rising influence of technology, students have become heavy users of instant messaging applications. It makes one wonder about students' motivations in using these applications and their usage habits. The aims of this study were to analyze the messaging activities of university students in blended classroom groups, to investigate the…