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 article reports on an empirical study on cognitive processes [i.e. (dis) fluency, temporal management of the translation process, and revision] and their relationship with fluency and adequacy. Based on Jakobsen and Schou's (1999) computational model of human translation, the author utilizes keylogging data retrieved from a Translog-II-based…

This study reviewed thirty-seven articles on intercultural learning supported by technology. The results are reported in terms of strength of evidence and relationship among research variables. The results indicated the following strength of evidence: (1) moderate evidence showed higher frequency of the technology usage in higher education or…

In this study, a predictive model is constructed to analyze learners' performance in programming tasks using data of programming behavioral events and behavioral sequences. First, this study identifies behavioral events from log data and applies lag sequence analysis to extract behavioral sequences that reflect learners' programming strategies.…

Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…

Attentional control theory indicates that concentration is considered an important variable that contributes to learning. There are some devices for players to practice their concentration, but there are few virtual reality (VR) designs which can increase the level of difficulty for students to discipline their mental concentration with…

ChatGPT is an AI tool that assisted in writing, learning, solving assessments and could do so in a conversational way. The purpose of the study was to develop a model that examined the predictors of adoption and use of ChatGPT among higher education students. The proposed model was based on a previous theory of technology adoption. Seven…

Given the paucity of research on mobile-assisted language learning (MALL) in secondary schools in China, this retrospective case study explored the psychological processes underlying the non-voluntary MALL experiences of Chinese secondary school students during a lockdown to contain the spread of COVID-19. Drawing on prior technology acceptance…

The outbreak of COVID-19 pandemic in March 2020 influenced all aspects of school life. Teaching and learning moved only online, with different software solutions emerging for teachers to make the most of them. These educational platforms provided more than just a traditional teaching which is focused on the transmission and access to information.…

While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs…

Despite the disruptive effects of COVID-19 on higher education institutions, the pandemic has enforced the intensive and sustained integration of new digital technologies and platforms into Education, a case that has instigated new contexts for online learning research. A considerable proportion of empirical literature advocates that perceived…