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…

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…

Recently, artificial intelligence (AI) technologies have been widely used in the field of education, and artificial intelligence in education (AIEd) has gained increasing attention. However, no quantitative meta-analysis has been conducted on the overall effectiveness of AI on learning achievement and learning perception. To close this research…

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…

Monitoring one's learning activities is a key component of self-regulated learning (SRL) leading to successful learning and performance outcomes across settings. Achievement emotions also play an important part in SRL and consequently student learning outcomes. However, there is little research on how specific types of monitoring (i.e.…

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…

One-to-one online learning has become pervasive in distance education. However, factors affecting learners' continuance intention toward one-to-one online learning are not well known. This study proposed a model to explain learners' continuance intention toward one-to-one online learning. The model extends previous technology acceptance models and…

The aim of this study was to explore the relationships among participation, peer support, self-regulated learning (SRL), course discipline and academic performance in small private open course (SPOC) environments. The study sample comprised of 309 undergraduates who completed SPOCs within the past year and consisted of 53% males (N = 164) and 47%…

The urgent imperative to "move online," caused by the recent COVID-19 pandemic, has led to an in-depth study of the psychological factors involved in designing successful online learning experiences. The social-cognitive model of academic satisfaction has been widely researched in conventional educational contexts in different countries.…

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.…

This study investigated factors that influenced university students' intentions to use smart applications in flipped learning (FL) in Thailand flipped classrooms (FC) by extending the technology acceptance model (TAM) as the research model. Eight variables including relative advantage (ADV), peer influence (PI), school support (SS), reputation…