Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…

Online education is growing because of its benefits and advantages that students enjoy. Educational technologies (e.g., learning analytics, student modelling, and intelligent tutoring systems) bring great potential to online education. Many online courses, particularly in self-paced online learning (SPOL), face some inherent barriers such as…

In this article, we leverage data from over 1,000 students participating in two different online courses to investigate whether better learning outcomes are associated with student decisions to practice instead of (re-)reading. Consistent with laboratory and classroom findings, we find that students' decisions to practice are related to better…

Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…

The importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of…

Massive open online courses (MOOCs) provide numerous open-access learning resources and allow for self-directed learning. The application of big data and artificial intelligence (AI) in MOOCs help comprehend raw educational data and enrich the learning process for students and instructors. Thus, we created two deep neural network models. The first…

With the rapid expansion of mobile, blended, and seamless learning, researchers claim two factors, lack of self-discipline and poor time management, adversely impact learning performance. In online educational environments, reduced social interactions and low engagement levels generate high dropout rates. Self-regulated learning (SRL), the…

This study proposed and implemented a blended self-directed learning program for English-as-a-Foreign-Language (EFL) college students beyond the classroom. Adopting a case study-mixed methods design, the study aimed to investigate (1) learners' engagement in the program, (2) the effects of the program, and (3) learners' perceptions of the…

Online learning has been growing steadily as an essential instructional mode in most higher education settings. In response to its popularity, many studies have been conducted to provide a better understanding of how learning occurs in this environment. Various frameworks and theories have been adopted to examine learning in this environment.…

The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…

Recommender systems in educational contexts have proven to be effective in identifying learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In this article, we present the design of a hybrid…

This study investigated how English learners complete multimodal formative quizzes. Participants included 17,950 students enrolled in a mandatory English for Academic Purposes course at a university in Hong Kong. We retrieved data from Blackboard, a learning management system, and conducted a two-step cluster analysis to examine student…

Purpose: This study explores ongoing research into self-mapped learning pathways that students utilize to move through a course when given two modalities to choose from: one that is instructor-led and one that is student-directed. Design/methodology/approach: Process mining analysis was utilized to examine and cluster clickstream data from an…

With the outbreak of COVID-19 in 2020, many universities shifted to online teaching. However, some online instruction had already been implemented well before the pandemic. This study investigates (1) how engagement in blended CALL activities differed during the pandemic, and (2) in what ways the assessment outcomes were associated with student…

The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…