Background: Massive Open Online Courses (MOOCs) can engage large numbers of learners. Understanding motivations for enrolling and elements that engage learners may help meet learner needs. This study explored motivations, intentions, recruitment methods and course acceptability of learners enrolled in 'The Science of Weight Loss: Dispelling diet…

Existing studies on Massive Open Online Courses (MOOCs) examine learners' engagement processes but have not explored links between them and motivations to enroll. In our previous work, we identified intrinsic, professional, and prosocial motivations for taking MOOCs. In this study, we used process mining to compare the course engagement patterns…

The rise of massive open online courses (MOOCs) brings rich opportunities for understanding learners' experiences based on analyzing learner-generated content such as course reviews. Traditionally, the unstructured textual data is analyzed qualitatively via manual coding, thus failing to offer a timely understanding of the learner's experiences.…

Students benefit from a nonlinear learning path, also known as a nonsequential learning path, because it allows them to control the pace and sequence of their learning. However, the dynamics of a nonlinear learning path, particularly within an open learning environment like MOOCs, remain underexplored. The current study aims to map out various…

Background: Forums in massive open online courses (MOOCs) enable written exchanges on course content; hence, they can potentially facilitate learners' cognitive engagement. Given the myriad of MOOC forum messages, this engagement is commonly analysed automatically through the linguistic features of the messages. Assessing linguistic features of…

The aim of the present paper is to explore students' perceptions of MOOCs in relation to their learning strategies. Drawing upon cognitive appraisal theory and learning strategies framework, the study examines the perception of MOOCs as threats or challenges and assesses students' learning approaches through the prism of deep and surface learning…

Self-regulated learning is a crucial skill that may enable massive numbers of learners to thrive in MOOCs, but MOOC learners differ in their self-regulated learning skills, as low self-regulated learners need support to regulate their learning process in MOOCs. Designing self-regulated learning scaffoldings builds upon an accurate appraisal of…

To design and script courses, practitioners often collaboratively use simple and tangible tools such as Post-it notes. In light of this, research and development were conducted to develop Eduscript Doctor, an analogic tool that would retain the inductive potential of Post-it notes while structuring the pedagogical scripting process. This…

The number of Massive Open Online Courses' (MOOCs) participants has been increasing over the years but its completion rate is extremely low. Social support/social interaction is one of the key factors that has a huge impact on students' learning motivation in both online and offline environments, but difficult to maintain in MOOCs due to its…

MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion…

Massive Open Online Courses (MOOCs) are revolutionizing online education and have become a popular teaching platform. However, traditional MOOCs often overlook learners' individual needs and preferences when designing learning materials and activities, resulting in suboptimal learning experiences. To address this issue, this paper proposes an…

To date, student issues with Massive Open Online Courses (MOOCs) have only been explored in context-specific environments. Mainstream problems such as declining student motivation during a course, massive student dropout rates, accountability, user experience, etc., persist due to the permutations and combinations of these issues. Literature is…

Identifying online users' contexts can help researchers understand their needs. However, the validity of different methods for identifying the location of online users has been underexplored. This paper proposes using multiple methods and examining their impact on different research questions to determine their validity. It then demonstrates this…

Contribution: This study proposes a student dropout prediction model, named image convolutional and bi-directional temporal convolutional network (IC-BTCN), which makes dropout prediction for learners based on the learning clickstream data of students in massive open online courses (MOOCs) courses. Background: The MOOCs learning platform attracts…

Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…