Forum discussions in Massive Open Online Courses (MOOCs) play a crucial role in promoting learning engagement and academic achievement. In particular, discussion topics significantly influence learners' emotional and cognitive engagement. However, the complex interrelationships among these factors remain underexplored. This study introduces an…

One challenging issue in improving the teaching and learning methods in MOOCs is to construct potential knowledge graphs from massive learning resources. Therefore, this study proposes knowledge graphs driving online learning behaviour prediction and multi-learning task recommendation in MOOCs. Based on the knowledge graphs supported by…

Quality MOOCs (massive open online courses) ensure open learning under the top-down guidance of established criteria and standards. With an evaluative approach, course providers can use the guiding frameworks in designing and refining courses while fostering students' targeted open learning competency. This study explores the openness embedded…

This study investigates the transformative potential of a professional development program launched in 2022 to meet the evolving needs of digital teaching competencies within K-12 and higher education sectors. Using the Cultural-Historical Activity Theory (CHAT) and Change Laboratory (CL) framework, the research examines how a MOOC platform…

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…

This study investigates the role of learning analytics in enhancing the learning experience within Massive Open Online Courses (MOOCs) through a two-phase design-based research approach, focusing on a Social Work MOOC. Initial engagement analysis revealed strong interactions with course content, especially with introductory elements and reflection…

MOOC learners come from different backgrounds, and they have various motivations and intentions for taking online courses. This study examines learner intentions with subsequent behaviors and the reasons for the intention-behavior gap in MOOCs. A total of four MOOCs from BilgeIs MOOC Portal was used in this study. This quantitative study with a…

Considering the ubiquity, large volume of similar courses, and the huge cost of a course, it becomes imperative to understand factors affecting MOOCs course enrolments. This paper aims to investigate how the home page elements of a MOOC influence students' enrolments. The elements in the home page include course category, course description, team…

For Massive Open Online Courses to have trustworthy credentials, assessments in these courses must be valid, reliable, and fair. Item Response Theory provides a robust approach to evaluating these properties. However, for this theory to be applicable, certain properties of the assessment items should be met, among them that item difficulties are…

The study aims to investigate the level of motivation and entrepreneurial competencies of students using online distance courses in entrepreneurial learning. Based on the Massive Open Online Courses (MOOCs) program, an experimental group of respondents took the course "How to Start Your Own Business" (March-May 2022), and their results…

MOOCs (massive open online courses), because of their scale and accessibility, have become a major area of interest in contemporary education. However, despite their growing popularity, the question of their quality remains a central concern, partly due to the lack of consensus on the criteria establishing such quality. This study set out to fill…

Predictive modelling in the education domain can be utilised to significantly improve teaching and learning experiences. Massive Open Online Courses (MOOCs) generate a large volume of data that can be exploited to predict and evaluate student performance based on various factors. This paper has two broad aims. Firstly, to develop and tune several…