相关论文: Social Interactions Clustering MOOC Students: An E…

The substantial growth of online learning, in particular, Massively Open Online Courses (MOOCs), supports research into the development of better models for effective learning. Learner 'confusion' is among one of the identified aspects…

Digital learning environments generate a precise record of the actions learners take as they interact with learning materials and complete exercises towards comprehension. With this high quantity of sequential data comes the potential to…

With an expansive and ubiquitously available gold mine of educational data, Massive Open Online courses (MOOCs) have become the an important foci of learning analytics research. In this paper, we investigate potential reasons as to why are…

We have analyzed the fully-anonymized headers of 362 million messages exchanged by 4.2 million users of Facebook, an online social network of college students, during a 26 month interval. The data reveal a number of strong daily and weekly…

An earlier study of a collaborative chat intervention in a Massive Open Online Course (MOOC) identified negative effects on attrition stemming from a requirement for students to be matched with exactly one partner prior to beginning the…

Curiosity is the strong desire to learn or know more about something or someone. Since learning is often a social endeavor, social dynamics in collaborative learning may inevitably influence curiosity. There is a scarcity of research,…

Massive Open Online Courses (MOOCs) bring together thousands of people from different geographies and demographic backgrounds -- but to date, little is known about how they learn or communicate. We introduce a new content-analysed MOOC…

Social media platforms can quickly disseminate STEM content to diverse audiences, but their operation can be mysterious. We used open-source machine learning methods such as clustering, regression, and sentiment analysis to analyze over…

This paper presents for the first time a detailed analysis of fine-grained navigation style identification in MOOCs backed by a large number of active learners. The result shows 1) whilst the sequential style is clearly in evidence, the…

Interactions between users in cyberspace may lead to phenomena different from those observed in common social networks. Here we analyse large data sets about users and Blogs which they write and comment, mapped onto a bipartite graph. In…

The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different…

The widespread adoption of online courses opens opportunities for the analysis of learner behaviour and for the optimisation of web-based material adapted to observed usage. Here we introduce a mathematical framework for the analysis of…

As online communities become increasingly popular, researchers have tried to examine participating activities in online communities as well as how to sustain online communities. However, relatively few studies have tried to understand what…

In this work, we explain the underlying interaction mechanisms which govern students' influence on each other in Massive Open Online Courses (MOOCs). Specifically, we outline different ways in which students can be negatively exposed to…

Over the past decade humans have experienced exponential growth in the use of online resources, in particular social media and microblogging websites such as Facebook, Twitter, YouTube and also mobile applications such as WhatsApp, Line,…

Studies on massive open online courses (MOOCs) users discuss the existence of typical profiles and their impact on the learning process of the students. However defining the typical behaviors as well as classifying the users accordingly is…

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which…

To find interesting structure in networks, community detection algorithms have to take into account not only the network topology, but also dynamics of interactions between nodes. We investigate this claim using the paradigm of…

We present a demonstration of REACT, a new Real-time Educational AI-powered Classroom Tool that employs EDM techniques for supporting the decision-making process of educators. REACT is a data-driven tool with a user-friendly graphical…

In this work, we explore video lecture interaction in Massive Open Online Courses (MOOCs), which is central to student learning experience on these educational platforms. As a research contribution, we operationalize video lecture…