What tweets tell us about MOOC participation

In this research paper, the authors analyze the collected Twitter data output during MobiMOOC 2011. This six-week data stream includes all tweets that contain the MOOC's hashtag (#mobiMOOC) and it has been analyzed using qualitative methodology. The analysis sought to examine the emotive vocabulary used, to determine if there was content-sharing via tweets, and to analyze the folksonomic trends of the tweets. In Addition sought a deeper understanding of what, and how, MOOC participants share what they share on the MOOC's Twitter channel. The aim of this study is to provide a little more insight into MOOC learner behaviors on Twitter so that future MOOC designers and facilitators can better engage with their learners.Facultad de Ciencias Exacta

What tweets tell us about MOOC participation

In this research paper, the authors analyze the collected Twitter data output during MobiMOOC 2011. This six-week data stream includes all tweets that contain the MOOC's hashtag (#mobiMOOC) and it has been analyzed using qualitative methodology. The analysis sought to examine the emotive vocabulary used, to determine if there was content-sharing via tweets, and to analyze the folksonomic trends of the tweets. In Addition sought a deeper understanding of what, and how, MOOC participants share what they share on the MOOC's Twitter channel. The aim of this study is to provide a little more insight into MOOC learner behaviors on Twitter so that future MOOC designers and facilitators can better engage with their learners.Facultad de Ciencias Exacta

What tweets tell us about MOOC participation

In this research paper, the authors analyze the collected Twitter data output during MobiMOOC 2011. This six-week data stream includes all tweets that contain the MOOC's hashtag (#mobiMOOC) and it has been analyzed using qualitative methodology. The analysis sought to examine the emotive vocabulary used, to determine if there was content-sharing via tweets, and to analyze the folksonomic trends of the tweets. In Addition sought a deeper understanding of what, and how, MOOC participants share what they share on the MOOC's Twitter channel. The aim of this study is to provide a little more insight into MOOC learner behaviors on Twitter so that future MOOC designers and facilitators can better engage with their learners.Facultad de Ciencias Exacta

The Utilization of Data Analysis Techniques in Predicting Student Performance in Massive Open Online Courses (MOOCs)

The growth of the Internet has enabled the popularity of open online learning platforms to increase over the years. This has led to the inception of Massive Open Online Courses (MOOCs) that enrol, millions of people, from all over the world. Such courses operate under the concept of open learning, where content does not have to be delivered via standard mechanisms that institutions employ, such as physically attending lectures. Instead learning occurs online via recorded lecture material and online tasks. This shift has allowed more people to gain access to education, regardless of their learning background. However, despite these advancements in delivering education, completion rates for MOOCs are low. In order to investigate this issue, the paper explores the impact that technology has on open learning and identifies how data about student performance can be captured to predict trend so that at risk students can be identified before they drop-out. In achieving this, subjects surrounding student engagement and performance in MOOCs and data analysis techniques are explored to investigate how technology can be used to address this issue. The paper is then concluded with our approach of predicting behaviour and a case study of the eRegister system, which has been developed to capture and analyse data. Keywords: Open Learning; Prediction; Data Mining; Educational Systems; Massive Open Online Course; Data Analysi