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Outputs (4)

Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course (2020)
Conference Proceeding
Yu, J., Aduragba, O. T., Sun, Z., Black, S., Stewart, C., Shi, L., & Cristea, A. (2020). Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course. In International Conference on Computer Science & Education (ICCSE) (182-187). https://doi.org/10.1109/iccse49874.2020.9201631

Social media is ubiquitous, a continuous part of our daily lives; it offers new ways of communication. This is especially crucial in education, where various online systems make use of (perceived) public or private communication, as a means to suppor... Read More about Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course.

Social Interactions Clustering MOOC Students: An Exploratory Study (2020)
Conference Proceeding
Shi, L., Cristea, A. I., Toda, A. M., Oliveira, W., Ahmad, A., Chang, M., …Pedaste, M. (2020). Social Interactions Clustering MOOC Students: An Exploratory Study. In IEEE 20th International Conference on Advanced Learning Technologies ICALT 2020 ; proceedings (172-174)

An exploratory study on social interactions of MOOC students in FutureLearn was conducted, to answer "how can we cluster students based on their social interactions?" Comments were categorized based on how students interacted with them, e.g., how a s... Read More about Social Interactions Clustering MOOC Students: An Exploratory Study.

Temporal Analysis in Massive Open Online Courses – Towards Identifying at-Risk Students Through Analyzing Demographical Changes (2020)
Book Chapter
Shi, L., Yang, B., & Toda, A. (2020). Temporal Analysis in Massive Open Online Courses – Towards Identifying at-Risk Students Through Analyzing Demographical Changes. In A. Siarheyeva, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Advances in information systems development (146-163). Springer Verlag. https://doi.org/10.1007/978-3-030-49644-9_9

This chapter demonstrates a temporal analysis in Massive Open Online Courses (MOOCs), towards identifying at-risk students through analyzing their demographical changes. At-risk students are those who tend to drop out from the MOOCs. Previous studies... Read More about Temporal Analysis in Massive Open Online Courses – Towards Identifying at-Risk Students Through Analyzing Demographical Changes.

Exploring Navigation Styles in a FutureLearn MOOC (2020)
Book Chapter
Shi, L., Cristea, A. I., Toda, A. M., & Oliveira, W. (2020). Exploring Navigation Styles in a FutureLearn MOOC. In V. Kumar, & C. Troussas (Eds.), Intelligent Tutoring Systems (45-55). Springer Verlag. https://doi.org/10.1007/978-3-030-49663-0_7

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 global style... Read More about Exploring Navigation Styles in a FutureLearn MOOC.