Data Mining and Social Network Analysis in the Educational Field: An Application for Non-Expert Users

García‐Saiz, Diego; Palazuelos, Camilo; Zorrilla, Marta E.

doi:10.1007/978-3-319-02738-8_15

Cited by 18 publications

(11 citation statements)

References 30 publications

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“…Ref. [24] associates betweenness to learning performance, although its relation is weaker than that of degree and closeness centrality, and [17] find that tutors and instructors show higher betweenness values, a result also found in [20].…”

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 81%

“…An increasing number of scholars -e.g. [2,[17][18][19][20][21][22]-have already validated the usefulness of social network learning analytics for instructors based on the use of social network metrics.…”

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 99%

“…Degree centrality has been found to be a predictor of sense of community [2] and to be related to academic performance [20].…”

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 99%

“…Edges can also have different weights depending, for example, on the strength or the number of interactions between two nodes. SNA offers individual centrality measures which are useful for social network learning analytics, such as degree centrality, betweenness centrality [23], hubs and authorities [20], among others.…”

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 99%

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Visualizations of Online Course Interactions for Social Network Learning Analytics

Hernández-García

González-González

Jiménez‐Zarco

et al. 2016

Int. J. Emerg. Technol. Learn.

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Abstract-Social network learning analytics aims to extract useful information to improve the learning process, but the variety of learning management systems makes this task burdensome and difficult to manage. This study shows how Gephi, a general-purpose, open-source social network analysis application, can be used by instructors and institutions to extract and visualize relevant information that is commonly hidden or difficult to observe for course coordinators and teachers. The empirical case study uses data from one cross-curricular course with 656 students at the Open University of Catalonia (UOC) and showcases the use of Gephi as a social network learning analytics tool. The study further discusses the potential of social network learning analytics to improve online instruction by visualization of educational data.

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Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 81%

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 99%

“…Degree centrality has been found to be a predictor of sense of community [2] and to be related to academic performance [20].…”

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 99%

Section: Online Class Interactions and Social Network Learning Anmentioning

confidence: 99%

See 2 more Smart Citations

Visualizations of Online Course Interactions for Social Network Learning Analytics

Hernández-García

González-González

Jiménez‐Zarco

et al. 2016

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

show abstract

“…It can be well connected (dense) or sparsely connected (less dense). The latter relates to the largest number of nodes that must be crossed in order to move from one node to another (Bayat, 2013;Garcia-Saiz, Palazuelos, & Zorrilla, 2013;Hernández-García et al, 2016;Liu, Chen, & Tai, 2017;Rosen, Miagkikh, & Suthers, 2011). It represents the distance that has to be traversed between the two farthest nodes as opposed to the geodesicthe shortest path between two nodes (Bayat, 2013).…”

Section: Discussionmentioning

confidence: 99%

Online module login data as a proxy measure of student engagement: the case of myUnisa, MoyaMA, Flipgrid, and Gephi at an ODeL institution in South Africa

Chaka

Nkhobo

2019

Int J Educ Technol High Educ

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The current study employed online module login data harvested from three tools, myUnisa, Moya MA and Flipgrid to determine how such data served as a proxy measure of student engagement. The first tool is a legacy learning management system (LMS) utilised for online learning at the University of South Africa (UNISA), while the other two tools are a mobile messaging application and an educational video discussion platform, respectively. In this regard, the study set out to investigate the manner in which module login data of undergraduate students (n = 3475 & n = 2954) and a cohort of Mathew Goniwe students (n = 27) enrolled for a second-level module, ENG2601, as extracted from myUnisa, Moya MA , and Flipgrid served as a proxy measure of student engagement. Collectively, these students were registered for this second-level module at UNISA at the time the study was conducted. The online login data comprised myUnisa module login file access frequencies. In addition, the online login data consisted of the frequencies of instant messages (IMs) posted on Moya MA by both the facilitator and Mathew Goniwe students, and video clips posted on and video clip view frequencies captured by Flipgrid in respect of the afore-cited module. One finding of this study is that student engagement as measured by login file access frequencies was disproportionally skewed toward one module file relative to other module files. The other finding of this study is that the overall module file access metrics of the Mathew Goniwe group were disproportionally concentrated in a sub-cohort of highly active users (HAU).

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Groups and Networks: Teachers’ Educational Networking at B@UNAM

Cervantes-Pérez

Vadillo

Bucio

2019

Lecture Notes in Social Networks

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Data Mining and Social Network Analysis in the Educational Field: An Application for Non-Expert Users

Cited by 18 publications

References 30 publications

Visualizations of Online Course Interactions for Social Network Learning Analytics

Visualizations of Online Course Interactions for Social Network Learning Analytics

Online module login data as a proxy measure of student engagement: the case of myUnisa, MoyaMA, Flipgrid, and Gephi at an ODeL institution in South Africa

Groups and Networks: Teachers’ Educational Networking at B@UNAM

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