Applying social learning analytics to message boards in online distance learning: A case study

Hernández-García, Ángel; González-González, Inés; Jiménez‐Zarco, Ana Isabel; Chaparro-Peláez, Julián

doi:10.1016/j.chb.2014.10.038

Cited by 105 publications

(87 citation statements)

References 26 publications

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“…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%

“…In order to show the full capabilities of Gephi for social network learning analytics, and following [22], three different datasets were generated from the original data extracted from the system log: 1) in Dataset1, each node represents an actor -student or instructor-, and each directed edge from node (user) a to node b has a weight that represents the number of times that node a replies to a post created by node b; 2) Dataset2 is similar to Dataset1, but with edges representing the number of times that node a reas a message posted by node b; both datasets include node attributes for further filtering capabilities, such as the classroom that each actor -node-was assigned to, as well as his or her final grade and role -student or teacher-, total number of reads, number of messages opening a discussion, and number of replies; and 3) Dataset3, where each node represents a forum post, and directed edges -with a weight of one-show the relation between messages -i.e., which message was written as a reply to another message; this third dataset includes additional information for each node (message) as attributes, such as number of times that a message has been read, the classroom where the message was posted, the type of message board, and the day when it was posted.…”

Section: Gephi In Actionmentioning

confidence: 99%

See 1 more Smart Citation

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: 99%

Section: Gephi In Actionmentioning

confidence: 99%

Visualizations of Online Course Interactions for Social Network Learning Analytics

Hernández-García

González-González

Jiménez‐Zarco

et al. 2016

Int. J. Emerg. Technol. Learn.

Self Cite

View full text Add to dashboard Cite

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“…The main idea behind GraphFES is that social network analysis is best done outside of the learning platform, using SNA specialized tools such as Gephi. Some advantages and applications of Gephi to the analysis of higher education courses from a social learning analytics approach can be found in [18,19].…”

Section: Learning Analytics Tools For Analysis Of Specific Issuesmentioning

confidence: 99%

Exploring Student Interactions: Learning Analytics Tools for Student Tracking

Conde

Hernández-García

García-Peñalvo

et al. 2015

Lecture Notes in Computer Science

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Abstract. This paper presents four categories of learning analytics tools: dashboards, ad hoc tools, tools for analysis of specific issues, and learning analytics frameworks, and details the characteristics of a selection of tools within each category: (1) Moodle Dashboard and Moodle default reporting tool; (2) Interactions and Teamwork Assessment Tool; (3) SNAPP, GraphFES and Moodle Engagement Analytics; and (4) VeLA and GISMO. The study investigates how these tools can be applied to the analysis of courses by using real data from a course that made intensive use of forums, wikis, web resources, videos, quizzes and assignments. The discussion that follows points out how the different tools complement each other, and suggests the implementation of basic dashboards in learning platforms and the use of external frameworks for learning analytics.

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“…In formal educational settings SNA focuses mainly in the interactions that take place in bounded spaces for collaboration, primarily course forums. The main uses of SNA of educational data include identification of relevant learning agents, such as at-risk students, knowledge brokers or influential students [9].…”

Section: Social Learning Analyticsmentioning

confidence: 99%

“…[7]-, more recent research on this field has brought novel approaches that try to go beyond statistical analysis and offer other informative and decision-oriented perspectives, such as visualization-e.g., [8]--or social learning analytics-e.g., [9].…”

Section: Introductionmentioning

confidence: 95%

A Web Services-Based Application for LMS Data Extraction and Processing for Social Network Analysis

Chaparro-Peláez

Acquila-Natale

Iglesías-Pradas

et al. 2015

New Information and Communication Technologies for Knowledge Management in Organizations

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Abstract. The emergence of learning analytics as a discipline of its own has given way to a diverse subset of research fields offering very different approximations to the topic. One of the most recent and active approaches is social learning analytics, which focuses primarily on the application of social network analysis (SNA) techniques and visualizations to study and help understanding interactions in online courses as a key pillar of social construction of learning. However, and despite this interest, current tools for analysis and visualization are very limited for advanced social learning analytics, and SNA applications cannot directly process data from learning management systems. This paper presents a technical view of the design and implementation of a web servicesbased application that aims to overcome these limitations by extracting and processing educational data about forum interactions in online courses to generate the corresponding social graphs and enable advanced social network analysis on SNA software.

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Applying social learning analytics to message boards in online distance learning: A case study

Cited by 105 publications

References 26 publications

Visualizations of Online Course Interactions for Social Network Learning Analytics

Visualizations of Online Course Interactions for Social Network Learning Analytics

Exploring Student Interactions: Learning Analytics Tools for Student Tracking

A Web Services-Based Application for LMS Data Extraction and Processing for Social Network Analysis

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