Social Network Analysis: A Primer, a Guide and a Tutorial in R

Saqr, Mohammed; López-Pernas, Sonsoles; Conde-González, Miguel Ángel; Hernández-García, Ángel

doi:10.1007/978-3-031-54464-4_15

Learning Analytics Methods and Tutorials 2024

DOI: 10.1007/978-3-031-54464-4_15

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Social Network Analysis: A Primer, a Guide and a Tutorial in R

Mohammed Saqr,

Sonsoles López-Pernas,

Miguel Ángel Conde-González

et al.

Abstract: This chapter introduces the concept and methods of social network analysis (SNA) with a detailed guide to analysis with real world data using the R programming language. The chapter first introduces the basic concepts and types of networks. Then the chapter goes through a detailed step by step analysis of networks, computation of graph level measures as well as centralities with a concise interpretation in a collaborative environment. The chapter concludes with a discussion of network analysis, next steps as w… Show more

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Cited by 1 publication

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Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods

López-Pernas,

Misiejuk,

Kaliisa

et al. 2024

Learning Analytics Methods and Tutorials

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The unique position of learning analytics at the intersection of education and computer science while reaching out to several other disciplines such as statistics, psychometrics, econometrics, mathematics, and linguistics has accelerated the growth and expansion of the field. Therefore, it is a crucial endeavor for learning analytics researchers to stay abreast of the latest methodological and computational advances to drive their research forward. The diversity and complexity of the existing methods can make this task overwhelming both for newcomers to the learning analytics field and for experienced researchers. With the motivation to accompany researchers in this challenging journey, the book “Learning Analytics Methods and Tutorials—A Practical Guide Using R” aims to provide a methodological guide for researchers to study, consult, and take the first steps toward innovation in the learning analytics field. Thanks to the unique wealth of authors’ backgrounds and expertise, which include authors of R packages and experts in methods and applications, the book offers a comprehensive array of methods that are described thoroughly with a primer on their usage in prior research in education. These methods include sequence analysis, Markov models, factor analysis, process mining, network analysis, predictive modeling, and cluster analysis among others. A step-by-step tutorial using the R programming language with real-life datasets and case studies is presented for each method. In addition, the initial chapters are devoted to getting novice researchers up to speed with the R programming learners and the basics of data analysis. The present chapter serves as an introduction to the book describing its main aim and intended audience. It describes the structure of the book and the methods covered by each chapter. It also points the readers to the companion code and data repositories to facilitate following the tutorials present in the book chapter.

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Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods

López-Pernas,

Misiejuk,

Kaliisa

et al. 2024

Learning Analytics Methods and Tutorials

View full text Add to dashboard Cite

show abstract

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Social Network Analysis: A Primer, a Guide and a Tutorial in R

Cited by 1 publication

References 46 publications

Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods

Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods

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