A Systematic Literature Review of Empirical Research on Epistemic Network Analysis in Education

Ramy Elmoazen,Laura Hirsto,Matti Tedre,Mohammed Saqr

doi:10.1109/access.2022.3149812

Abstract

Over the past decade, epistemic network analysis (ENA) has emerged as a quantitative ethnography tool for modeling discourse in different types of human behaviors. This article offers a comprehensive systematic review of ENA educational applications in empirical studies ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{n}=76$ </tex-math></inline-formula> ) published between 2010 and 2021. We review the ENA methods that research has relied on, the use of educational theories, their method of application, comparisons across groups and the main findings. Our results show that ENA has helped visually model the coded interactions and illustrate the connection strength among elements of network models. The applications of ENA have expanded beyond discourse analysis to several new areas of inquiry such as modeling surveys, log files or game play. Most of the reviewed articles used ENA based on educational theories and frameworks ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{n}=53$ </tex-math></inline-formula> , 69.7%), with one or more theories per article, while 23 articles (30.3%) did not report theoretical grounding. The implementation of ENA has enabled comparisons across groups and helped augment the insights of other methods such as process mining, however there is little evidence that studies have exploited the quantitative potential of ENA. Most of the reviewed studies used ENA on small sample size with manually coded interactions with few examples of large samples and automated coding.

Highlights

Epistemic network analysis (ENA) has emerged as a method for discourse modeling
The resulting epistemic network analysis (ENA) model contains information about (i) Codes, which are the people/ concepts connected in the ENA model, (ii) Relations, which is how codes relate to each other, (iii) Stanzas, which are the units of identification based on either time or process, and (iv) Evidence, which verifies the connection between codes [33]
ENA can be performed using the web tool or the R package rENA [34]. It is beyond the scope of this review to offer a comprehensive overview of ENA, and readers interested in reading more about the theory and methods are advised to consult the tutorial by Shaffer et al [10] or Shaffer’s textbook on quantitative ethnography [5]

Summary

Introduction

Epistemic network analysis (ENA) has emerged as a method for discourse modeling. The method builds on the notion that “the connections between ideas and actions are more significant to the learning process than either ideas or actions separately” [1]. ENA was developed to address these issues by using several mathematical principles that aim to quantify the strength of connections and offer fixed layouts as well as several options for comparing networks across groups [2] Another feature of ENA was its emphasis on modeling dynamic interactions, which showed how and when different codes were shared among collaborators [10]. ENA can be performed using the web tool or the R package rENA [34] It is beyond the scope of this review to offer a comprehensive overview of ENA, and readers interested in reading more about the theory and methods are advised to consult the tutorial by Shaffer et al [10] or Shaffer’s textbook on quantitative ethnography [5]. For more about the mathematical foundations, readers are advised to read the work of Bowman et al [2]

Methods

Discussion

Conclusion