Epistemic Network Analysis: A Worked Example of Theory-Based Learning Analytics
Open accessAbstract
In this chapter, we look at the role of theory in learning analytics.Researchers who study learning are blessed with unprecedented quantities of data, whether information about staggeringly large numbers of individuals or data showing the microscopic, moment-by-moment actions in the learning process.It is a brave new world.We can look at second-by-second changes in where skills are effective by looking at thousands of students in a MOOC.of the Journal of Learning Analytics, however, it is dangerous to think that with enough information, the data can speak for themselves -that we can conduct analyses of learning without theories of learning.In fact, the opposite is true.With larger amounts of data, large enough so that random effects are normally distributed, but small enough to be obtained using traditional data collection techniques.Applying these techniques to datasets that are orders of magnitude larger in length and number of variables without a strong theoretical foundation is perilous at best.In what follows, we look at this question not by anatheoretical framework.What Wise and Shaffer suggest -and what the articles and commentaries in the special section of the Journal of Learning Analytics show -is that conducting theory-based learning analytics is challenging.As a result, our approach in what follows through the use of a worked example: the presentation of a problem along with a step-by-step description of In doing so, our aim is not to provide an ideal solution for others to emulate, nor to suggest that our particular use of theory in learning analytics is better than of a theory-based approach -as opposed to an atheoretical or data-driven approach -to the analysis of large educational datasets.We do so by presenting epistemic network analysis (ENA; Andrist, Collier, Chapter 15: Epistemic Network Analysis: A Worked Example of Theory-Based Learning AnalyticsDavid Williamson Shaffer and A. R. Ruis data-driven -approach.We do so by presenting 1) epistemic frame theory as an approach cational game design based on epistemic frame theory; and 3) epistemic network analysis of learning analytics.
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“It combines quantitative and qualitative analyses and closes the interpretative loop by enabling researchers to triangulate the network results using original data (Shaffer & Ruis, 2017).”
InfluentialLee, I. A., Grover, S., Martin, F., Pillai, S., & Malyn‐Smith, J. (2019) · Journal of Science Education and Technology · doi:10.1007/s10956-019-09803-w · Cited by 209 · see citing works
“The automated assessment tool is based on epi-stemic network analysis or ENA (Shaffer et al. 2016; Shaffer et al. 2009; Shaffer and Ruis 2017).”
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“The process of creating epistemic network models is explained in detail elsewhere (Shaffer, 2017; Shaffer et al., 2016; Shaffer & Ruis, 2017), but in brief, ENA uses a sliding window to construct a network model for each turn of talk in the data.”
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“these results be communicated simply and clearly to practitioners? Moreover, how are such differences translated into practice? The literature review has left us pondering the comparison between ENA and SNA and multivariate analysis which are methods that ENA was built to address some of their shortcomings [2], [10],…”
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“ENA measures when and how often learners make links between domain-relevant elements during their work.”
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“In our analysis, each point in the sensemaking space is the centroid of each student ’ s network, that is, a sum-mary of their network, within the sensemaking space (Shaffer and Ruis 2017).”
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“Furthermore, ENA enabled us to perform comparative analysis among different results within a set of networks (Shaffer & Ruis, 2017 ).”
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“ENA allows to measure the co-occurrence of elements in coded data and thus to identify the connections between them by modeling the weighted structure of these connections and illustrating this structure in dynamic network models (Shaffer & Ruis, 2017; Shaffer et al., 2016).”
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“To explore associations between students’ perceptions of feedback and their adaptations of SRL and how these differed by context, we employed epistemic network analysis (ENA; Shaffer & Ruis, 2017).”
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“ENA was used to exam - ine the overall structure of group’s immediate uptakes based on co-occurrence relationships of codes and was visualized in a network model to demonstrate the immediate effect (Shaffer & Ruis, 2017; Shaffer et al., 2009, 2016).”
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“The centroid takes into account the weights of the connections between the nodes of the cognitive presence and can be represented as a corresponding plotted dot (Bressler et al., 2019; Liu et al., 2021; D. Shaffer & Ruis, 2017).”
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“Each learner’s cognitive processing network has a centroid that represents a summary of its network (Shaffer & Ruis, 2017).”
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Öner, D. (2019) · Australasian Journal of Educational Technology · doi:10.14742/ajet.5192 · Cited by 44 · see citing works
“Implications for future research on the TPACK construct In the present study, the TPACK development of preservice teachers was evaluated using ENA, which was originally developed to visualise co-occurrences of frame elements in discourse (Shaffer & Ruis, 2017).”
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A network analytic approach to gaze coordination during a collaborative task
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“…use a technique from learning analytics called epistemic network analysis (ENA), which measures, visualizes, and enables both quantitative and qualitative comparison of complex, collaborative interactions (Shaffer & Ruis, 2017; Shaffer, 2017; Shaffer, Collier, & Ruis, 2016; Shaffer et al., 2009).”
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“Explaining the process is beyond our research and page limits, therefore, we recommend readers to be familiar with the process in a worked example by Shaffer who brought the concept to the LA community [33].”
MethodKaliisa, R., Misiejuk, K., Irgens, G. A., & Misfeldt, M. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-67788-6_1 · Cited by 32 · see citing works
“Using ENA, researchers analyze the development of learners’ epistemic frames by modeling connections in student discourse [13] and measuring the co-occurrence of concepts within the conversations, topics, or activities that take place during learning [11, 12].”
BackgroundMethodFour paradigms in learning analytics: Why paradigm convergence matters
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“…using methods like clustering to gain understanding of deeper differences between individuals (Amershi & Conati, 2009), and epistemic network analysis of the difference in patterns of discourse between college and high school students working through the same curriculum (Shaffer & Ruis, 2017).”
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“The thickness of the line is an indicator of the proportion of stanzas in which the two codes co-occurred (Shaffer & Ruis, 2017).”
BackgroundMethodPedagogical design: Bridging learning theory and learning analytics
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“Shaffer and Ruis (2017) offer a worked example of ENA applied to educational data from a learning environment Pedagogical Design: Bridging Learning Theory and Learning Analytics 13 to illustrate the potential of this approach.”
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“To address these research gaps, this study used the epistemic network analysis (ENA; Shaffer et al., 2016; Shaffer & Ruis, 2017), a network analysis technique,”
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Cheng, Y., Lyons, K., Chen, G., Gašević, D., & Swiecki, Z. (2024) · Proceedings of the 14th Learning Analytics and Knowledge Conference · doi:10.1145/3636555.3636866 · Cited by 29 · see citing works
“ENA is a widely used learning analytic technique for modeling actions via network models [31].”
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“ONA extends ENA to emphasize (1) the directions of co-occurrences, and (2) self-loops when a learning activity repeats itself.”
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“…algorithms to calculate the connections between the coded data of concepts, keywords or ideas within given texts, visualised them in dynamic network models and illustrated the changes in structures and connection strength over time (Shaffer et al., 2009; Shaffer et al., 2016; Shaffer & Ruis, 2017).”
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“ENA is a novel but established method for quantifying and visualizing coded data in forms of networked models that show the structure of connections and strength of association among elements of a framework (Shaffer, 2017; Shaffer & Ruis, 2017; Shaffer et al., 2016).”
MethodSupporting teachers' intervention in students' virtual collaboration using a network based model
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“In the case of virtual internships, Shaffer and colleagues developed a suite of theoretically grounded learning analytics tools that allow researchers to interpret and compare students’ network of relations between critical concepts [11, 7, 12, 13].”
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“Based on QE, segments [38] (m rows) are the smallest units considered for analysis.”
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“In the study, the ENA web tool was used to generate a two-dimensional network graph visualizing the connections between the elements corresponding to the coding framework shown in Table 1 (Shaffer & Ruis, 2017).”
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“ENA serves as a valuable method to analyze and visualize the findings of our qualitative content analysis, that is, the co-occurrence of the dimensions of facilitators or barriers in the included studies [56,58-60].”
Liu, S., Kang, L., Liu, Z., Zhao, L., Yang, Z., & Su, Z. M. (2022) · Journal of Computing in Higher Education · doi:10.1007/s12528-022-09335-0 · Cited by 24 · see citing works
“Finally, ENA presents the codes in the exact same places of the projection space and further identifies whether there are significant differences between these codes among different individuals or groups (Shaffer & Ruis, 2017).”
BackgroundWhat Can Analytics for Teamwork Proxemics Reveal About Positioning Dynamics In Clinical Simulations?
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“, in terms of their plotted point position) and network difference graphs which illustrate the differences between two networks by subtraction (Shaffer et al., 2016; Shaffer and Ruis, 2017).”
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Epistemic Network Analysis Visualization
Tan, Y., Hinojosa, C., Marquart, C. L., Ruis, A. R., & Shaffer, D. W. (2022) · Communications in computer and information science · doi:10.1007/978-3-030-93859-8_9 · Cited by 19 · see citing works
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“Epistemic network analysis (ENA) is still a relatively novel analysis method focused on modelling co-occurrences of coded data [35], which has been used in learning analytics as an approach to analyse (co-)temporal relationships among communication behaviours [40].”
BackgroundMethodFinding Meaning in Log-File Data
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“Epistemic network analysis (ENA) is a technique that visualises the weighted connections between a relatively small number of nodes in discourse data (Shaffer and Ruis, 2017).”
BackgroundNewton, M. H., Annetta, L. A., & Bressler, D. M. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10057-w · Cited by 19 · see citing works
“…a set of meaningful features in the data (i.e., codes); (2) that the data has local structure (i.e., conversations); and (3) that an important feature of the data is the way that codes are connected to one another within conversations (Shaffer, 2017; Shaffer & Ruis, 2017; Shaffer et al., 2016).”
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An Epistemic Network Approach to Teacher Students’ Professional Vision in Tutoring Video Analysis
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“From coded data representing these network elements, ENA recognizes links, calculates the relationship intensity and the elemental structure of the associations between these features, and displays them graphically (Shaffer and Ruis, 2017; Bowman et al., 2021).”
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“…are projected on a two-dimensional plot, where the x -axis accounts for the highest percentage of variance explained by a dimension and the y -axis is an orthogonal dimension that accounts for the next highest percentage of variance (Shaffer, 2017; Shaffer et al., 2009, 2016; Shaffer & Ruis, 2017).”
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“…analysis is a dimensional - ity reduction process of complex data, which has limitations for representations data that is more than two-dimensional (Shaffer & Ruis, 2017), while common models of conceptions of learning are the five-factor model and the seven-factor model (Säljö, 1979; Täks et al.,…”
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“To answer RQ3, epistemic network analysis (ENA; Shaffer, 2017; Shaffer et al., 2016; Shaffer & Ruis, 2017) was employed based on the semi-structured interviews among the 16 students.”
A systematic review of visual representations for analyzing collaborative discourse
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Self-citationMerikko, J., & Kivimäki, V. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.1010255 · Cited by 17 · see citing works
“To answer the first research question, we applied Epistemic Network Analysis (Shaffer et al., 2016; Shaffer, 2017; Shaffer and Ruis, 2017) to our data using the ENA 1.”
MethodInfluentialEspino, D. P., Lee, S. B., Tress, L. V., Baker, T. T., & Hamilton, E. R. (2020) · Research in Social Sciences and Technology · doi:10.46303/ressat.05.01.5 · Cited by 13 · see citing works
“ENA is grounded in epistemic network theory, which posits that “learning can be characterized by the structure of connections that students make among elements of authentic practice” (Shaffer & Ruis, 2017, p. 182).”
BackgroundFostering cognitive strategies for learning with 360° videos in history education contexts
Nachtigall, V., Yek, S., Lewers, E., Brunnenberg, C., & Rummel, N. (2022) · Unterrichtswissenschaft · doi:10.1007/s42010-022-00154-x · Cited by 13 · see citing works
“ENA models the weighted structure of these connections and illustrates the respective structure in dynamic network models (Shaffer and Ruis 2017; Shaffer et al. 2016).”
BackgroundStahnke, R., & Friesen, M. E. (2023) · Frontiers in Education · doi:10.3389/feduc.2023.1253459 · Cited by 12 · see citing works
Elmoazen, R., Saqr, M., Hirsto, L., & Tedre, M. (2024) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-024-09431-6 · Cited by 17 · see citing works
“The illustrated ENA graphs display the interaction between codes within a unit of analysis to understand the structure and dynamics of the discourse (Shaffer & Ruis, 2017).”
Gaining Insight by Transforming Between Temporal Representations of Human Interaction
Lund, K., Quignard, M., & Shaffer, D. W. (2017) · Journal of Learning Analytics · doi:10.18608/jla.2017.43.6 · Cited by 12 · see citing works
“The specific method with which ENA does this is described in detail elsewhere (Shaffer, 2014; Shaffer, Collier, & Ruis, 2016; Shaffer & Ruis, 2017; Siebert-Evenstone et al., 2016), but in brief, ENA creates network models by computing the co-occurrences of codes in recent temporal context — that…”
MethodSelf-citationSiebert-Evenstone, A., & Shaffer, D. W. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-33232-7_19 · Cited by 12 · see citing works
Self-citationLi, S., Huang, X., Wang, T., Pan, Z., & Lajoie, S. P. (2022) · Journal of Learning Analytics · doi:10.18608/jla.2022.7571 · Cited by 12 · see citing works
Learning Analytics for a New Epistemological Perspective of Learning
Oshima, J., & Shaffer, D. W. (2021) · Information and Technology in Education and Learning · doi:10.12937/itel.1.1.inv.p003 · Cited by 12 · see citing works
Self-citationTan, J. S. H., Chen, W., Su, J., & Su, G. (2023) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-023-09390-4 · Cited by 11 · see citing works
Simplification of Epistemic Networks Using Parsimonious Removal with Interpretive Alignment
Wang, Y., Swiecki, Z., Ruis, A. R., & Shaffer, D. W. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-67788-6_10 · Cited by 11 · see citing works
Self-citationWeiler, D. T., Lingg, A. J., Eagan, B. R., Shaffer, D. W., & Werner, N. E. (2022) · Ergonomics · doi:10.1080/00140139.2022.2051609 · Cited by 11 · see citing works
Self-citationAssessing approaches to learning with nonparametric multidimensional scaling
Knezek, G., Gibson, D., Christensen, R. W., Trevisan, O., & Carter, M. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13275 · Cited by 11 · see citing works
“Finally, we have shown that ENA (Shaffer & Ruis, 2017) is a useful theory and toolset for exploratory research that can help bridge traditional psychometrics and game-based learning analysis.”
BackgroundVega, H., Irgens, G. A., & Bailey, C. S. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-67788-6_19 · Cited by 11 · see citing works
“The quantitative perspective allows for making sense of large data sets through data visualizations in order to uncover relationships between codes and to analyze small-d discourse (what participants say) and big-D discourse (the meanings of the community) [21].”
BackgroundIrgens, G. A. (2022) · Learning Media and Technology · doi:10.1080/17439884.2021.2018608 · Cited by 11 · see citing works
Wang, D., Gao, L., Shan, D., Chen, G., Zhang, C., & Kao, B. (2024) · Journal of Science Education and Technology · doi:10.1007/s10956-024-10154-4 · Cited by 10 · see citing works
“Drawing on epistemic frame theory, ENA emphasizes the importance of connections between discourse elements rather than their mere presence (Shaffer & Ruis, 2017).”
Woollaston, S., Flanagan, B., Ocheja, P., Toyokawa, Y., & Ogata, H. (2025) · Proceedings of the 15th International Learning Analytics and Knowledge Conference · doi:10.1145/3706468.3706556 · Cited by 10 · see citing works
“We applied epistemic network analysis [21] to our data using the ENA Web Tool (version 1.7.0) [17].”
InfluentialStahnke, R., & Gegenfurtner, A. (2025) · Learning and Instruction · doi:10.1016/j.learninstruc.2025.102167 · Cited by 10 · see citing works
iTalk–iSee: A participatory visual learning analytical tool for productive peer talk
Hu, L., Wu, J., & Chen, G. (2022) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-022-09374-w · Cited by 10 · see citing works
“There is a growing awareness among researchers regarding how specific learning theories can guide the development of learning tools (Hillaire et al., 2016; Martinez-Maldonado et al., 2021; Shaffer & Ruis, 2017; Wise & Schaffer, 2015).”
BackgroundPratt, S. M. (2019) · Reading Psychology · doi:10.1080/02702711.2019.1674434 · Cited by 10 · see citing works
“To create the visual graphs of the coded data, ENA uses dimensional reduction through an optimization routine that minimizes the differences between plotted points and the centroid of each group’s network (Shaffer et al., 2016; Shaffer & Ruis, 2017).”
BackgroundMethodVujović, M., Amarasinghe, I., & Hernández‐Leo, D. (2021) · Sensors · doi:10.3390/s21092898 · Cited by 10 · see citing works
“The network centroids can be described as something similar to the centre of the mass of an object [29] and each condition has its own centroid in this case.”
BackgroundMethodInfluentialConnected design rationale: a model for measuring design learning using epistemic network analysis
Irgens, G. A. (2021) · Instructional Science · doi:10.1007/s11251-021-09551-8 · Cited by 10 · see citing works
“Shaffer and Ruis (2017) discuss the mathematics ENA in more detail.”
Hung, H.-C., Chuang, M.-Y., & Chen, C.-H. (2024) · International Journal of Science and Mathematics Education · doi:10.1007/s10763-024-10470-6 · Cited by 9 · see citing works
“…data connections, assuming the systematic identification of meaningful features (codes), recognizing local data structure (conversations), and emphasizing the significance of code connections within conversations (Bowman et al., 2021; Shaffer, 2017; Shaffer et al., 2016; Shaffer & Ruis, 2017).”
Pratt, S. M., Coleman, J. M., & Dantzler, J. (2022) · Literacy Research and Instruction · doi:10.1080/19388071.2022.2039334 · Cited by 8 · see citing works
“ENA analyzes coded data segment-by-segment to quantify the co-occurrence of elements within the same or neighboring segments to produce a weighted network of co-occurrences (Shaffer et al., 2016; Shaffer & Ruis, 2017).”
BackgroundZhang, X., Wang, Y., & Chen, H. (2025) · Studies In Educational Evaluation · doi:10.1016/j.stueduc.2024.101441 · Cited by 8 · see citing works
- Authors
- University of Wisconsin–Madison, U., Shaffer, D. W., Ruis, A. R., & University of Wisconsin–Madison, U.
- Affiliations
- University of Wisconsin–Madison (US)
- Venue
- Handbook of Learning Analytics
- Published
- 2017-05
- Pages
- 175-187
- OpenAlex
- W2611007723
- Cited by
- 255
- References
- 1
- Citations by year
- 2026: 30 · 2025: 45 · 2024: 47 · 2023: 34 · 2022: 31 · 2021: 25 · 2020: 15 · 2019: 16 · 2018: 9 · 2017: 3
- FWCI
- 34.95
- Type
- book chapter
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Society for Learning Analytics Research (SoLAR) eBooks (publishedVersion, cc-by)
- Funders
- John D. and Catherine T. MacArthur Foundation
- Spencer Foundation
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Keywords
- epistemic network analysis, educational game design, data-driven analysis, epistemic networks
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