{"id":2134,"date":"2025-02-22T17:26:14","date_gmt":"2025-02-22T15:26:14","guid":{"rendered":"https:\/\/sites.uef.fi\/learning-analytics\/?page_id=2134"},"modified":"2026-03-07T21:18:47","modified_gmt":"2026-03-07T19:18:47","slug":"tna","status":"publish","type":"page","link":"https:\/\/sites.uef.fi\/learning-analytics\/tna\/","title":{"rendered":"Transition Network Analysis"},"content":{"rendered":"\n<p>Transition Network Analysis (TNA) is a novel learning analytics method that integrates <strong>Stochastic Process Mining<\/strong> and <strong>probabilistic graph representation<\/strong> to model, visualize, and analyze patterns in learning process data. The method captures both relational and temporal aspects, offering a comprehensive and rigorous view of learning behaviors. The main features of TNA are:<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"437\" src=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-2-1024x437.png\" alt=\"\" class=\"wp-image-2173\" style=\"width:622px;height:auto\" srcset=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-2-1024x437.png 1024w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-2-300x128.png 300w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-2-768x327.png 768w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-2-1536x655.png 1536w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-2-2048x873.png 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Centrality analysis<\/strong> to identify important learning events.<\/li>\n\n\n\n<li><strong>Community detection<\/strong> to uncover behaviors that commonly occur together.<\/li>\n\n\n\n<li><strong>Clustering<\/strong> to reveal different temporal patterns in learning processes.<\/li>\n\n\n\n<li><strong>Significance testing<\/strong> to validate key transitions and remove noise.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"819\" height=\"1024\" src=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1-819x1024.png\" alt=\"\" class=\"wp-image-2170\" style=\"width:446px;height:auto\" srcset=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1-819x1024.png 819w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1-240x300.png 240w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1-768x960.png 768w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1-1229x1536.png 1229w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1-1638x2048.png 1638w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/02\/image-1.png 2000w\" sizes=\"auto, (max-width: 819px) 100vw, 819px\" \/><\/figure>\n\n\n\n<p>TNA will be presented for the first time at the Learning Analytics &amp; Knowledge conference (LAK) 2025. <\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Mohammed Saqr, Sonsoles L\u00f3pez-Pernas, Tiina T\u00f6rm\u00e4nen, Rogers Kaliisa, Kamila Misiejuk, and Santtu Tikka. 2025.<em> Transition Network Analysis: A Novel Framework for Modeling, Visualizing, and Identifying the Temporal Patterns of Learners and Learning Processes<\/em>. In Proceedings of the 15th International Learning Analytics and Knowledge Conference (LAK &#8217;25). Association for Computing Machinery, New York, NY, USA, 351\u2013361. <a href=\"https:\/\/doi.org\/10.1145\/3706468.3706513\">https:\/\/doi.org\/10.1145\/3706468.3706513<\/a><\/li>\n<\/ul>\n\n\n\n<p>TNA can be implemented using the R package of the same name, available on CRAN:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>CRAN page:<\/strong> Santu Tikka, Sonsoles L\u00f3pez-Pernas, Mohammed Saqr (2024).&nbsp;<em>tna: An R package for Transition Network Analysis<\/em>. R package version 1.0.0,&nbsp;<a href=\"https:\/\/github.com\/sonsoleslp\/tna\">https:\/\/github.com\/sonsoleslp\/tna<\/a>.<\/li>\n\n\n\n<li><strong>Citation<\/strong>: Tikka, S., L\u00f3pez-Pernas, S., &amp; Saqr, M. (2025). tna: An R Package for Transition Network Analysis. <em>Applied Psychological Measurement<\/em>. <a href=\"https:\/\/doi.org\/10.1177\/01466216251348840 \">https:\/\/doi.org\/10.1177\/01466216251348840 <\/a><\/li>\n<\/ul>\n\n\n\n<p>The reference manual is available in <a href=\"https:\/\/sonsoles.me\/tna\">https:\/\/sonsoles.me\/tna<\/a> <\/p>\n\n\n\n<p>Recently, we have released a Python version:<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"748\" height=\"757\" src=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2026\/02\/download.png\" alt=\"\" class=\"wp-image-2497\" style=\"aspect-ratio:0.9881107189299647;width:553px;height:auto\" srcset=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2026\/02\/download.png 748w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2026\/02\/download-296x300.png 296w\" sizes=\"auto, (max-width: 748px) 100vw, 748px\" \/><\/figure>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>PyPI page: <\/strong>Saqr, M., Tikka, S., &amp; L\u00f3pez-Pernas, S. (2026). <em>TNA: Transition Network Analysis for Python<\/em>. <a href=\"https:\/\/pypi.org\/project\/tnapy\/\">https:\/\/pypi.org\/project\/tnapy\/<\/a><\/li>\n\n\n\n<li><strong>Tutorial<\/strong>: <a href=\"https:\/\/sonsoles.me\/extra\/tna-py.html\">https:\/\/sonsoles.me\/extra\/tna-py.html <\/a><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Learning TNA<\/h2>\n\n\n\n<p>Latest updated TNA tutorials:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Saqr, Mohammed, and Sonsoles L\u00f3pez-Pernas. 2026.&nbsp;\u201cAn Updated Comprehensive Tutorial on Transition Network Analysis (TNA).\u201d&nbsp;<a href=\"https:\/\/sonsoleslp.github.io\/posts\/tna-tutorial\/\">https:\/\/sonsoleslp.github.io\/posts\/tna-tutorial\/<\/a>.<\/li>\n\n\n\n<li>Saqr, Mohammed, and Sonsoles L\u00f3pez-Pernas. 2026.&nbsp;\u201cTNA Data Preparation: A Comprehensive Guide to `Prepare_data()`.\u201d&nbsp;<a href=\"https:\/\/sonsoleslp.github.io\/posts\/tna-data\/\">https:\/\/sonsoleslp.github.io\/posts\/tna-data\/<\/a>.<\/li>\n\n\n\n<li>Saqr, Mohammed, and Sonsoles L\u00f3pez-Pernas. 2026.&nbsp;\u201cTNA Clustering: Discovering and Analysis of Clusters.\u201d&nbsp;<a href=\"https:\/\/sonsoleslp.github.io\/posts\/tna-clustering\/\">https:\/\/sonsoleslp.github.io\/posts\/tna-clustering\/<\/a>.<\/li>\n\n\n\n<li>Saqr, Mohammed, and Sonsoles L\u00f3pez-Pernas. 2026.&nbsp;\u201cTNA Group Analysis: Analysis and Comparison of Groups.\u201d&nbsp;<a href=\"https:\/\/sonsoleslp.github.io\/posts\/tna-group\/\">https:\/\/sonsoleslp.github.io\/posts\/tna-group\/<\/a>.<\/li>\n<\/ul>\n\n\n\n<p>There are three tutorials available about TNA in our <a href=\"http:\/\/lamethods.org\">latest book<\/a>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"text-decoration: underline\"><strong>Basic tutorial<\/strong>: <\/span>Mohammed Saqr, Sonsoles L\u00f3pez-Pernas, Santtu Tikka (2025).&nbsp;<em>Mapping Relational Dynamics with Transition Network Analysis: A Primer and Tutoria<\/em><strong>l<\/strong>. In M. Saqr &amp; S. L\u00f3pez-Pernas (Eds.),&nbsp;<em>Advanced Learning Analytics Methods: AI, Precision and Complexity<\/em>&nbsp;(in \u2013 press). Springer.&nbsp;<a href=\"https:\/\/lamethods.org\/book2\/chapters\/ch15-tna\/ch15-tna.html\">https:\/\/lamethods.org\/book2\/chapters\/ch15-tna\/ch15-tna.html<\/a><\/li>\n\n\n\n<li><span style=\"text-decoration: underline\"><strong>Frequency-based TNA<\/strong>: <\/span>Mohammed Saqr, Sonsoles L\u00f3pez-Pernas, Santtu Tikka (2025).&nbsp;<em>Capturing The Breadth and Dynamics of the Temporal Processes with Frequency Transition Network Analysis: A Primer and Tutorial<\/em>. In M. Saqr &amp; S. L\u00f3pez-Pernas (Eds.),&nbsp;<em>Advanced Learning Analytics Methods: AI, Precision and Complexity<\/em>&nbsp;(in \u2013 press). Springer.&nbsp;<a href=\"https:\/\/lamethods.org\/book2\/chapters\/ch16-ftna\/ch16-ftna.html\">https:\/\/lamethods.org\/book2\/chapters\/ch16-ftna\/ch16-ftna.html<\/a><\/li>\n\n\n\n<li><span style=\"text-decoration: underline\"><strong>Clustering:<\/strong> <\/span>Sonsoles L\u00f3pez-Pernas, Santtu Tikka, Mohammed Saqr (2025).<em>&nbsp;Mining Patterns and Clusters with Transition Network Analysis: A Heterogeneity Approach.<\/em> In M. Saqr &amp; S. L\u00f3pez-Pernas (Eds.),&nbsp;<em>Advanced Learning Analytics Methods: AI, Precision and Complexity<\/em>&nbsp;(in \u2013 press). Springer.&nbsp;<a href=\"https:\/\/lamethods.org\/book2\/chapters\/ch17-tna-clusters\/ch17-tna-clusters.html\">https:\/\/lamethods.org\/book2\/chapters\/ch17-tna-clusters\/ch17-tna-clusters.html<\/a><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">TNA for non-coders<\/h2>\n\n\n\n<p>We have released a plugin to work with TNA using the desktop app Jamovi: <a href=\"https:\/\/github.com\/sonsoleslp\/jTNA\">https:\/\/github.com\/sonsoleslp\/jTNA <\/a><\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"554\" src=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/05\/image-1024x554.png\" alt=\"\" class=\"wp-image-2203\" style=\"width:640px;height:auto\" srcset=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/05\/image-1024x554.png 1024w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/05\/image-300x162.png 300w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/05\/image-768x416.png 768w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/05\/image-1536x831.png 1536w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/05\/image.png 1593w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>We are also working on a Shiny web application to be able to use tna without coding: <a href=\"https:\/\/sonsoleslp.shinyapps.io\/tna-app\">https:\/\/sonsoleslp.shinyapps.io\/tna-app<\/a>. <\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>L\u00f3pez-Pernas, S., Tikka, S., Misiejuk, K., &amp; Saqr, M. (2026). <strong>tna-shiny: Advanced Analytics Just a Few Clicks Away<\/strong>. <em>Proceedings TEEM 2025: Thirteennth International Conference on Technological Ecosystems for Enhancing Multiculturality. TEEM 2025. Lecture Notes in Computer Science<\/em>. TEEM 2025, Salamanca, Spain.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"580\" src=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/03\/Screenshot-2025-03-02-at-15.31.41-1024x580.png\" alt=\"\" class=\"wp-image-2176\" style=\"width:639px;height:auto\" srcset=\"https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/03\/Screenshot-2025-03-02-at-15.31.41-1024x580.png 1024w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/03\/Screenshot-2025-03-02-at-15.31.41-300x170.png 300w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/03\/Screenshot-2025-03-02-at-15.31.41-768x435.png 768w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/03\/Screenshot-2025-03-02-at-15.31.41-1536x869.png 1536w, https:\/\/sites.uef.fi\/learning-analytics\/wp-content\/uploads\/sites\/444\/2025\/03\/Screenshot-2025-03-02-at-15.31.41-2048x1159.png 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>Stay tuned to find out all new developments!<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Empirical papers using TNA<\/strong><\/h2>\n\n\n\n<p>Even though TNA is a very recent method, a few articles implementing it have already been published. The list is growing every month: <\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>L\u00f3pez-Pernas, S., Misiejuk, K., Kaliisa, R., &amp; Saqr, M. (2025)<strong>. Capturing the process of students\u2019 AI interactions when creating and learning complex network structures.<\/strong>&nbsp;<em>IEEE Transactions on Learning Technologies<\/em>, 1\u201313. <a href=\"https:\/\/doi.org\/10.1109\/tlt.2025.3568599\">https:\/\/doi.org\/10.1109\/tlt.2025.3568599<\/a> <\/li>\n\n\n\n<li>T\u00f6rm\u00e4nen, T., Saqr, M., L\u00f3pez-Pernas, S., M\u00e4nty, K., Suoraniemi, J., Heikkala, N., &amp; J\u00e4rvenoja, H. (2025). <strong>Emotional dynamics and regulation in collaborative learning<\/strong>. <em>Learning and Instruction<\/em>, <em>100<\/em>, 102188. <a href=\"https:\/\/doi.org\/10.1016\/j.learninstruc.2025.102188\">https:\/\/doi.org\/10.1016\/j.learninstruc.2025.102188<\/a><\/li>\n\n\n\n<li><strong>L\u00f3pez-Pernas, S.<\/strong>, Misiejuk, K., Oliveira, E., &amp; <strong>Saqr, M. <\/strong>(2025). The dynamics of the self-regulation process in student-AI interactions: The case of problem-solving in programming education. <em>Proceedings of the 25th Koli Calling International Conference on Computing Education Research<\/em>, 1\u201312. <a href=\"https:\/\/doi.org\/10.1145\/3769994.3770043\">https:\/\/doi.org\/10.1145\/3769994.3770043<\/a> <\/li>\n\n\n\n<li>Kilanioti, I., Saqr, M., &amp; L\u00f3pez-Pernas, S. (2026).<strong> Exploring the Process of Students\u2019 Learning in the Laboratory with Transition Network Analysis<\/strong>. <em>Proceedings TEEM 2025: Thirteennth International Conference on Technological Ecosystems for Enhancing Multiculturality. TEEM 2025. Lecture Notes in Computer Science<\/em>.<\/li>\n\n\n\n<li>Heikkinen, S., Saqr, M., Malmberg, J., &amp; Tedre, M. (2025). <strong>A longitudinal study of interplay between student engagement and self-regulation<\/strong>. <em>International Journal of Educational Technology in Higher Education<\/em>, <em>22<\/em>(1), 1\u201328. <a href=\"https:\/\/doi.org\/10.1186\/s41239-025-00523-3\">https:\/\/doi.org\/10.1186\/s41239-025-00523-3<\/a><\/li>\n\n\n\n<li>Heikkinen, S., Saqr, M., Malmberg, J., &amp; Tedre, M. (2025). <strong>The interplay of engagement and learning regulation in online learning<\/strong>. In <em>Lecture Notes in Educational Technology<\/em> (pp. 427\u2013436). Springer Nature Singapore. <a href=\"https:\/\/doi.org\/10.1007\/978-981-96-5658-5_43 \">https:\/\/doi.org\/10.1007\/978-981-96-5658-5_43 <\/a><\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Transition Network Analysis (TNA) is a novel learning analytics method that integrates Stochastic Process Mining and probabilistic graph representation to model, visualize, and analyze patterns in learning process data. The method captures both relational and temporal aspects, offering a comprehensive and rigorous view of learning behaviors. The main features of TNA are: TNA will be [&hellip;]<\/p>\n","protected":false},"author":1045,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-2134","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Transition Network Analysis<\/title>\n<meta name=\"description\" content=\"Transition Network Analysis (TNA) is a novel learning analytics method that integrates Stochastic Process Mining and probabilistic graph representation to model, visualize, and analyze patterns in learning process data. 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