Publications

Also on Google Scholar and ORCID.

† doctoral student under my main supervision · ‡ undergraduate student under my supervision

2026
How do critical evaluations of generative AI outputs shape teacher agency? A mixed-methods comparative analysis
Sha, L., Liang, Z., Zhao, L., Li, Y., Fernandez-Nieto, G. M., Tsai, Y., Swiecki, Z., Chen, G., & Gašević, D.
International Journal of Human–Computer Interaction

In press

Capturing and sharing know-how through visual process representations: A human-centred approach to teacher workflows
Fernandez-Nieto, G. M., Echeverria, V., Li, Y., Tsai, Y., Sha, L., Chen, G., Gašević, D., & Swiecki, Z.
Behaviour & Information Technology. Advance online publication

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Ink and algorithm: Exploring temporal dynamics in generative AI-assisted writing
Yang, K., Cheng, Y.†, Zhao, L., Raković, M., Swiecki, Z., Gašević, D., & Chen, G.
British Journal of Educational Technology, 57(2), 508–534
Community of inquiry in motion: Modeling inquiry dynamics with movement analysis (MOVA)
Ba, S., Swiecki, Z., Tan, Y., Lu, G., Shaffer, D. W., & Gašević, D.
Computers & Education, 242, 105513
Towards reliable generative AI-driven scaffolding: Reducing hallucinations and enhancing quality in self-regulated learning support
Qian, K., Liu, S., Li, T., Raković, M., Li, X., Guan, R., Molenaar, I., Nawaz, S., Swiecki, Z., Yan, L., & Gašević, D.
Computers & Education, 240, 105448
Open tools for the authentic assessment of GenAI-assisted practices
Swiecki, Z.
In Designing University Assessment for a World with Artificial Intelligence. Routledge

In press

From diagnosis to redesign: Using quantitative ethnography to improve multi-agent LLM reasoning
Khatri, V., Cusimano, A., Swiecki, Z., Xu, Z., Liu, X., & Yu, R.
Eighth International Conference on Quantitative Ethnography (ICQE26), Hiroshima, Japan

Accepted

Toward an affordance-based taxonomy of GenAI-assisted writing tools
Cheng, Y.†, & Swiecki, Z.
Eighth International Conference on Quantitative Ethnography (ICQE26), Hiroshima, Japan

Accepted

Trace: Replay
Arora, J., & Swiecki, Z.
Visualization tool for GenAI-assisted writing sessions
Trace: Browser
Wen, J., Arora, J., & Swiecki, Z.
Browser extension for capturing GenAI-assisted writing; closed beta
Method-facing simulation of coded collaborative discourse
Fang, Z.†, & Swiecki, Z.
International Journal of Computer-Supported Collaborative Learning

Under review

2025
Asking generative artificial intelligence the right questions improves writing performance
Cheng, Y.†, Fan, Y., Li, X., Chen, G., Gašević, D., & Swiecki, Z.
Computers and Education: Artificial Intelligence, 8, 100374
Analytics of self-regulated learning strategies and scaffolding: Associations with learning performance
Li, T., Yan, L., Iqbal, S., Srivastava, N., Singh, S., Raković, M., Swiecki, Z., Tsai, Y., Gašević, D., Fan, Y., & Li, X.
Computers and Education: Artificial Intelligence, 8, 100410
Dissecting the temporal dynamics of embodied collaborative learning using multimodal learning analytics
Yan, L., Martinez-Maldonado, R., Swiecki, Z., Zhao, L., Li, X., & Gašević, D.
Journal of Educational Psychology, 117(1), 106–133
Investigating the effect of visualization literacy and guidance on teachers’ dashboard interpretation
Pozdniakov, S., Martinez-Maldonado, R., Tsai, Y., Echeverria, V., Swiecki, Z., & Gašević, D.
Journal of Learning Analytics, 12(1), 367–390
Desktop versus VR for collaborative sensemaking
Yang, Y., Dwyer, T., Swiecki, Z., Lee, B., Wybrow, M., Cordeil, M., Wulandari, T., Thomas, B. H., & Billinghurst, M.
Frontiers in Virtual Reality, 6, 1570383
More than words: Evidencing qualitative findings through multimodal narratives
Cheng, Y.†, & Swiecki, Z.
Advances in Quantitative Ethnography (ICQE 2025), 242–257. CCIS vol. 2677. Springer

Best Student Paper Award

Demands-resources in doctoral education: Mapping pathways to dropout intention and careers in further research
Han, J., Iveson, S. D., & Swiecki, Z.
Advances in Quantitative Ethnography (ICQE 2025). CCIS vol. 2677. Springer

Best Student Paper finalist

ShareFlow: Seamless knowledge capture and proactive push for efficient teacher workflows in higher education
Sha, L., Fernandez-Nieto, G., Li, Y., Tsai, Y., Chen, G., Wen, J., Singh, S., Feraud, I. S., Gašević, D., & Swiecki, Z.
Proceedings of the 30th International Conference on Intelligent User Interfaces (IUI ’25), 1242–1255. ACM
The company you keep: Refining neural epistemic network analysis
Fang, Z.†, Wang, W., Chen, G., & Swiecki, Z.
Proceedings of the 15th Learning Analytics and Knowledge Conference (LAK ’25), 216–226. ACM

Best Paper finalist

Qualitative parameter triangulation: A conceptual and methodological framework for event-based temporal models
Wang, Y., Carpenter, Z., Swiecki, Z., & Shaffer, D. W.
Proceedings of the 15th Learning Analytics and Knowledge Conference (LAK ’25), 537–546. ACM
TeamTeachingViz: Benefits, challenges, and ethical considerations of using a multimodal dashboard to support team teaching reflection
Alfredo, R., Mejia-Domenzain, P., Echeverria, V., Rahayu, D., Zhao, L., Alajilan, H., Swiecki, Z., Kaser, T., Gašević, D., & Martinez-Maldonado, R.
Proceedings of the 15th Learning Analytics and Knowledge Conference (LAK ’25), 58–69. ACM
Self-regulated learning processes in secondary education: A network analysis of trace-based measures
Cheng, Y.†, Guan, R., Li, T., Raković, M., Li, X., Fan, Y., Jin, F., Tsai, Y., Gašević, D., & Swiecki, Z.
Proceedings of the 15th Learning Analytics and Knowledge Conference (LAK ’25), 260–271. ACM
Turning real-time analytics into adaptive scaffolds for self-regulated learning using generative artificial intelligence
Li, T., Nath, D., Cheng, Y.†, Fan, Y., Li, X., Raković, M., Khosravi, H., Swiecki, Z., Tsai, Y., & Gašević, D.
Proceedings of the 15th Learning Analytics and Knowledge Conference (LAK ’25), 667–679. ACM
Trace: Web
Arora, J., & Swiecki, Z.
Learning analytics platform for GenAI-assisted writing
2024
Evidence-based multimodal learning analytics for feedback and reflection in collaborative learning
Yan, L., Echeverria, V., Jin, Y., Fernandez-Nieto, G., Zhao, L., Li, X., Alfredo, R., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R.
British Journal of Educational Technology, 55, 1900–1925
Towards automated transcribing and coding of embodied teamwork communication through multimodal learning analytics
Zhao, L., Gašević, D., Swiecki, Z., Li, Y., Lin, J., Sha, L., Yan, L., Alfredo, R., Li, X., & Martinez-Maldonado, R.
British Journal of Educational Technology, 55, 1673–1702
Human-centred learning analytics and AI in education: A systematic literature review
Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R.
Computers and Education: Artificial Intelligence, 6, 100215
Designing a human-centred learning analytics dashboard in-use
Alfredo, R., Echeverria, V., Zhao, L., Lawrence, L., Fan, J. X., Yan, L., Li, X., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R.
Journal of Learning Analytics, 11(3), 62–81
In conversation: Baker, Järvelä & Williamson Shaffer — The relationship between computational methods and theory in learning analytics
Swiecki, Z., Baker, R., Järvelä, S., & Shaffer, D. W.
In K. Bartimote, S. K. Howard, & D. Gašević (Eds.), Theory Informing and Arising from Learning Analytics (pp. 175–186). Springer
Epistemic network analysis and ordered network analysis in learning analytics
Tan, Y., Swiecki, Z., Ruis, A. R., & Shaffer, D. W.
In M. Saqr & S. López-Pernas (Eds.), Learning Analytics Methods and Tutorials: A Practical Guide Using R (pp. 569–634). Springer
Putting our minds together: Iterative exploration for collaborative mind mapping
Yang, Y., Dwyer, T., Swiecki, Z., Lee, B., Wybrow, M., Cordeil, M., Wulandari, T., Thomas, B. H., & Billinghurst, M.
Proceedings of the Augmented Humans International Conference 2024, 255–258
Co-designing a knowledge management tool for educator communities of practice
Fernandez-Nieto, G., Swiecki, Z., Tsai, Y., Sha, L., Wei, Y., Wen, J., Li, Y., Jin, Y., Silva Feraud, I., Li, Y., Wang, W., Chen, G., & Gašević, D.
Designing Interactive Systems Conference (DIS ’24), 1970–1990. ACM
Analytics of planning behaviours in self-regulated learning: Links with strategy use and prior knowledge
Li, T., Fan, Y., Srivastava, N., Zeng, Z., Li, X., Khosravi, H., Tsai, Y., Swiecki, Z., & Gašević, D.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 438–449. ACM
Neural epistemic network analysis: Combining graph neural networks and epistemic network analysis to model collaborative processes
Fang, Z.†, Wang, W., Chen, G., & Swiecki, Z.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 157–166. ACM
Measuring affective and motivational states as conditions for cognitive and metacognitive processing in self-regulated learning
Raković, M., Li, Y., Foumani, N., Salehi, M., Kuhlmann, L., Mackellar, G., Martinez-Maldonado, R., Haffari, G., Swiecki, Z., Li, X., Chen, G., & Gašević, D.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 701–712. ACM
Automated discourse analysis via generative artificial intelligence
Garg, G.‡, Han, J., Cheng, Y.†, Fang, Z.†, & Swiecki, Z.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 814–820. ACM
Evidence-centered assessment for writing with generative AI
Cheng, Y.†, Lyons, K., Chen, G., Gašević, D., & Swiecki, Z.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 178–188. ACM
Epistemic network analysis for end-users: Closing the loop in the context of multimodal analytics for collaborative team learning
Zhao, L., Echeverria, V., Swiecki, Z., Yan, L., Alfredo, R., Li, X., Gašević, D., & Martinez-Maldonado, R.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 90–100. ACM
SLADE: A method for designing human-centred learning analytics systems
Alfredo, R., Echeverria, V., Jin, Y., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R.
Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK ’24), 24–34. ACM
Human-AI collaboration in thematic analysis using ChatGPT: A user study and design recommendations
Yan, L., Echeverria, V., Fernandez-Nieto, G. M., Jin, Y., Swiecki, Z., Zhao, L., Gašević, D., & Martinez-Maldonado, R.
Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, Article 191, 1–7. ACM

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2023
Analytics of self-regulated learning scaffolding: Effects on learning processes
Li, T., Fan, Y., Tan, Y., Wang, Y., Singh, S., Li, X., Raković, M., van der Graaf, J., Lim, L., Yang, B., Molenaar, I., Bannert, M., Moore, J., Swiecki, Z., Tsai, Y. S., Shaffer, D. W., & Gašević, D.
Frontiers in Psychology, 14, 1206696
Artificial intelligence techniques for supporting face-to-face and online collaborative learning
Martinez-Maldonado, R., van Leeuwen, A., & Swiecki, Z.
In B. du Boulay, A. Mitrovic, & K. Yacef (Eds.), Handbook of Artificial Intelligence in Education (pp. 422–439). Edward Elgar
Do learners appreciate adaptivity? An epistemic network analysis of how learners perceive adaptive scaffolding
Li, T., Lin, J., Iqbal, S., Swiecki, Z., Tsai, Y., Fan, Y., & Gašević, D.
Advances in Quantitative Ethnography (ICQE 2023), 3–17. Springer
Automated code discovery via graph neural networks and generative AI
Fang, Z.†, Yang, Y., & Swiecki, Z.
Advances in Quantitative Ethnography (ICQE 2023), 438–454. Springer
Characterising individual-level collaborative learning behaviours using ordered network analysis and wearable sensors
Yan, L., Tan, Y., Swiecki, Z., Gašević, D., Shaffer, D. W., Zhao, L., Li, X., & Martinez-Maldonado, R.
Advances in Quantitative Ethnography (ICQE 2023), 66–80. Springer
“That student should be a lion tamer!” StressViz: Designing a stress analytics dashboard for teachers
Alfredo, R. D., Nie, L., Kennedy, P., Power, T., Hayes, C., Chen, H., McGregor, C., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R.
Proceedings of the 13th International Learning Analytics and Knowledge Conference (LAK ’23), 57–67. ACM
METS: Multimodal learning analytics of embodied teamwork learning
Zhao, L., Swiecki, Z., Gašević, D., Yan, L., Dix, S., Jaggard, H., Wotherspoon, R., Osborne, A., Li, X., Alfredo, R. D., & Martinez-Maldonado, R.
Proceedings of the 13th International Learning Analytics and Knowledge Conference (LAK ’23), 186–196. ACM
2022
Assessment in the age of artificial intelligence
Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., Selwyn, N., & Gašević, D.
Computers and Education: Artificial Intelligence, 3, 100075
The role of data simulation in quantitative ethnography
Swiecki, Z., & Eagan, B.
Advances in Quantitative Ethnography (ICQE 2022), 87–100. Springer

Best Paper finalist

Popularity prediction in MOOCs: A case study on Udemy
Li, L., Swiecki, Z., Gašević, D., & Chen, G.
Artificial Intelligence in Education (AIED 2022), 607–613. LNCS vol. 13355. Springer
Simulating collaborative discourse data
Swiecki, Z., Marquart, C., & Eagan, B.
Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning (CSCL 2022), 83–90. ISLS
Uncovering associations between cognitive presence and speech acts: A network-based approach
Iqbal, S., Swiecki, Z., Joksimovic, S., Mello, R. F., Aljohani, N. R., Hassan, S.-U., & Gašević, D.
Proceedings of the 12th International Learning Analytics and Knowledge Conference (LAK ’22), 315–325. ACM
The expected value test: A new statistical warrant for theoretical saturation
Swiecki, Z.
Advances in Quantitative Ethnography (ICQE 2021), 49–65. CCIS vol. 1522. Springer

Best Paper Award

2021
Measuring the impact of interdependence on individuals during collaborative problem-solving
Swiecki, Z.
Journal of Learning Analytics, 8(1), 75–94
What do you mean by collaboration analytics? A conceptual model
Martinez-Maldonado, R., Fernandez-Nieto, G., Echeverria, V., Swiecki, Z., Buckingham Shum, S., & Gašević, D.
Journal of Learning Analytics, 8(1), 126–153
The mathematical foundations of epistemic network analysis
Bowman, D., Swiecki, Z., Cai, Z., Wang, Y., Eagan, B., Linderoth, J., & Shaffer, D. W.
Advances in Quantitative Ethnography (ICQE 2020), 91–105. Springer
Directed epistemic network analysis
Fogel, A., Swiecki, Z., Marquart, C., Cai, Z., Wang, Y., Brohinsky, J., Siebert-Evenstone, A., Eagan, B., Ruis, A. R., & Shaffer, D. W.
Advances in Quantitative Ethnography (ICQE 2020), 122–136. Springer
Simplification of epistemic networks using parsimonious removal with interpretive alignment
Wang, Y., Swiecki, Z., Ruis, A. R., & Shaffer, D. W.
Advances in Quantitative Ethnography (ICQE 2020), 137–151. Springer
Exploring the effects of segmentation on semi-structured interview data with epistemic network analysis
Zörgő, S., Swiecki, Z., & Ruis, A. R.
Advances in Quantitative Ethnography (ICQE 2020), 78–90. Springer

Best Paper Award

2020
Assessing individual contributions to collaborative problem solving: A network analysis approach
Swiecki, Z., Ruis, A. R., Farrell, C., & Shaffer, D. W.
Computers in Human Behavior, 104, 105876

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iSENS: An integrated approach to combining epistemic and social network analyses
Swiecki, Z., & Shaffer, D. W.
Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 305–313. ACM

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Modeling interdependence in collaborative problem-solving
Swiecki, Z.
Doctoral dissertation, University of Wisconsin–Madison
2019
Understanding when students are active-in-thinking through modeling-in-context
Swiecki, Z., Ruis, A. R., Gautam, D., Ruis, V., & Shaffer, D. W.
British Journal of Educational Technology, 50(5), 2346–2364
Designing an interface for sharing quantitative ethnographic research data
Swiecki, Z., Marquart, C., Sachar, A., Hinojosa, C., Ruis, A. R., & Shaffer, D. W.
Advances in Quantitative Ethnography (ICQE 2019), 334–341. CCIS vol. 1112. Springer
The binary replicate test: Determining the sensitivity of CSCL models to coding error
Eagan, B., Swiecki, Z., Farrell, C., & Shaffer, D. W.
Proceedings of the 13th International Conference on Computer-Supported Collaborative Learning (CSCL 2019), Vol. 2, 328–336. ISLS
Does order matter? Investigating sequential and cotemporal models of collaboration
Swiecki, Z., Lian, Z., Ruis, A. R., & Shaffer, D. W.
Proceedings of the 13th International Conference on Computer-Supported Collaborative Learning (CSCL 2019), Vol. 1, 112–120. ISLS

Naomi Miyake Best Student Paper finalist

Modeling and visualizing team performance using epistemic network analysis
Swiecki, Z., Ruis, A. R., & Shaffer, D. W.
Proceedings of the 7th Annual GIFT Users Symposium (GIFTSym7), 148–157
2018
Behind the curtain: An epistemic design process for democratic media education simulations
Stoddard, J., Swiecki, Z., & Shaffer, D. W.
In C. Wright-Maley (Ed.), More Like Life Itself: Simulations as Powerful and Purposeful Social Studies (pp. 21–39). Information Age Publishing
Toward a taxonomy of team performance visualization tools
Swiecki, Z., & Shaffer, D. W.
Proceedings of the 13th International Conference of the Learning Sciences (ICLS 2018), Vol. 1, 144–151. ISLS
Supporting teachers’ intervention in students’ virtual collaboration using a network based model
Herder, T., Swiecki, Z., Fougt, S. S., Tamborg, A. L., Allsopp, B. B., Shaffer, D. W., & Misfeldt, M.
Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK ’18), 21–25. SoLAR
Epistemic Network Analysis (web application, v1.7.0)
Marquart, C. L., Hinojosa, C., Swiecki, Z., Eagan, B., & Shaffer, D. W.
Web application

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rENA: Epistemic Network Analysis (v0.1.5)
Marquart, C., Swiecki, Z., Collier, W., Eagan, B., Woodward, R., & Shaffer, D. W.
R package, CRAN

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ncodeR: Techniques for Automated Classifiers (v0.1.2)
Marquart, C., Swiecki, Z., Eagan, B., & Shaffer, D. W.
R package, CRAN

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2017
A grounded qualitative analysis of the effect of a focus group on design process in a virtual internship
Markovetz, M. R., Sullivan, S., Clark, R. M., Swiecki, Z., Arastoopour Irgens, G., Shaffer, D. W., Chesler, N. C., & Bodnar, C. A.
International Journal of Engineering Education, 33(6), 1834–1841
In search of conversational grain size: Modeling semantic structure using moving stanza windows
Siebert-Evenstone, A. L., Arastoopour Irgens, G., Collier, W., Swiecki, Z., Ruis, A. R., & Shaffer, D. W.
Journal of Learning Analytics, 4(3), 123–139
Dependency-centered design as an approach to pedagogical authoring
Swiecki, Z., Misfeldt, M., Stoddard, J., & Shaffer, D. W.
In Y. Baek (Ed.), Game-Based Learning: Theory, Strategies and Performance Outcomes. NOVA
Modeling classifiers for virtual internships without participant data
Gautam, D., Swiecki, Z., Shaffer, D. W., Graesser, A. C., & Rus, V.
Proceedings of the 10th International Conference on Educational Data Mining (EDM 2017), 278–283
2016
Influence of end customer exposure on product design within an epistemic game environment
Markovetz, M. R., Clark, R. M., Swiecki, Z., Arastoopour, G., Chesler, N. C., Shaffer, D. W., & Bodnar, C. A.
Advances in Engineering Education, 6(2), 1–22
Teaching and assessing engineering design thinking with virtual internships and epistemic network analysis
Arastoopour, G., Shaffer, D. W., Swiecki, Z., Ruis, A. R., & Chesler, N. C.
International Journal of Engineering Education, 32(3B), 1492–1501
Assessing student-generated design justifications in virtual engineering internships
Rus, V., Gautam, D., Swiecki, Z., Shaffer, D. W., & Graesser, A.
Proceedings of the 9th International Conference on Educational Data Mining (EDM 2016), 496–501
In search of conversational grain size: Modeling semantic structure using moving stanza windows
Siebert-Evenstone, A. L., Arastoopour, G., Collier, W., Swiecki, Z., Ruis, A. R., & Shaffer, D. W.
Proceedings of the International Conference of the Learning Sciences (ICLS 2016), Vol. 2, 631–638. ISLS
2015
A novel paradigm for engineering education: Virtual internships with individualized mentoring and assessment of engineering thinking
Chesler, N. C., Ruis, A. R., Collier, W., Swiecki, Z., Arastoopour, G., & Shaffer, D. W.
Journal of Biomechanical Engineering, 137(2), 024701
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