
Brings real-world examples to learning.
Brings real-world insights to the classroom.
Always approachable and supportive.
Always prepared and organized for students.
Inspires a passion for knowledge and growth.
Makes learning feel effortless and fun.
Zachari Swiecki is a Lecturer of Learning Analytics in the Faculty of Information Technology at Monash University, where he also holds the position of Senior Research Fellow in the Department of Data Science & AI. He earned his Ph.D. in Educational Psychology from the University of Wisconsin-Madison in 2020 and his Master's degree in the same field from the same institution in 2015, during which time he was a member of the Epistemic Analytics lab. Swiecki graduated summa cum laude with a Bachelor's degree in Mathematics and Physics from the University of Alabama in 2013. His academic journey has positioned him at the forefront of applying data science to educational contexts, with prior involvement in the development of innovative educational simulations, automated assessment techniques, and simulation authoring tools for educators.
Swiecki's research specializations lie in learning analytics, with a particular emphasis on collaborative learning settings. He has played a central role in the development and dissemination of Quantitative Ethnography, an emerging methodology that integrates qualitative analysis, statistics, and data science into a unified framework. His current work includes modeling collaborative processes in domains such as engineering design, medicine, and the military, as well as designing real-time systems for monitoring teams. Recent projects focus on understanding how students work with generative artificial intelligence in writing tasks. Key publications include 'Community of inquiry in motion: Modeling inquiry dynamics with movement analysis (MOVA)' (2026, Computers and Education), 'Towards reliable generative AI-driven scaffolding: Reducing hallucinations and enhancing quality in self-regulated learning support' (2026, Computers and Education), 'Analytics of self-regulated learning strategies and scaffolding: Associations with learning performance' (2025, Computers and Education: Artificial Intelligence), 'Asking generative artificial intelligence the right questions improves writing performance' (2025, Computers and Education: Artificial Intelligence), and 'Assessment after Artificial Intelligence: the research we should be doing' (2025, Journal of University Teaching and Learning Practice). With 77 research outputs documented on the Monash research repository, Swiecki contributes significantly to advancing quantitative methods in educational psychology and learning sciences. He was a finalist for the Naomi Miyake Best Student Paper Award at the 13th International Conference on Computer-Supported Collaborative Learning (CSCL 2019) for 'Does order matter? Investigating sequential and cotemporal models of collaboration'.