Michael Liut
Impact in
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- Teaching and Learning Programming
- Online Learning and Analytics
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Online Learning and Analytics 15
- Teaching and Learning Programming 14
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- Topic Modeling 6
- Intelligent Tutoring Systems and Adaptive Learning 5
- Co-authors
- Andrew Petersen (19 shared papers)Oscar Karnalim (3 shared papers)Joseph Jay Williams (14 shared papers)Ali Raza (1 shared paper)Anna Ly (5 shared papers)Anastasia Kuzminykh (3 shared papers)Quintin Cutts (2 shared papers)Jack Parkinson (3 shared papers)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (1 paper)Complex & Intelligent Systems (1 paper)ACM SIGMOD Record (1 paper)ACM Inroads (1 paper)Murdoch Research Repository (Murdoch University) (1 paper)
- Partner nations
- CanadaUnited StatesNetherlands
In The Last Decade
Michael Liut
38 papers receiving 258 citations
Peers
Comparison fields: 5 of 59
- Computer Science Applications 69
- Health Informatics 15
- Developmental and Educational Psychology 34
- Safety Research 22
- Software 10
Countries citing papers authored by Michael Liut
This map shows the geographic impact of Michael Liut's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Liut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Liut more than expected).
Fields of papers citing papers by Michael Liut
This network shows the impact of papers produced by Michael Liut. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Liut. The network helps show where Michael Liut may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Liut, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 31 | |
| 2 | 2024 | 25 | |
| 3 | 2021 | 23 | |
| 4 | 2024 | 22 | |
| 5 | 2024 | 16 | |
| 6 | 2021 | 15 | |
| 7 | 2020 | 15 | |
| 8 | 2021 | 14 | |
| 9 | 2024 | 12 | |
| 10 | 2023 | 10 | |
| 11 | 2022 | 10 | |
| 12 | 2024 | 8 | |
| 13 | 2022 | 6 | |
| 14 | 2024 | 6 | |
| 15 | 2021 | 5 | |
| 16 | 2024 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2021 | 4 | |
| 19 | 2021 | 4 | |
| 20 | 2025 | 3 |
About Michael Liut
Michael Liut is a scholar working on Computer Science Applications, Artificial Intelligence, Developmental and Educational Psychology, Information Systems and Information Systems and Management, having authored 50 papers that have together received 264 indexed citations. Recurring topics across this work include Online Learning and Analytics (15 papers), Teaching and Learning Programming (14 papers), Innovative Teaching and Learning Methods (10 papers), Topic Modeling (6 papers), Educational Games and Gamification (5 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers), Scientific Computing and Data Management (4 papers) and Perfectionism, Procrastination, Anxiety Studies (4 papers). The work is most often cited by research in Computer Science Applications (69 citations), Health Informatics (15 citations), Developmental and Educational Psychology (34 citations), Safety Research (22 citations) and Software (10 citations). Michael Liut has collaborated with scholars based in Canada, United States and Netherlands. Frequent co-authors include Andrew Petersen, Oscar Karnalim, Joseph Jay Williams, Ali Raza, Anna Ly, Anastasia Kuzminykh, Quintin Cutts, Jack Parkinson, Tovi Grossman and Bogdan Simion. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Complex & Intelligent Systems, ACM SIGMOD Record, ACM Inroads and Murdoch Research Repository (Murdoch University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.