Ken Holstein

1.2k citations
6 papers · 663 · 1 hit paper · h-index 5

Impact in

Papers in

    • Adversarial Robustness in Machine Learning 1
    • Intelligent Tutoring Systems and Adaptive Learning 1
    • Digital Economy and Work Transformation 1
    • Qualitative Comparative Analysis Research 1
    • Criminal Justice and Corrections Analysis 1
    • Disaster Management and Resilience 1

Ken Holstein

6 papers receiving 617 citations

Ken Holstein's Hit Papers

Ethics of AI in Education: Towards a Community-Wide Framework 2021 · 588 citations
5880+1+3Years since publication100200300400500

Peers

Ken Holstein
Comparison fields: 5 of 72
  • Health Informatics 157
  • Computer Science Applications 258
  • Safety Research 191
  • Artificial Intelligence 223
  • Information Systems 99
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Belle Dang Finland
Ha Ngan Ngo New Zealand
Yvonne Hong New Zealand
Matthias Carl Laupichler Germany
Alexandra Aster Germany
Maya Bialik
Seongyune Choi South Korea
Tanya Nazaretsky Israel
Leo S. Lo United States
Abdülkadir Karadeniz Türkiye
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Citations per field
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Citations per year

Countries citing papers authored by Ken Holstein

Since Specialization
Citations

This map shows the geographic impact of Ken Holstein'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 Ken Holstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Holstein more than expected).

Fields of papers citing papers by Ken Holstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ken Holstein. 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 Ken Holstein. The network helps show where Ken Holstein may publish in the future.

Co-authors

The 19 scholars most cited alongside Ken Holstein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ken Holstein Line = papers co-authored together Ken Holstein links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown

About Ken Holstein

Ken Holstein is a scholar working on Artificial Intelligence, Sociology and Political Science, Computer Science Applications, General Health Professions and Safety Research, having authored 6 papers that have together received 663 indexed citations. Recurring topics across this work include Online Learning and Analytics (3 papers), Ethics and Social Impacts of AI (2 papers), Digital Economy and Work Transformation (1 paper), Qualitative Comparative Analysis Research (1 paper), Criminal Justice and Corrections Analysis (1 paper), Adversarial Robustness in Machine Learning (1 paper), Intelligent Tutoring Systems and Adaptive Learning (1 paper) and Disaster Management and Resilience (1 paper). The work is most often cited by research in Health Informatics (157 citations), Computer Science Applications (258 citations), Safety Research (191 citations), Artificial Intelligence (223 citations) and Information Systems (99 citations). Ken Holstein has collaborated with scholars based in United States, Spain and Philippines. Frequent co-authors include Kaśka Porayska‐Pomsta, Ma. Mercedes T. Rodrigo, Kenneth R. Koedinger, Mutlu Cukurova, W. Holmes, Olga C. Santos, Simon Buckingham Shum, Ig Ibert Bittencourt, Haiyi Zhu and Min Hun Lee. Their work appears in journals such as International Journal of Artificial Intelligence in Education, Edward Elgar Publishing eBooks, arXiv (Cornell University) and Proceedings of the AAAI/ACM Conference on AI Ethics and Society.

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.

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