Human and artificial intelligence collaboration for socially shared regulation in learning

120 indexed citations

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This paper, published in 2023, received 120 indexed citations. Written by Sanna Järvelä, Andy Nguyen and Allyson F. Hadwin covering the research area of Computer Science Applications, Developmental and Educational Psychology and Education. It is primarily cited by scholars working on Computer Science Applications (64 citations), Artificial Intelligence (39 citations) and Developmental and Educational Psychology (37 citations). Published in British Journal of Educational Technology.

Countries where authors are citing Human and artificial intelligence collaboration for socially shared regulation in learning

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This map shows the geographic impact of Human and artificial intelligence collaboration for socially shared regulation in learning. 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 Human and artificial intelligence collaboration for socially shared regulation in learning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Human and artificial intelligence collaboration for socially shared regulation in learning more than expected).

Fields of papers citing Human and artificial intelligence collaboration for socially shared regulation in learning

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Human and artificial intelligence collaboration for socially shared regulation in learning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Human and artificial intelligence collaboration for socially shared regulation in learning.

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.

This paper is also available at doi.org/10.1111/bjet.13325.

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