Teachers' trust in AI ‐powered educational technology and a professional development program to improve it

216 indexed citations

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This paper, published in 2022, received 216 indexed citations. Written by Tanya Nazaretsky, Moriah Ariely, Mutlu Cukurova and Giora Alexandron covering the research area of Computer Science Applications, Artificial Intelligence and Safety Research. It is primarily cited by scholars working on Computer Science Applications (105 citations), Artificial Intelligence (67 citations) and Education (47 citations). Published in British Journal of Educational Technology.

Countries where authors are citing Teachers' trust in AI ‐powered educational technology and a professional development program to improve it

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This map shows the geographic impact of Teachers' trust in AI ‐powered educational technology and a professional development program to improve it. 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 Teachers' trust in AI ‐powered educational technology and a professional development program to improve it with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teachers' trust in AI ‐powered educational technology and a professional development program to improve it more than expected).

Fields of papers citing Teachers' trust in AI ‐powered educational technology and a professional development program to improve it

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Teachers' trust in AI ‐powered educational technology and a professional development program to improve it. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Teachers' trust in AI ‐powered educational technology and a professional development program to improve it.

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.13232.

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