Open University Learning Analytics dataset
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- Scientific Data
In The Last Decade
doi.org/10.1038/sdata.2017.171 →Countries where authors are citing Open University Learning Analytics dataset
This map shows the geographic impact of Open University Learning Analytics dataset. 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 Open University Learning Analytics dataset with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Open University Learning Analytics dataset more than expected).
Fields of papers citing Open University Learning Analytics dataset
This network shows the impact of Open University Learning Analytics dataset. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Open University Learning Analytics dataset.
About Open University Learning Analytics dataset
This paper, published in 2017, received 258 indexed citations . Written by Jakub Kužílek, Martin Hlosta and Zdeněk Zdráhal covering the research area of Computer Science Applications and Artificial Intelligence. It is primarily cited by scholars working on Computer Science Applications (208 citations), Artificial Intelligence (127 citations) and Education (56 citations). Published in Scientific Data.
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/10.1038/sdata.2017.171.