Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Assessment in the age of artificial intelligence
2022171 citationsZachari Swiecki, Hassan Khosravi et al.Computers and Education Artificial Intelligenceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Sandra Milligan
Since
Specialization
Citations
This map shows the geographic impact of Sandra Milligan'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 Sandra Milligan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandra Milligan more than expected).
This network shows the impact of papers produced by Sandra Milligan. 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 Sandra Milligan. The network helps show where Sandra Milligan may publish in the future.
Co-authorship network of co-authors of Sandra Milligan
This figure shows the co-authorship network connecting the top 25 collaborators of Sandra Milligan.
A scholar is included among the top collaborators of Sandra Milligan based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Sandra Milligan. Sandra Milligan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Swiecki, Zachari, Hassan Khosravi, Guanliang Chen, et al.. (2022). Assessment in the age of artificial intelligence. Computers and Education Artificial Intelligence. 3. 100075–100075.171 indexed citations breakdown →
Corrin, Linda, et al.. (2018). Evaluating systems and tools that link learning analytics and learning design. Swinburne Research Bank (Swinburne University of Technology).1 indexed citations
Milligan, Sandra, et al.. (1993). A report of an evaluation of the Women in Leadership Program Edith Cowan University. Australasian Journal of Paramedicine.2 indexed citations
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.