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.
Applying Best Practice Online Learning, Teaching, and Support to Intensive Online Environments: An Integrative Review
Countries citing papers authored by Jason M. Lodge
Since
Specialization
Citations
This map shows the geographic impact of Jason M. Lodge'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 Jason M. Lodge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason M. Lodge more than expected).
This network shows the impact of papers produced by Jason M. Lodge. 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 Jason M. Lodge. The network helps show where Jason M. Lodge may publish in the future.
Co-authorship network of co-authors of Jason M. Lodge
This figure shows the co-authorship network connecting the top 25 collaborators of Jason M. Lodge.
A scholar is included among the top collaborators of Jason M. Lodge 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 Jason M. Lodge. Jason M. Lodge 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 →
Thompson, Kate, Linda Corrin, Gwo‐Jen Hwang, & Jason M. Lodge. (2021). Trends in education technology in higher education. Australasian Journal of Educational Technology. 37(3). 1–4.7 indexed citations
Lodge, Jason M., Kate Thompson, Jared Cooney Horvath, Paula De Barba, & Marion Blumenstein. (2018). Learning analytics in the classroom. ASCILITE Publications. 559–561.2 indexed citations
Lodge, Jason M., et al.. (2016). The Search for Pedagogical Dynamism - Design Patterns and the Unselfconscious Process. Educational Technology & Society. 19(2). 274–285.8 indexed citations
17.
Loughlin, Wendy A., Mary Gregory, Glenn Harrison, & Jason M. Lodge. (2013). Beyond the First Year Experience in Science: Identifying the Need for a Supportive Learning and Teaching Environment for Second Year Science Students. International Journal of Innovation in Science and Mathematics Education. 21(4). 13–26.11 indexed citations
18.
Lodge, Jason M., et al.. (2012). Pigeon pecks and mouse clicks: Putting the learning back into learning analytics. Minerva Access (University of Melbourne). 2012(1).12 indexed citations
McMurray, Anne, et al.. (2008). Evidence-based Best Practice in Maintaining Skin Integrity. Griffith Research Online (Griffith University, Queensland, Australia). 16(2). 5–15.10 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.