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.
A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023)
202478 citationsAditya Johri et al.SHILAP Revista de lepidopterologíaprofile →
Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines
202558 citationsNora McDonald, Aditya Johri et al.SHILAP Revista de lepidopterologíaprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Aditya Johri'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 Aditya Johri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Johri more than expected).
This network shows the impact of papers produced by Aditya Johri. 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 Aditya Johri. The network helps show where Aditya Johri may publish in the future.
Co-authorship network of co-authors of Aditya Johri
This figure shows the co-authorship network connecting the top 25 collaborators of Aditya Johri.
A scholar is included among the top collaborators of Aditya Johri 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 Aditya Johri. Aditya Johri is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
McDonald, Nora, et al.. (2025). Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines. SHILAP Revista de lepidopterología. 3. 100121–100121.58 indexed citations breakdown →
Johri, Aditya, Seungwon Yang, Mihaela Vorvoreanu, & Krishna Madhavan. (2016). Perceptions and Practices of Data Sharing in Engineering Education.. AEE Journal. 5(2).8 indexed citations
14.
Domeniconi, Carlotta, et al.. (2016). Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCs.. Educational Data Mining. 376–381.6 indexed citations
15.
Johri, Aditya, et al.. (2014). U.S. Graduate engineering students’ perceptions of and strategies towards acquiring external funding for their education. International journal of engineering education. 30(5). 1136–1144.1 indexed citations
16.
Johri, Aditya, et al.. (2013). Visualizing and Analyzing Productive Structures and Patterns in Online Communities Using Multilevel Social Network Analysis.. Computer Supported Collaborative Learning. 173–176.1 indexed citations
17.
Johri, Aditya & Vinod Lohani. (2011). Framework for improving engineering representational literacy by using pen-based computing. International journal of engineering education. 27(5). 958–967.19 indexed citations
18.
Newstetter, Wendy, Aditya Johri, & Volker Wulf. (2008). Laboratory learning: industry and university research as site for situated and distributed cognition. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 290–297.1 indexed citations
19.
Johri, Aditya & Vinod Lohani. (2008). Analysis of tablet PC based learning experiences in engineering classes. International Conference of Learning Sciences. 51–53.
20.
Johri, Aditya & Vinod Lohani. (2008). Creating a participatory learning environment in large lecture classes using pen-based computing. International Conference of Learning Sciences. 398–405.3 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.