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.
The viability of crowdsourcing for survey research
This map shows the geographic impact of Eric Wiebe'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 Eric Wiebe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Wiebe more than expected).
This network shows the impact of papers produced by Eric Wiebe. 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 Eric Wiebe. The network helps show where Eric Wiebe may publish in the future.
Co-authorship network of co-authors of Eric Wiebe
This figure shows the co-authorship network connecting the top 25 collaborators of Eric Wiebe.
A scholar is included among the top collaborators of Eric Wiebe 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 Eric Wiebe. Eric Wiebe is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Min, Wookhee, et al.. (2020). Enhancing Student Competency Models for Game-Based Learning with a Hybrid Stealth Assessment Framework.. Educational Data Mining.8 indexed citations
Min, Wookhee, et al.. (2018). Improving Stealth Assessment in Game-Based Learning with LSTM-Based Analytics. Educational Data Mining.19 indexed citations
8.
Min, Wookhee, Bradford Mott, Jonathan Rowe, et al.. (2017). Multimodal Goal Recognition in Open-World Digital Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(1). 80–86.20 indexed citations
9.
Wiggins, Joseph B., et al.. (2016). The Affective Impact of Tutor Questions: Predicting Frustration and Engagement.. Educational Data Mining. 247–254.11 indexed citations
Spires, Hiller A., Eric Wiebe, Carl A. Young, Karen Hollebrands, & John Lee. (2012). Towards a New Learning Ecology: Professional Development for Teachers in 1:1 Learning Environments. Contemporary issues in technology and teacher education. 12(2). 232–254.18 indexed citations
12.
Wiebe, Eric, et al.. (2012). Lessons Learned in Summer Camp: A Case Study of the Learning Paths of Three Campers. Scholar Commons (University of South Carolina). 16(3). 1–18.2 indexed citations
13.
Wiebe, Eric, et al.. (2011). Online Resource Utilization in a Hybrid Course in Engineering Graphics.. AEE Journal. 2(3).5 indexed citations
14.
Scheiter, Katharina, Eric Wiebe, & Jana Holšánová. (2009). Theoretical and Methodological Aspects of Learning with Visualizations. Lund University Publications (Lund University).3 indexed citations
Bertoline, Gary & Eric Wiebe. (2005). Fundamentals of Graphics Communication (McGraw-Hill Graphics).11 indexed citations
17.
Butler, Susan M. & Eric Wiebe. (2003). Designing a Technology-Based Science Lesson: Student Teachers Grapple with an Authentic Problem of Practice. The Journal of Technology and Teacher Education. 11(4). 463–481.4 indexed citations
18.
Wiebe, Eric, et al.. (2001). Scientific Visualisation: Linking Science and Technology Education through Graphic Communications. 6(1).1 indexed citations
19.
Clark, Aaron C. & Eric Wiebe. (2000). Scientific Visualization for Secondary and Post-Secondary Schools.. The Journal of Technology Studies. 26(1). 24–32.6 indexed citations
20.
Wiebe, Eric. (1991). Scientific Visualization: An Experimental Introductory Graphics Course for Science and Engineering Students.. 56(1). 39–44.7 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.