This map shows the geographic impact of Yoav Bergner'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 Yoav Bergner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yoav Bergner more than expected).
This network shows the impact of papers produced by Yoav Bergner. 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 Yoav Bergner. The network helps show where Yoav Bergner may publish in the future.
Co-authorship network of co-authors of Yoav Bergner
This figure shows the co-authorship network connecting the top 25 collaborators of Yoav Bergner.
A scholar is included among the top collaborators of Yoav Bergner 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 Yoav Bergner. Yoav Bergner is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Liu, Zhongxiu, Rebecca Brown, Collin Lynch, et al.. (2016). MOOC learner behaviors by country and culture; An exploratory analysis. Educational Data Mining. 127–134.36 indexed citations
Brown, Rebecca, Collin Lynch, Michael Eagle, et al.. (2015). Good Communities and Bad Communities: Does Membership Affect Performance?. Educational Data Mining. 612–613.5 indexed citations
11.
Bergner, Yoav, Deirdre Kerr, & David E. Pritchard. (2015). Methodological Challenges in the Analysis of MOOC Data for Exploring the Relationship between Discussion Forum Views and Learning Outcomes.. Educational Data Mining. 234–241.24 indexed citations
12.
Crossley, Scott A., Danielle S. McNamara, Ryan S. Baker, et al.. (2015). Language to Completion: Success in an Educational Data Mining Massive Open Online Class. Educational Data Mining. 388–391.29 indexed citations
13.
Brown, Rebecca, Collin Lynch, Yuan Wang, et al.. (2015). Communities of performance & communities of preference. Educational Data Mining. 1446.12 indexed citations
14.
Seaton, Daniel, Yoav Bergner, Isaac L. Chuang, Piotr Mitros, & David E. Pritchard. (2014). Who does what in a massive open online course. DSpace@MIT (Massachusetts Institute of Technology).3 indexed citations
15.
Bergner, Yoav, Shu Zhan, & Alina A. von Davier. (2014). Visualization and Confirmatory Clustering of Sequence Data from a Simulation-Based Assessment Task. Educational Data Mining. 177–184.20 indexed citations
Seaton, Daniel, Yoav Bergner, & David E. Pritchard. (2013). Exploring the relationship between course structure and etext usage in blended and open online courses.. Educational Data Mining. 350–351.4 indexed citations
18.
Pardos, Zachary A., Yoav Bergner, Daniel Seaton, & David E. Pritchard. (2013). Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX. Educational Data Mining. 137–144.51 indexed citations
19.
Bergner, Yoav, et al.. (2012). Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory. Educational Data Mining. 95–102.66 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.