This map shows the geographic impact of Collin Lynch'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 Collin Lynch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Collin Lynch more than expected).
This network shows the impact of papers produced by Collin Lynch. 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 Collin Lynch. The network helps show where Collin Lynch may publish in the future.
Co-authorship network of co-authors of Collin Lynch
This figure shows the co-authorship network connecting the top 25 collaborators of Collin Lynch.
A scholar is included among the top collaborators of Collin Lynch 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 Collin Lynch. Collin Lynch is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rutherford, Teomara, et al.. (2020). Investigating Relations between Self-Regulated Reading Behaviors and Science Question Difficulty.. Educational Data Mining.1 indexed citations
5.
Rutherford, Teomara, et al.. (2020). Associations Between Self-Regulated Learning Strategies and Science Assignment Score in a Digital Literacy Platform.. ICLS.1 indexed citations
6.
Lynch, Collin, et al.. (2019). What You Say is Relevant to How You Make Friends: Measuring the Effect of Content on Social Connection.. Educational Data Mining.1 indexed citations
7.
Lynch, Collin, et al.. (2019). Collaborative Talk Across Two Pair-Programming Configurations. Computer Supported Collaborative Learning. 1.10 indexed citations
8.
Lynch, Collin, et al.. (2017). Task and Timing: Separating Procedural and Tactical Knowledge in Student Models.. Educational Data Mining.2 indexed citations
9.
Wang, Jianxun, et al.. (2017). Towards Closing the Loop: Bridging Machine-Induced Pedagogical Policies to Learning Theories.. Educational Data Mining.13 indexed citations
10.
Lynch, Collin, et al.. (2017). Graph-based Educational Data Mining.. Educational Data Mining.3 indexed citations
11.
Crossley, Scott A., Tiffany Barnes, Collin Lynch, & Danielle S. McNamara. (2017). Linking Language to Math Success in a Blended Course.. Educational Data Mining.3 indexed citations
12.
Liu, Zhongxiu, et al.. (2017). The Antecedents of and Associations with Elective Replay in an Educational Game: Is Replay Worth It?.. Educational Data Mining.7 indexed citations
13.
Xue, Linting, Collin Lynch, & Min Chi. (2017). Mining Innovative Augmented Graph Grammars for Argument Diagrams through Novelty Selection.. Educational Data Mining.
14.
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
15.
Lynch, Collin, et al.. (2016). The Impact of Granularity on the Effectiveness of Students' Pedagogical Decisions.. Cognitive Science.1 indexed citations
16.
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
Lynch, Collin, Kevin D. Ashley, Niels Pinkwart, & Vincent Aleven. (2009). Computational Argument as a Diagnostic Tool: The role of reliability.. National Conference on Artificial Intelligence.2 indexed citations
19.
Lynch, Collin, Kevin D. Ashley, Niels Pinkwart, & Vincent Aleven. (2008). Argument graph classification with Genetic Programming and C4.5. Educational Data Mining. 137–146.8 indexed citations
20.
Pinkwart, Niels, Vincent Aleven, Kevin Ashley, & Collin Lynch. (2006). Schwachstellenermittlung und Rückmeldungsprinzipen in einem intelligenten Tutorensystem für juristische Argumentation. DeLFI. 75–86.3 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.