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.
Understanding Tutor Learning: Knowledge-Building and Knowledge-Telling in Peer Tutors’ Explanations and Questions
2007430 citationsRod D. Roscoe, T. H. Micheleneprofile →
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 Rod D. Roscoe'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 Rod D. Roscoe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rod D. Roscoe more than expected).
This network shows the impact of papers produced by Rod D. Roscoe. 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 Rod D. Roscoe. The network helps show where Rod D. Roscoe may publish in the future.
Co-authorship network of co-authors of Rod D. Roscoe
This figure shows the co-authorship network connecting the top 25 collaborators of Rod D. Roscoe.
A scholar is included among the top collaborators of Rod D. Roscoe 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 Rod D. Roscoe. Rod D. Roscoe is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Stewart, Craig, et al.. (2019). Growth Mindset: Associations with Apprehension, Self-Perceived Competence, and Beliefs about Public Speaking. Basic communication course annual. 31(1). 44–69.7 indexed citations
11.
Allen, Laura K., Matthew E. Jacovina, Mihai Dascălu, et al.. (2016). {ENTER}ing the Time Series {SPACE}: Uncovering the Writing Process through Keystroke Analyses.. Grantee Submission. 22–29.4 indexed citations
12.
Jacovina, Matthew E., Erica L. Snow, Laura K. Allen, et al.. (2015). How to Visualize Success: Presenting Complex Data in a Writing Strategy Tutor.. Educational Data Mining. 594–595.4 indexed citations
13.
Roscoe, Rod D., et al.. (2014). Evaluating lesson design and implementation within the ICAP framework. International Conference of Learning Sciences. 2. 972–976.2 indexed citations
14.
Roscoe, Rod D., et al.. (2013). Developing Pedagogically-Guided Algorithms for Intelligent Writing Feedback.. Grantee Submission. 8(4). 362–381.1 indexed citations
15.
Crossley, Scott A., Rod D. Roscoe, & Danielle S. McNamara. (2013). Using Automatic Scoring Models to Detect Changes in Student Writing in an Intelligent Tutoring System. The Florida AI Research Society. 208–213.22 indexed citations
16.
Roscoe, Rod D., et al.. (2013). Educational Game Enjoyment, Perceptions, and Features in an Intelligent Writing Tutor.. The Florida AI Research Society. 515–520.7 indexed citations
17.
Roscoe, Rod D., et al.. (2012). Developing pedagogically-guided threshold algorithms for intelligent automated essay feedback. The Florida AI Research Society. 466–471.18 indexed citations
Biswas, Gautam, et al.. (2009). Promoting motivation and self-regulated learning skills through social interactions in agent-based learning environments. National Conference on Artificial Intelligence. 32–39.2 indexed citations
20.
Roscoe, Rod D. & Michelene T.H.. (2004). The Influence of the Tutee in Learning by Peer Tutoring. eScholarship (California Digital Library). 26(26).18 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.