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.
Self‐Explanations: How Students Study and Use Examples in Learning to Solve Problems
19891.2k citationsMichelene T.H., Miriam Bassok et al.Cognitive Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Matthew W. Lewis
Since
Specialization
Citations
This map shows the geographic impact of Matthew W. Lewis'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 Matthew W. Lewis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew W. Lewis more than expected).
Fields of papers citing papers by Matthew W. Lewis
This network shows the impact of papers produced by Matthew W. Lewis. 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 Matthew W. Lewis. The network helps show where Matthew W. Lewis may publish in the future.
Co-authorship network of co-authors of Matthew W. Lewis
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew W. Lewis.
A scholar is included among the top collaborators of Matthew W. Lewis 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 Matthew W. Lewis. Matthew W. Lewis is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Marler, Timothy, Susan G. Straus, John S. Hollywood, et al.. (2021). Effective Game-Based Training for Police Officer Decision-Making: Linking Missions, Skills, and Virtual Content.1 indexed citations
Steele, Jennifer, Matthew W. Lewis, Lucrecia Santibáñez, et al.. (2014). Competency-Based Education in Three Pilot Programs.
7.
Lewis, Matthew W., et al.. (2014). Equity in Competency Education: Realizing the Potential, Overcoming the Obstacles.8 indexed citations
8.
Lewis, Matthew W., Jennifer Steele, Lucrecia Santibáñez, et al.. (2013). Proficiency-Based Pathways in Three Pilot Programs: Examining Implementation and Outcomes.. Society for Research on Educational Effectiveness.2 indexed citations
9.
Lewis, Matthew W., et al.. (2009). The Prospects for Increasing the Reuse of Digital Training Content. Defense Technical Information Center (DTIC).2 indexed citations
Stasz, Cathy, et al.. (1990). Teaching and Learning Generic Skills for the Workplace.35 indexed citations
19.
T.H., Michelene, Miriam Bassok, Matthew W. Lewis, Peter Reimann, & Robert Glaser. (1989). Self‐Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science. 13(2). 145–182.1177 indexed citations breakdown →
20.
Lewis, Matthew W., Robert Milson, & John R. Anderson. (1987). The TEACHER'S APPRENTICE: Designing an intelligent authoring system for high school mathematics. Addison-Wesley Longman Publishing Co., Inc. eBooks. 269–301.9 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.