Rolf Biehler

2.1k citations
164 papers · 1.5k · h-index 17

Impact in

Papers in

    • Education Methods and Technologies 65
    • Mathematics Education and Teaching Techniques 60
    • Vocational Education and Training 10
    • Statistics Education and Methodologies 58

Rolf Biehler

153 papers receiving 1.3k citations

Peers

Rolf Biehler
Comparison fields: 5 of 89
  • Statistics and Probability 800
  • Theoretical Computer Science 63
  • Education 922
  • Modeling and Simulation 93
  • Computer Science Applications 112
Replace Rita Borromeo Ferri with:
Rita Borromeo Ferri Germany
Lianghuo Fan United Kingdom
Morten Blomhøj Denmark
Helen Chick Australia
J. Michael Shaughnessy United States
Ken Clements Australia
Jean-Baptiste Lagrange France
Gloria Stillman Australia
Günter Törner Germany
Gilbert Greefrath Germany
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Citations per field
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Citations per year

Countries citing papers authored by Rolf Biehler

Since Specialization
Citations

This map shows the geographic impact of Rolf Biehler'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 Rolf Biehler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rolf Biehler more than expected).

Fields of papers citing papers by Rolf Biehler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rolf Biehler. 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 Rolf Biehler. The network helps show where Rolf Biehler may publish in the future.

Co-authors

The 25 scholars most cited alongside Rolf Biehler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rolf Biehler Line = papers co-authored together Rolf Biehler links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 164 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002204
2 2011132
3 201292
4 199759
5 200458
6 202157
7 199145
8 199344
9 200141
10 201740
11 201839
12 202134
13 201526
14 200523
15 202022
16 201818
17 202016
18 201516
19 202015
20 202214

About Rolf Biehler

Rolf Biehler is a scholar working on Education, Statistics and Probability, Sociology and Political Science, Artificial Intelligence and Language and Linguistics, having authored 164 papers that have together received 1.5k indexed citations. Recurring topics across this work include Education Methods and Technologies (65 papers), Mathematics Education and Teaching Techniques (60 papers), Statistics Education and Methodologies (58 papers), Sociology and Education Studies (18 papers), Linguistic Education and Pedagogy (15 papers), Data Analysis with R (15 papers), Vocational Education and Training (10 papers) and History and Theory of Mathematics (9 papers). The work is most often cited by research in Statistics and Probability (800 citations), Theoretical Computer Science (63 citations), Education (922 citations), Modeling and Simulation (93 citations) and Computer Science Applications (112 citations). Rolf Biehler has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Gail Burrill, Rudolf Sträßer, Roland W. Scholz, Daniel Frischemeier, Arthur Bakker, Reinhard Hochmuth, Dani Ben‐Zvi, Katie Makar, Ghislaine Gueudet and Birgit Pepin. Their work appears in journals such as ZDM, International Journal of Research in Undergraduate Mathematics Education, International Statistical Review, Statistics Education Research Journal and Journal for Research in Mathematics Education.

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.

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