Rolf Biehler

2.1k citations
101 papers · 708 indexed · h-index 12

Impact in

Papers in

    • Mathematics Education and Teaching Techniques 33
    • Education Methods and Technologies 26
    • Innovations in Educational Methods 6
    • Statistics Education and Methodologies 43

Rolf Biehler

93 papers receiving 616 citations

Peers

Rolf Biehler
Comparison fields: 5 of 84
  • Statistics and Probability 337
  • Theoretical Computer Science 19
  • Education 431
  • Computer Science Applications 74
  • Modeling and Simulation 59
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Helen Chick Australia
Portia C. Elliott United States
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Morten Blomhøj Denmark
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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 101 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002140
2 200452
3 202146
4 199742
5 201830
6 202125
7 200124
8 201519
9 202018
10 201816
11 202015
12 202212
13 202011
14
A MODEL FOR TEACHER KNOWLEDGE AS A BASIS FOR ONLINE COURSES FOR PROFESSIONAL DEVELOPMENT OF STATISTICS TEACHERS
201011
15 201710
16 201510
17
PERSPECTIVES FOR AN INTERDISCIPLINARY DATA SCIENCE CURRICULUM IN GERMAN SECONDARY SCHOOLS
20178
18 20218
19 20218
20 20207

About Rolf Biehler

Rolf Biehler is a scholar working on Education, Statistics and Probability, Artificial Intelligence, Sociology and Political Science and Language and Linguistics, having authored 101 papers that have together received 708 indexed citations. Recurring topics across this work include Statistics Education and Methodologies (43 papers), Mathematics Education and Teaching Techniques (33 papers), Education Methods and Technologies (26 papers), Data Analysis with R (12 papers), Sociology and Education Studies (8 papers), Linguistic Education and Pedagogy (8 papers), Mathematics Education and Programs (6 papers) and Innovations in Educational Methods (6 papers). The work is most often cited by research in Statistics and Probability (337 citations), Theoretical Computer Science (19 citations), Education (431 citations), Computer Science Applications (74 citations) and Modeling and Simulation (59 citations). Rolf Biehler has collaborated with scholars based in Germany, France and United Kingdom. Frequent co-authors include Rudolf Sträßer, Roland W. Scholz, Cliff Konold, Arthur Bakker, Ghislaine Gueudet, Birgit Pepin, Reinhard Hochmuth, Carsten Schulte, Niclas Schaper and Hans-Georg Rück. Their work appears in journals such as ZDM, International Journal of Research in Undergraduate Mathematics Education, Statistics Education Research Journal, International Statistical Review 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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