Daniel Frischemeier
Impact in
- Statistics and Probability top 5%
- Statistics Education and Methodologies
- Computer Science Applications top 10%
- Online Learning and Analytics
- Teaching and Learning Programming
Papers in
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- Statistics Education and Methodologies 29
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- Data Analysis with R 11
- Co-authors
- Rolf Biehler (18 shared papers)Carsten Schulte (8 shared papers)Aisling Leavy (3 shared papers)Joachim Engel (3 shared papers)Angela Schwering (1 shared paper)Laura Martignon (1 shared paper)Christoph Selter (2 shared papers)Sibel Kazak (1 shared paper)
In The Last Decade
Daniel Frischemeier
32 papers receiving 145 citations
Peers
Comparison fields: 5 of 33
- Statistics and Probability 110
- Computer Science Applications 26
- Information Systems and Management 10
- Management Information Systems 11
- Education 35
Countries citing papers authored by Daniel Frischemeier
This map shows the geographic impact of Daniel Frischemeier'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 Daniel Frischemeier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Frischemeier more than expected).
Fields of papers citing papers by Daniel Frischemeier
This network shows the impact of papers produced by Daniel Frischemeier. 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 Daniel Frischemeier. The network helps show where Daniel Frischemeier may publish in the future.
Co-authors
The 10 scholars most cited alongside Daniel Frischemeier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 30 | |
| 2 | 2018 | 16 | |
| 3 | 2020 | 10 | |
| 4 | 2017 | 10 | |
| 5 | 2021 | 8 | |
| 6 | 2021 | 8 | |
| 7 | 2019 | 7 | |
| 8 | 2019 | 7 | |
| 9 | 2020 | 5 | |
| 10 | 2021 | 4 | |
| 11 | 2016 | 4 | |
| 12 | 2020 | 3 | |
| 13 | 2016 | 3 | |
| 14 | 2018 | 3 | |
| 15 | 2012 | 3 | |
| 16 | 2018 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2022 | 2 | |
| 20 | 2022 | 2 |
About Daniel Frischemeier
Daniel Frischemeier is a scholar working on Statistics and Probability, Artificial Intelligence, Education, Information Systems and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 147 indexed citations. Recurring topics across this work include Statistics Education and Methodologies (29 papers), Data Analysis with R (11 papers), Mathematics Education and Teaching Techniques (5 papers), Educational Assessment and Pedagogy (3 papers), Data Visualization and Analytics (2 papers), Sports Analytics and Performance (2 papers), Education Methods and Technologies (1 paper) and Educational Research and Pedagogy (1 paper). The work is most often cited by research in Statistics and Probability (110 citations), Computer Science Applications (26 citations), Information Systems and Management (10 citations), Management Information Systems (11 citations) and Education (35 citations). Daniel Frischemeier has collaborated with scholars based in Germany, Cyprus and Türkiye. Frequent co-authors include Rolf Biehler, Carsten Schulte, Aisling Leavy, Joachim Engel, Angela Schwering, Laura Martignon, Christoph Selter, Sibel Kazak, Efi Paparistodemou and Μaria Meletiou-Mavrotheris. Their work appears in journals such as Statistics Education Research Journal, Mathematics Education Research Journal, ZDM, Journal of Mathematics Teacher Education and Teaching Statistics.
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.