Tobias Kohn

748 citations
21 papers · 317 indexed · 1 hit paper · h-index 7

Tobias Kohn

19 papers receiving 308 citations

Hit Papers

The Robots Are Here: Navigating the Generative AI Revolut...151202320262024202550100150

Peers

Tobias Kohn
Comparison fields: 5 of 49
  • Computer Science Applications 212
  • Health Informatics 34
  • Software 38
  • Developmental and Educational Psychology 52
  • Information Systems 73
Replace Viraj Kumar with:
Viraj Kumar India
Ibrahim Albluwi United States
Diana Cukierman Canada
Aidan Mooney Ireland
Sruti Srinivasa Ragavan United States
Kelly Rivers United States
Amali Weerasinghe Australia
Adalbert Gerald Soosai Raj United States
Veronica Cateté United States
Ian Drosos United States
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Citations per field
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Citations per year

Countries citing papers authored by Tobias Kohn

Since Specialization
Citations

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

Fields of papers citing papers by Tobias Kohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Tobias Kohn, 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 Tobias Kohn Line = papers co-authored together Tobias Kohn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20252
3 20243
4 202316
5 202345
6
The Robots Are Here: Navigating the Generative AI Revolution in Computing Educationbreakdown →
2023151
7 20231
8 20204
9 20205
10
An Elementary Approach Towards Teaching Dynamic Programming
20190
11 201929
12 20192
13 20192
14
Einfach Informatik 7-9: Programmieren. Sekundarstufe I. Begleitband
20180
15
Algorithmic Thinking from the Start
20174
16 20171
17 201720
18 201611
19 20163
20 20156

About Tobias Kohn

Tobias Kohn is a scholar working on Computer Science Applications, Software and Hardware and Architecture, having authored 21 papers that have together received 317 indexed citations. Recurring topics across this work include Teaching and Learning Programming (14 papers), Online Learning and Analytics (4 papers), Parallel Computing and Optimization Techniques (4 papers), Software Testing and Debugging Techniques (3 papers), Educational Games and Gamification (2 papers), Software Engineering Research (2 papers), Evolutionary Algorithms and Applications (2 papers) and Music Technology and Sound Studies (2 papers). The work is most often cited by research in Computer Science Applications (212 citations), Health Informatics (34 citations) and Software (38 citations). Tobias Kohn has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Juho Leinonen, Natalie Kiesler, Jaromír Šavelka, Hieke Keuning, Brett A. Becker, Michelle Craig, Raymond Pettit, James Prather, Stephen MacNeil and Andrew Luxton-Reilly.

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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