Natalie Kiesler

1.1k total citations · 1 hit paper
53 papers, 510 citations indexed

About

Natalie Kiesler is a scholar working on Computer Science Applications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Natalie Kiesler has authored 53 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computer Science Applications, 14 papers in Information Systems and 11 papers in Artificial Intelligence. Recurrent topics in Natalie Kiesler's work include Teaching and Learning Programming (23 papers), Online Learning and Analytics (16 papers) and Information Systems Education and Curriculum Development (9 papers). Natalie Kiesler is often cited by papers focused on Teaching and Learning Programming (23 papers), Online Learning and Analytics (16 papers) and Information Systems Education and Curriculum Development (9 papers). Natalie Kiesler collaborates with scholars based in Germany, United States and Netherlands. Natalie Kiesler's co-authors include Hieke Keuning, John Impagliazzo, Stephen MacNeil, Amruth N. Kumar, Bonnie MacKellar, Mihaela Sabin, Juho Leinonen, James Prather, Renée McCauley and Brett A. Becker and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Computer Assisted Learning and Journal of Computing in Higher Education.

In The Last Decade

Natalie Kiesler

46 papers receiving 499 citations

Hit Papers

The Robots Are Here: Navigating the Generative AI Revolut... 2023 2026 2024 2025 2023 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Natalie Kiesler Germany 11 298 158 133 74 70 53 510
Ibrahim Albluwi United States 6 424 1.4× 139 0.9× 94 0.7× 61 0.8× 127 1.8× 10 544
Valentin Kuleto Serbia 7 159 0.5× 153 1.0× 120 0.9× 76 1.0× 31 0.4× 19 497
Ralf Romeike Germany 14 348 1.2× 144 0.9× 59 0.4× 89 1.2× 158 2.3× 68 524
Lehong Shi United States 7 181 0.6× 80 0.5× 130 1.0× 133 1.8× 80 1.1× 13 403
Raymond Pettit United States 13 591 2.0× 269 1.7× 120 0.9× 59 0.8× 233 3.3× 22 771
Deborah Seehorn United States 7 528 1.8× 150 0.9× 149 1.1× 106 1.4× 173 2.5× 8 738
Keith Quille Ireland 13 358 1.2× 76 0.5× 61 0.5× 95 1.3× 118 1.7× 46 457
Dan Păun Romania 6 146 0.5× 100 0.6× 126 0.9× 70 0.9× 36 0.5× 13 463
Pedro Manuel Moreno-Marcos Spain 13 582 2.0× 135 0.9× 188 1.4× 194 2.6× 76 1.1× 32 727
Tianchong Wang Hong Kong 13 182 0.6× 177 1.1× 52 0.4× 231 3.1× 53 0.8× 38 538

Countries citing papers authored by Natalie Kiesler

Since Specialization
Citations

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

Fields of papers citing papers by Natalie Kiesler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalie Kiesler

This figure shows the co-authorship network connecting the top 25 collaborators of Natalie Kiesler. A scholar is included among the top collaborators of Natalie Kiesler 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 Natalie Kiesler. Natalie Kiesler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kiesler, Natalie, J. J. B. Smith, Juho Leinonen, et al.. (2025). The Role of Generative AI in Software Student CollaborAItion. Jyväskylä University Digital Archive (University of Jyväskylä). 72–78. 2 indexed citations
2.
Prather, James, Juho Leinonen, Natalie Kiesler, et al.. (2025). Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools. VTechWorks (Virginia Tech). 300–338. 10 indexed citations
3.
Keuning, Hieke, et al.. (2025). You're (Not) My Type‐ Can LLMs Generate Feedback of Specific Types for Introductory Programming Tasks?. Journal of Computer Assisted Learning. 41(1). 5 indexed citations
4.
Kiesler, Natalie, et al.. (2025). GenAI Voice Mode in Programming Education. 1–8. 1 indexed citations
5.
Kiesler, Natalie, et al.. (2025). Student Engagement with GenAI's Tutoring Feedback: A Mixed Methods Study. arXiv (Cornell University). 1–12. 1 indexed citations
6.
MacNeil, Stephen, Juho Leinonen, Paul Denny, et al.. (2024). Discussing the Changing Landscape of Generative AI in Computing Education. OHMdok (Technische Hochschule Nürnberg). 1916–1916. 6 indexed citations
7.
Barendsen, Erik, Violetta Lonati, Keith Quille, et al.. (2024). AI in and for K-12 Informatics Education. Life after Generative AI.. VTechWorks (Virginia Tech). 279–280. 2 indexed citations
8.
Kiesler, Natalie, et al.. (2024). "Let Them Try to Figure It Out First" - Reasons Why Experts (Do Not) Provide Feedback to Novice Programmers. OHMdok (Technische Hochschule Nürnberg). 38–44. 1 indexed citations
9.
Kiesler, Natalie, et al.. (2024). With Great Power Comes Great Responsibility - Integrating Data Ethics into Computing Education. OHMdok (Technische Hochschule Nürnberg). 471–477. 2 indexed citations
10.
Prather, James, Juho Leinonen, Natalie Kiesler, et al.. (2024). How Instructors Incorporate Generative AI into Teaching Computing. OHMdok (Technische Hochschule Nürnberg). 771–772. 10 indexed citations
11.
Kiesler, Natalie, et al.. (2024). Novice Learners of Programming and Generative AI - Prior Knowledge Matters. OHMdok (Technische Hochschule Nürnberg). 1–2. 1 indexed citations
12.
Kiesler, Natalie, et al.. (2024). How Do You Solve A Problem Like Recruitment? On The Hiring and Retention of Computing Academics. KTH Publication Database DiVA (KTH Royal Institute of Technology). 263–266.
14.
Prather, James, Paul Denny, Juho Leinonen, et al.. (2023). Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans. 561–562. 16 indexed citations
15.
Prather, James, Paul Denny, Juho Leinonen, et al.. (2023). The Robots Are Here: Navigating the Generative AI Revolution in Computing Education. 108–159. 151 indexed citations breakdown →
16.
Kiesler, Natalie & John Impagliazzo. (2023). Evaluating Diversity, Equity, Inclusion, and Accessibility in Accreditation. OHMdok (Technische Hochschule Nürnberg). 1–5.
17.
Kiesler, Natalie, et al.. (2023). Exploring and Improving Workflows for the Donation and Curation of Research Data. 1. 1 indexed citations
18.
Kiesler, Natalie, et al.. (2023). Exploring the Potential of Large Language Models to Generate Formative Programming Feedback. OHMdok (Technische Hochschule Nürnberg). 1–5. 36 indexed citations
19.
Jeuring, Johan, Hieke Keuning, Samiha Marwan, et al.. (2022). Towards Giving Timely Formative Feedback and Hints to Novice Programmers. Aaltodoc (Aalto University). 95–115. 17 indexed citations
20.
Kiesler, Natalie. (2016). Ein Bild sagt mehr als tausend Worte - interaktive Visualisierungen in webbasierten Programmieraufgaben.. DeLFI. 335–337. 1 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.

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