James Prather

3.6k total citations · 9 hit papers
72 papers, 2.1k citations indexed

About

James Prather is a scholar working on Computer Science Applications, Information Systems and Developmental and Educational Psychology. According to data from OpenAlex, James Prather has authored 72 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Computer Science Applications, 18 papers in Information Systems and 14 papers in Developmental and Educational Psychology. Recurrent topics in James Prather's work include Teaching and Learning Programming (39 papers), Online Learning and Analytics (31 papers) and Software Engineering Research (16 papers). James Prather is often cited by papers focused on Teaching and Learning Programming (39 papers), Online Learning and Analytics (31 papers) and Software Engineering Research (16 papers). James Prather collaborates with scholars based in United States, New Zealand and Ireland. James Prather's co-authors include Brett A. Becker, Paul Denny, Andrew Luxton-Reilly, James Finnie-Ansley, Juho Leinonen, Brent N. Reeves, Raymond Pettit, Eddie Antonio Santos, Arto Hellas and Dastyni Loksa and has published in prestigious journals such as Communications of the ACM, Public Administration Review and Educational Psychology Review.

In The Last Decade

James Prather

64 papers receiving 2.0k citations

Hit Papers

The Robots Are Coming: Exploring the Implications of Open... 2022 2026 2023 2024 2022 2023 2023 2023 2024 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming
    2022 226 citations James Finnie-Ansley, Paul Denny et al. profile →
  2. Programming Is Hard - Or at Least It Used to Be
    2023 185 citations Brett A. Becker, Paul Denny et al. profile →
  3. The Robots Are Here: Navigating the Generative AI Revolution in Computing Education
    2023 151 citations James Prather, Paul Denny et al. profile →
  4. Using Large Language Models to Enhance Programming Error Messages
    2023 128 citations Juho Leinonen, Arto Hellas et al. Aaltodoc (Aalto University) profile →
  5. Computing Education in the Era of Generative AI
    2024 108 citations Paul Denny, James Prather et al. Communications of the ACM profile →
  6. My AI Wants to Know if This Will Be on the Exam: Testing OpenAI’s Codex on CS2 Programming Exercises
    2023 105 citations James Finnie-Ansley, Paul Denny et al. profile →
  7. “It’s Weird That it Knows What I Want”: Usability and Interactions with Copilot for Novice Programmers
    2023 90 citations James Prather, Brent N. Reeves et al. ACM Transactions on Computer-Human Interaction profile →
  8. Prompt Problems: A New Programming Exercise for the Generative AI Era
    2024 69 citations Paul Denny, Juho Leinonen et al. profile →
  9. The Widening Gap: The Benefits and Harms of Generative AI for Novice Programmers
    2024 53 citations James Prather, Brent N. Reeves et al. Aaltodoc (Aalto University) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Prather United States 22 1.4k 620 595 379 327 72 2.1k
Juho Leinonen Finland 21 1.4k 1.1× 549 0.9× 660 1.1× 331 0.9× 217 0.7× 118 2.1k
Arto Hellas Finland 20 1.3k 0.9× 440 0.7× 459 0.8× 350 0.9× 159 0.5× 115 1.7k
Benedict du Boulay United Kingdom 20 1.1k 0.8× 450 0.7× 640 1.1× 678 1.8× 140 0.4× 60 1.8k
‪Marcos Román-González‬ Spain 23 2.1k 1.5× 411 0.7× 340 0.6× 1.0k 2.7× 175 0.5× 55 2.5k
Judy Sheard Australia 27 1.7k 1.3× 684 1.1× 274 0.5× 648 1.7× 215 0.7× 155 3.0k
Brent N. Reeves United States 18 560 0.4× 348 0.6× 391 0.7× 118 0.3× 111 0.3× 37 1.2k
Irene Lee United States 14 1.3k 0.9× 240 0.4× 228 0.4× 515 1.4× 64 0.2× 38 1.6k
Petri Ihantola Finland 22 1.4k 1.0× 524 0.8× 305 0.5× 469 1.2× 371 1.1× 71 1.8k
Chris Piech United States 16 1.5k 1.1× 378 0.6× 779 1.3× 378 1.0× 104 0.3× 45 2.0k
Irwin Kwan United States 15 489 0.4× 623 1.0× 399 0.7× 127 0.3× 106 0.3× 29 1.3k

Countries citing papers authored by James Prather

Since Specialization
Citations

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

Fields of papers citing papers by James Prather

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Prather

This figure shows the co-authorship network connecting the top 25 collaborators of James Prather. A scholar is included among the top collaborators of James Prather 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 James Prather. James Prather 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.
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.
Margulieux, Lauren E., James Prather, Brent N. Reeves, et al.. (2024). Self-Regulation, Self-Efficacy, and Fear of Failure Interactions with How Novices Use LLMs to Solve Programming Problems. Aaltodoc (Aalto University). 276–282. 18 indexed citations
4.
Denny, Paul, James Prather, Brett A. Becker, et al.. (2024). Computing Education in the Era of Generative AI. Communications of the ACM. 67(2). 56–67. 108 indexed citations breakdown →
5.
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
6.
Denny, Paul, Juho Leinonen, James Prather, et al.. (2024). Prompt Problems: A New Programming Exercise for the Generative AI Era. 296–302. 69 indexed citations breakdown →
7.
Prather, James, et al.. (2024). The Widening Gap: The Benefits and Harms of Generative AI for Novice Programmers. Aaltodoc (Aalto University). 469–486. 53 indexed citations breakdown →
8.
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
9.
Denny, Paul, David H. Smith, James Prather, et al.. (2024). Integrating Natural Language Prompting Tasks in Introductory Programming Courses. 88–94. 3 indexed citations
10.
Sarsa, Sami, James Prather, Juho Leinonen, et al.. (2024). Solving Proof Block Problems Using Large Language Models. Aaltodoc (Aalto University). 1063–1069. 6 indexed citations
11.
Hellas, Arto, et al.. (2024). Evaluating Contextually Personalized Programming Exercises Created with Generative AI. Jyväskylä University Digital Archive (University of Jyväskylä). 95–113. 9 indexed citations
12.
Reeves, Brent N., Sami Sarsa, James Prather, et al.. (2023). Evaluating the Performance of Code Generation Models for Solving Parsons Problems With Small Prompt Variations. Aaltodoc (Aalto University). 299–305. 39 indexed citations
13.
Finnie-Ansley, James, Paul Denny, Andrew Luxton-Reilly, et al.. (2023). My AI Wants to Know if This Will Be on the Exam: Testing OpenAI’s Codex on CS2 Programming Exercises. 97–104. 105 indexed citations breakdown →
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, Brent N. Reeves, Paul Denny, et al.. (2023). “It’s Weird That it Knows What I Want”: Usability and Interactions with Copilot for Novice Programmers. ACM Transactions on Computer-Human Interaction. 31(1). 1–31. 90 indexed citations breakdown →
16.
Becker, Brett A., et al.. (2022). Community Input for CS2023. 1245–1245. 1 indexed citations
17.
MacNeil, Stephen, Joanne Kim, Juho Leinonen, et al.. (2022). The Implications of Large Language Models for CS Teachers and Students. Open Research Online (The Open University). 1255–1255. 26 indexed citations
18.
Ericson, Barbara, Paul Denny, James Prather, et al.. (2022). Parsons Problems and Beyond. Aaltodoc (Aalto University). 191–234. 31 indexed citations
19.
Pettit, Raymond & James Prather. (2017). Automated assessment tools: too many cooks, not enough collaboration. Journal of computing sciences in colleges. 32(4). 113–121. 12 indexed citations
20.
Prather, James, et al.. (1994). When Four-Year and Community Colleges Cooperate: Studies in Planning for Enrollment Maximization.. 1(2). 3 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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