James Lester

881 total citations
17 papers, 430 citations indexed

About

James Lester is a scholar working on Developmental and Educational Psychology, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, James Lester has authored 17 papers receiving a total of 430 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Developmental and Educational Psychology, 10 papers in Artificial Intelligence and 5 papers in Computer Science Applications. Recurrent topics in James Lester's work include Educational Games and Gamification (11 papers), Artificial Intelligence in Games (6 papers) and Intelligent Tutoring Systems and Adaptive Learning (4 papers). James Lester is often cited by papers focused on Educational Games and Gamification (11 papers), Artificial Intelligence in Games (6 papers) and Intelligent Tutoring Systems and Adaptive Learning (4 papers). James Lester collaborates with scholars based in United States and Canada. James Lester's co-authors include Jonathan Rowe, Roger Azevedo, Andrew Emerson, Michelle Taub, Elizabeth B. Cloude, Andy Smith, Robert G. Sawyer, Scott McQuiggan, Sun Young Lee and Bradford Mott and has published in prestigious journals such as Computers in Human Behavior, Computers & Education and British Journal of Educational Technology.

In The Last Decade

James Lester

17 papers receiving 412 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Lester United States 9 240 177 161 95 46 17 430
Lucy R. Shores United States 6 261 1.1× 124 0.7× 108 0.7× 65 0.7× 68 1.5× 7 361
Toby Dragon United States 9 234 1.0× 220 1.2× 237 1.5× 88 0.9× 19 0.4× 18 458
Jennifer Sabourin United States 8 227 0.9× 113 0.6× 123 0.8× 114 1.2× 56 1.2× 14 422
Christian Sebastian Loh United States 9 225 0.9× 91 0.5× 90 0.6× 52 0.5× 71 1.5× 19 329
Jennifer K. Olsen Switzerland 12 185 0.8× 96 0.5× 122 0.8× 89 0.9× 16 0.3× 35 374
Kay Berkling Germany 12 195 0.8× 307 1.7× 108 0.7× 76 0.8× 40 0.9× 63 519
Carol Forsyth United States 10 239 1.0× 147 0.8× 99 0.6× 102 1.1× 24 0.5× 21 388
Xian Peng China 11 135 0.6× 177 1.0× 261 1.6× 175 1.8× 25 0.5× 31 500
Andrea Valente Denmark 8 167 0.7× 64 0.4× 81 0.5× 52 0.5× 35 0.8× 41 360
Ming‐Puu Chen Taiwan 7 400 1.7× 72 0.4× 222 1.4× 199 2.1× 54 1.2× 26 590

Countries citing papers authored by James Lester

Since Specialization
Citations

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

Fields of papers citing papers by James Lester

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Lester

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

All Works

17 of 17 papers shown
1.
Kim, Yeo Jin, et al.. (2024). LLM-Based Student Plan Generation for Adaptive Scaffolding in Game-Based Learning Environments. International Journal of Artificial Intelligence in Education. 35(2). 533–558. 10 indexed citations
2.
Kim, Yeo Jin, et al.. (2023). Language Model-Based Player Goal Recognition in Open World Digital Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 19(1). 75–85. 2 indexed citations
3.
Glazewski, Krista, Anne Ottenbreit‐Leftwich, Cindy E. Hmelo‐Silver, et al.. (2022). PrimaryAI. 628–628. 1 indexed citations
4.
Ha, Eun Young, Jonathan E. Rowe, Bradford Mott, & James Lester. (2021). Goal Recognition with Markov Logic Networks for Player-Adaptive Games. Proceedings of the AAAI Conference on Artificial Intelligence. 26(1). 2113–2119. 3 indexed citations
5.
Emerson, Andrew, et al.. (2020). Predictive Student Modeling in Game-Based Learning Environments with Word Embedding Representations of Reflection. International Journal of Artificial Intelligence in Education. 31(1). 1–23. 26 indexed citations
6.
Emerson, Andrew, et al.. (2020). Predictive Student Modeling in Educational Games with Multi-Task Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 34(1). 654–661. 13 indexed citations
7.
Emerson, Andrew, Elizabeth B. Cloude, Roger Azevedo, & James Lester. (2020). Multimodal learning analytics for game‐based learning. British Journal of Educational Technology. 51(5). 1505–1526. 93 indexed citations
8.
Taub, Michelle, Robert G. Sawyer, Andy Smith, et al.. (2019). The agency effect: The impact of student agency on learning, emotions, and problem-solving behaviors in a game-based learning environment. Computers & Education. 147. 103781–103781. 126 indexed citations
9.
Min, Wookhee, et al.. (2018). Affect-Based Early Prediction of Player Mental Demand and Engagement for Educational Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 14(1). 243–249. 6 indexed citations
10.
Taub, Michelle, et al.. (2017). Using multi-channel data with multi-level modeling to assess in-game performance during gameplay with Crystal Island. Computers in Human Behavior. 76. 641–655. 44 indexed citations
11.
Harley, Jason M., Jonathan Rowe, James Lester, & Claude Frasson. (2015). Designing Story-Centric Games for Player Emotion: A Theoretical Perspective. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 11(4). 34–37. 1 indexed citations
12.
Ha, Eun Young, Jonathan Rowe, Bradford Mott, & James Lester. (2011). Goal Recognition with Markov Logic Networks for Player-Adaptive Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 7(1). 32–39. 25 indexed citations
13.
Rowe, Jonathan & James Lester. (2010). Modeling User Knowledge with Dynamic Bayesian Networks in Interactive Narrative Environments. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 6(1). 57–62. 41 indexed citations
14.
McQuiggan, Scott, Sun Young Lee, & James Lester. (2006). Predicting User Physiological Response for Interactive Environments: An Inductive Approach. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 2(1). 60–65. 35 indexed citations
15.
Lester, James. (1998). Staking Your Claim. Civil engineering. 68(7). 65–67. 2 indexed citations
16.
Lester, James. (1987). Lawyer on a Microchip. Civil engineering. 57(6). 68–69. 1 indexed citations
17.
Lester, James. (1985). Genetic changes during development of penaeid shrimp.. SEAFDEC/AQD Repository (Southeast Asian Fisheries Development Center). 165. 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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