Bradford Mott

4.2k total citations
140 papers, 2.0k citations indexed

About

Bradford Mott is a scholar working on Developmental and Educational Psychology, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, Bradford Mott has authored 140 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Developmental and Educational Psychology, 66 papers in Artificial Intelligence and 62 papers in Computer Science Applications. Recurrent topics in Bradford Mott's work include Educational Games and Gamification (67 papers), Teaching and Learning Programming (53 papers) and Innovative Teaching and Learning Methods (30 papers). Bradford Mott is often cited by papers focused on Educational Games and Gamification (67 papers), Teaching and Learning Programming (53 papers) and Innovative Teaching and Learning Methods (30 papers). Bradford Mott collaborates with scholars based in United States, Sweden and Puerto Rico. Bradford Mott's co-authors include James C. Lester, Jonathan Rowe, Lucy R. Shores, Eric Wiebe, Wookhee Min, Kristy Elizabeth Boyer, Hiller A. Spires, Jennifer Sabourin, Scott McQuiggan and Cindy E. Hmelo‐Silver and has published in prestigious journals such as Information Sciences, Frontiers in Psychology and Journal of Adolescent Health.

In The Last Decade

Bradford Mott

131 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bradford Mott United States 24 1.0k 809 789 285 246 140 2.0k
Susan Bull United Kingdom 24 825 0.8× 870 1.1× 882 1.1× 440 1.5× 154 0.6× 86 2.0k
Ig Ibert Bittencourt Brazil 24 824 0.8× 809 1.0× 721 0.9× 412 1.4× 298 1.2× 193 2.3k
Τhanasis Daradoumis Spain 20 496 0.5× 722 0.9× 481 0.6× 454 1.6× 146 0.6× 115 1.7k
Iván Martínez‐Ortiz Spain 22 1.0k 1.0× 661 0.8× 350 0.4× 291 1.0× 440 1.8× 76 1.6k
Alexandra I. Cristea United Kingdom 21 730 0.7× 882 1.1× 676 0.9× 246 0.9× 379 1.5× 226 1.9k
Jodi Asbell‐Clarke United States 10 1.4k 1.3× 1.2k 1.5× 238 0.3× 404 1.4× 312 1.3× 30 2.2k
Dietrich Albert Austria 17 551 0.5× 452 0.6× 443 0.6× 261 0.9× 169 0.7× 174 1.4k
Kristy Elizabeth Boyer United States 24 771 0.7× 1.1k 1.4× 765 1.0× 310 1.1× 56 0.2× 174 2.1k
Michael Hanus Germany 17 965 0.9× 390 0.5× 835 1.1× 321 1.1× 297 1.2× 99 2.1k
Tiffany Barnes United States 30 1.4k 1.3× 2.1k 2.6× 864 1.1× 503 1.8× 312 1.3× 262 3.1k

Countries citing papers authored by Bradford Mott

Since Specialization
Citations

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

Fields of papers citing papers by Bradford Mott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bradford Mott

This figure shows the co-authorship network connecting the top 25 collaborators of Bradford Mott. A scholar is included among the top collaborators of Bradford Mott 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 Bradford Mott. Bradford Mott 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.
Lee, Seung, Bradford Mott, Krista Glazewski, et al.. (2024). Supporting Upper Elementary Students in Learning AI Concepts with Story-Driven Game-Based Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23092–23100. 1 indexed citations
2.
Ottenbreit‐Leftwich, Anne, Cindy E. Hmelo‐Silver, Krista Glazewski, et al.. (2024). Inquiry-based Artificial Intelligence Curriculum for Upper Elementary Students: A Design Case of PrimaryAI. Indiana Magazine of History (Indiana University). 15(3). 94–108. 1 indexed citations
3.
Glazewski, Krista, Cindy E. Hmelo‐Silver, Thomas Brush, et al.. (2024). An Investigation of Dashboard in Collaborative Inquiry: The Dynamic Interplay between Technology and Pedagogy in Classroom Orchestration. Computer-supported collaborative learning/˜The œComputer-Supported Collaborative Learning Conference. 253–256. 1 indexed citations
4.
Kim, Yeo Jin, Wookhee Min, Jonathan Rowe, et al.. (2024). Dual Process Masking for Dialogue Act Recognition. 15270–15283.
5.
Min, Wookhee, et al.. (2024). Unplugged K-12 AI Learning: Exploring Representation and Reasoning with a Facial Recognition Game. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23285–23293. 5 indexed citations
6.
Lee, Seung, et al.. (2024). Exploring Gameplay and Learning in a Narrative-Centered Digital Game for Elementary Science Education. IEEE Transactions on Games. 16(4). 947–959.
7.
Glazewski, Krista, et al.. (2023). Co-designing a Classroom Orchestration Assistant for Game-based PBL Environments. TechTrends. 67(6). 918–930. 1 indexed citations
8.
Mott, Bradford, Krista Glazewski, Anne Ottenbreit‐Leftwich, et al.. (2023). Fostering Upper Elementary AI Education: Iteratively Refining a Use-Modify-Create Scaffolding Progression for AI Planning. 647–647. 1 indexed citations
9.
Ottenbreit‐Leftwich, Anne, Krista Glazewski, Cindy E. Hmelo‐Silver, et al.. (2022). Lessons Learned for AI Education with Elementary Students and Teachers. International Journal of Artificial Intelligence in Education. 33(2). 267–289. 48 indexed citations
10.
Ottenbreit‐Leftwich, Anne, Krista Glazewski, Cindy E. Hmelo‐Silver, et al.. (2022). Is Elementary AI Education Possible?. 1364–1364. 1 indexed citations
11.
Lester, James C., et al.. (2021). How Use-Modify-Create Brings Middle Grades Students To Computational Thinking. 12(3). 1–20. 2 indexed citations
12.
Min, Wookhee, et al.. (2020). Enhancing Student Competency Models for Game-Based Learning with a Hybrid Stealth Assessment Framework.. Educational Data Mining. 8 indexed citations
13.
14.
Smith, Andy, et al.. (2018). A Multimodal Assessment Framework for Integrating Student Writing and Drawing in Elementary Science Learning. IEEE Transactions on Learning Technologies. 12(1). 3–15. 28 indexed citations
15.
Wang, Pengcheng, Jonathan Rowe, Wookhee Min, Bradford Mott, & James C. Lester. (2017). Simulating Player Behavior for Data-Driven Interactive Narrative Personalization. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(1). 255–261. 4 indexed citations
16.
Min, Wookhee, Bradford Mott, Jonathan Rowe, & James C. Lester. (2017). Deep LSTM-Based Goal Recognition Models for Open-World Digital Games.. National Conference on Artificial Intelligence. 5 indexed citations
17.
Min, Wookhee, et al.. (2016). A Generalized Multidimensional Evaluation Framework for Player Goal Recognition. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 12(1). 197–203. 9 indexed citations
18.
19.
Min, Wookhee, Eun Young Ha, Jonathan Rowe, Bradford Mott, & James C. Lester. (2014). Deep Learning-Based Goal Recognition in Open-Ended Digital Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 10(1). 37–43. 38 indexed citations
20.
Rowe, Jonathan, Bradford Mott, & James C. Lester. (2014). Optimizing Player Experience in Interactive Narrative Planning: A Modular Reinforcement Learning Approach. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 10(1). 160–166. 18 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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