Christina Gardner‐McCune

1.6k total citations · 1 hit paper
72 papers, 951 citations indexed

About

Christina Gardner‐McCune is a scholar working on Computer Science Applications, Developmental and Educational Psychology and Information Systems. According to data from OpenAlex, Christina Gardner‐McCune has authored 72 papers receiving a total of 951 indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computer Science Applications, 23 papers in Developmental and Educational Psychology and 20 papers in Information Systems. Recurrent topics in Christina Gardner‐McCune's work include Teaching and Learning Programming (54 papers), Educational Games and Gamification (18 papers) and Online Learning and Analytics (14 papers). Christina Gardner‐McCune is often cited by papers focused on Teaching and Learning Programming (54 papers), Educational Games and Gamification (18 papers) and Online Learning and Analytics (14 papers). Christina Gardner‐McCune collaborates with scholars based in United States and Colombia. Christina Gardner‐McCune's co-authors include David S. Touretzky, Deborah Seehorn, Fred Martin, Amanpreet Kapoor, Cynthia Breazeal, Lisa Anthony, Wenjing Luo, Anne Corinne Huggins‐Manley, Albert D. Ritzhaupt and LaGarrett J. King and has published in prestigious journals such as Journal of Science Education and Technology, AI Magazine and IEEE Transactions on Education.

In The Last Decade

Christina Gardner‐McCune

55 papers receiving 900 citations

Hit Papers

Envisioning AI for K-12: What Should Every Child Know abo... 2019 2026 2021 2023 2019 100 200 300 400
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. Envisioning AI for K-12: What Should Every Child Know about AI?
    2019 459 citations David S. Touretzky, Christina Gardner‐McCune et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christina Gardner‐McCune United States 13 636 202 200 186 164 72 951
Deborah Seehorn United States 7 528 0.8× 150 0.7× 173 0.9× 106 0.6× 119 0.7× 8 738
Ilkka Jormanainen Finland 13 545 0.9× 195 1.0× 199 1.0× 108 0.6× 63 0.4× 56 821
Irene Lee United States 14 1.3k 2.0× 240 1.2× 515 2.6× 246 1.3× 167 1.0× 38 1.6k
Michelle Craig Canada 22 902 1.4× 318 1.6× 358 1.8× 308 1.7× 115 0.7× 63 1.3k
Thomas Price United States 19 802 1.3× 246 1.2× 429 2.1× 277 1.5× 68 0.4× 72 1.4k
Randi Williams United States 14 494 0.8× 163 0.8× 228 1.1× 183 1.0× 197 1.2× 23 1.0k
Shiyan Jiang United States 13 487 0.8× 125 0.6× 242 1.2× 160 0.9× 26 0.2× 55 842
Tufan Adıgüzel Türkiye 11 270 0.4× 158 0.8× 177 0.9× 392 2.1× 123 0.8× 36 983
Safinah Ali United States 13 431 0.7× 130 0.6× 168 0.8× 97 0.5× 198 1.2× 31 853
Amber Settle United States 18 830 1.3× 269 1.3× 376 1.9× 197 1.1× 57 0.3× 84 1.1k

Countries citing papers authored by Christina Gardner‐McCune

Since Specialization
Citations

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

Fields of papers citing papers by Christina Gardner‐McCune

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christina Gardner‐McCune. 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 Christina Gardner‐McCune. The network helps show where Christina Gardner‐McCune may publish in the future.

Co-authorship network of co-authors of Christina Gardner‐McCune

This figure shows the co-authorship network connecting the top 25 collaborators of Christina Gardner‐McCune. A scholar is included among the top collaborators of Christina Gardner‐McCune 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 Christina Gardner‐McCune. Christina Gardner‐McCune 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.
Touretzky, David S., et al.. (2025). From Lecture Hall to Homeroom: Co-Designing an AI Elective with Middle School CS Teachers. International Journal of Artificial Intelligence in Education. 35(4). 1749–1792.
3.
Hernández, Mónica, Zhiyuan Liu, Christina Gardner‐McCune, et al.. (2025). Deploying computation-based Making projects in authentic public school classrooms at scale: Lessons learned. International Journal of Child-Computer Interaction. 45. 100738–100738.
4.
Weintrop, David, Rotem Israel‐Fishelson, & Christina Gardner‐McCune. (2024). Emerging computational and digital literacies in K-12 education. International Journal of Child-Computer Interaction. 43. 100707–100707. 1 indexed citations
5.
6.
Gardner‐McCune, Christina, et al.. (2024). Understanding Social Good-Based Introductory Computer Science Pedagogy for Black Boys. 128–132.
7.
Touretzky, David S. & Christina Gardner‐McCune. (2023). Guiding Students to Investigate What Google Speech Recognition Knows about Language. Proceedings of the AAAI Conference on Artificial Intelligence. 37(13). 16040–16047. 2 indexed citations
8.
Touretzky, David S., Christina Gardner‐McCune, & Deborah Seehorn. (2022). Machine Learning and the Five Big Ideas in AI. International Journal of Artificial Intelligence in Education. 33(2). 233–266. 69 indexed citations
9.
Touretzky, David S., et al.. (2022). Lessons Learned From Teaching Artificial Intelligence to Middle School Students. 1371–1371. 6 indexed citations
10.
Gardner‐McCune, Christina, et al.. (2022). Case Study on VR Empathy Game: Challenges with VR Games Development for Emotional Interactions with the VR Characters. 16(1). 412–418. 1 indexed citations
11.
Kapoor, Amanpreet & Christina Gardner‐McCune. (2022). Categorizing Research on Identity in Undergraduate Computing Education. 1–13. 3 indexed citations
12.
13.
Kapoor, Amanpreet & Christina Gardner‐McCune. (2020). Barriers to Securing Industry Internships in Computing. 142–151. 17 indexed citations
14.
Touretzky, David S., Christina Gardner‐McCune, Cynthia Breazeal, Fred Martin, & Deborah Seehorn. (2019). A Year in K–12 AI Education. AI Magazine. 40(4). 88–90. 64 indexed citations
15.
Touretzky, David S. & Christina Gardner‐McCune. (2018). Calypso for Cozmo. 1110–1110. 9 indexed citations
16.
Touretzky, David S., et al.. (2018). Demonstrating the Ability of Elementary School Students to Reason About Programs. 735–740. 6 indexed citations
17.
Kapoor, Amanpreet & Christina Gardner‐McCune. (2018). Understanding How Computer Science Undergraduate Students are Developing their Professional Identities. 1080–1080.
18.
Boyer, Kristy Elizabeth, et al.. (2017). How block categories affect learner satisfaction with a block-based programming interface. 9 indexed citations
19.
Touretzky, David S., et al.. (2016). Teaching "Lawfulness" With Kodu. 621–626. 5 indexed citations
20.

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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