Valerie Barr

2.3k total citations · 1 hit paper
42 papers, 1.4k citations indexed

About

Valerie Barr is a scholar working on Computer Science Applications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Valerie Barr has authored 42 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Science Applications, 15 papers in Information Systems and 8 papers in Artificial Intelligence. Recurrent topics in Valerie Barr's work include Teaching and Learning Programming (18 papers), Online Learning and Analytics (6 papers) and Software Engineering Research (6 papers). Valerie Barr is often cited by papers focused on Teaching and Learning Programming (18 papers), Online Learning and Analytics (6 papers) and Software Engineering Research (6 papers). Valerie Barr collaborates with scholars based in United States and Mexico. Valerie Barr's co-authors include Chris Stephenson, Avelino J. González, Susanne E. Hambrusch, Vicki H. Allan, Dennis Brylow, Amber Settle, Mark Guzdial, Debra S. Goldberg, Deborah Trytten and Beth Quinn and has published in prestigious journals such as SHILAP Revista de lepidopterología, Communications of the ACM and Knowledge-Based Systems.

In The Last Decade

Valerie Barr

38 papers receiving 1.3k citations

Hit Papers

align trajectories

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.

Bringing computational thinking to K-12

2011 1.1k citations Valerie Barr et al. ACM Inroads profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Valerie Barr United States	11	1.2k	517	214	203	193	42	1.4k
Irene Lee United States	14	1.3k 1.0×	515 1.0×	228 1.1×	240 1.2×	182 0.9×	38	1.6k
Joyce Malyn‐Smith United States	10	1.0k 0.8×	473 0.9×	123 0.6×	184 0.9×	173 0.9×	23	1.2k
Michal Armoni Israel	20	1.4k 1.2×	682 1.3×	194 0.9×	349 1.7×	97 0.5×	85	1.6k
Satabdi Basu United States	15	1.0k 0.8×	623 1.2×	148 0.7×	153 0.8×	203 1.1×	33	1.2k
Kemi Jona United States	12	948 0.8×	472 0.9×	131 0.6×	156 0.8×	212 1.1×	29	1.4k
Valentina Dagienė Lithuania	21	1.1k 0.9×	461 0.9×	230 1.1×	383 1.9×	93 0.5×	109	1.5k
Amber Settle United States	18	830 0.7×	376 0.7×	127 0.6×	269 1.3×	82 0.4×	84	1.1k
Linda Mannila Sweden	17	1.3k 1.1×	601 1.2×	133 0.6×	374 1.8×	92 0.5×	49	1.6k
Jesús Moreno-León Spain	18	1.0k 0.8×	485 0.9×	153 0.7×	215 1.1×	106 0.5×	35	1.1k
Chris Stephenson United States	16	2.0k 1.6×	867 1.7×	218 1.0×	335 1.7×	317 1.6×	48	2.3k

Countries citing papers authored by Valerie Barr

Since Specialization

Citations

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

Fields of papers citing papers by Valerie Barr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Valerie Barr

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Barr, Valerie, Grant Braught, Janet Davis, et al.. (2025). CS2023: Computer Science Curriculum Guidelines: A New Liberal Arts Perspective. ACM Inroads. 16(1). 40–52.

2.

Barr, Valerie, Carla E. Brodley, & Manuel A. Pérez-Quiñones. (2024). Visualizing Progress in Broadening Participation in Computing: The Value of Context. Communications of the ACM. 67(7). 46–55. 1 indexed citations

3.

Zieffler, Andrew, et al.. (2022). Facilitating team-based data science: Lessons learned from the DSC-WAV project. arXiv (Cornell University). 5(2). 244–265. 4 indexed citations

4.

Horton, Nicholas J., Benjamin S. Baumer, Andrew Zieffler, & Valerie Barr. (2021). The Data Science Corps Wrangle-Analyze-Visualize Program: Building Data Acumen for Undergraduate Students. SHILAP Revista de lepidopterología. 2 indexed citations

5.

Barr, Valerie. (2017). Gender diversity in computing. Communications of the ACM. 60(4). 5–5. 5 indexed citations

6.

Barr, Valerie, et al.. (2017). Computer Science Topics in First- and Second- Year Seminar Courses. 643–644. 1 indexed citations

7.

Barr, Valerie, Michael Stonebraker, Raul Castro Fernandez, Dong Deng, & Michael L. Brodie. (2016). How we teach CS2All, and what to do about database decay. Communications of the ACM. 60(1). 10–11. 2 indexed citations

8.

Barr, Valerie & Mark Guzdial. (2015). Advice on teaching CS, and the learnability of programming languages. Communications of the ACM. 58(3). 8–9. 7 indexed citations

9.

Barr, Valerie & Michael Stonebraker. (2015). How men can help women in CS; winning 'computing's Nobel prize'. Communications of the ACM. 58(11). 10–11.

10.

Guzdial, Mark & Valerie Barr. (2013). The lure of live coding; the attraction of small data. Communications of the ACM. 56(12). 10–11. 1 indexed citations

11.

Barr, Valerie. (2012). Create two, three, many courses: an experiment in contextualized introductory computer science. Journal of computing sciences in colleges. 27(6). 19–25. 7 indexed citations

12.

Caristi, James, et al.. (2011). Starting a computational science program. 3–4. 1 indexed citations

13.

Barr, Valerie, et al.. (2009). Building a campus wide computation initiative: panel discussion. Journal of computing sciences in colleges. 24(3). 109–110. 1 indexed citations

14.

Barr, Valerie, et al.. (2004). Verification of Lexicalized Tree Adjoining Grammars. 126–131.

15.

Barr, Valerie. (2003). A Proposed Model for Effective Verification of Natural Language Generation Systems.. The Florida AI Research Society. 10(12). 208–212. 3 indexed citations

16.

Barr, Valerie. (2001). A Quagmire of Terminology: Verification and Validation, Testing, and Evaluation. The Florida AI Research Society. 625–629. 6 indexed citations

17.

Barr, Valerie & Judith L. Klavans. (2001). Verification and validation of language processing systems. 9. 1–7. 10 indexed citations

18.

Adams, Elizabeth, et al.. (2000). Teaching software testing throughout the curriculum. Journal of computing sciences in colleges. 15(5). 178–180. 1 indexed citations

19.

Barr, Valerie. (1999). Applying Reliability Engineering to Expert Systems. The Florida AI Research Society. 494–498. 7 indexed citations

20.

Barr, Valerie. (1999). Applications of rule-base coverage measures to expert system evaluation. Knowledge-Based Systems. 12(1-2). 27–35. 7 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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