John T. Behrens

2.3k total citations
56 papers, 1.3k citations indexed

About

John T. Behrens is a scholar working on Artificial Intelligence, Computer Science Applications and Developmental and Educational Psychology. According to data from OpenAlex, John T. Behrens has authored 56 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 16 papers in Computer Science Applications and 11 papers in Developmental and Educational Psychology. Recurrent topics in John T. Behrens's work include Intelligent Tutoring Systems and Adaptive Learning (13 papers), Online Learning and Analytics (11 papers) and Innovative Teaching and Learning Methods (6 papers). John T. Behrens is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (13 papers), Online Learning and Analytics (11 papers) and Innovative Teaching and Learning Methods (6 papers). John T. Behrens collaborates with scholars based in United States, China and United Kingdom. John T. Behrens's co-authors include Robert J. Mislevy, Raymond B. Miller, Barbara A. Greene, Kristen E. DiCerbo, Roy Levy, John W. Maag, Wayne Rowe, Mark M. Leach, Malcolm Bauer and William A. Stock and has published in prestigious journals such as Information Sciences, Psychological Methods and Journal of Counseling Psychology.

In The Last Decade

John T. Behrens

55 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John T. Behrens United States 17 318 282 270 219 206 56 1.3k
DE Ayala United States 2 286 0.9× 180 0.6× 193 0.7× 106 0.5× 175 0.8× 4 1.3k
Okan Bulut Canada 22 498 1.6× 159 0.6× 261 1.0× 328 1.5× 219 1.1× 142 1.7k
Terry A. Ackerman United States 19 321 1.0× 176 0.6× 215 0.8× 182 0.8× 286 1.4× 62 2.2k
Andreas Frey Germany 17 519 1.6× 247 0.9× 278 1.0× 103 0.5× 159 0.8× 91 1.4k
Menucha Birenbaum Israel 26 1.1k 3.4× 234 0.8× 419 1.6× 173 0.8× 273 1.3× 73 1.9k
Christine E. DeMars United States 23 622 2.0× 330 1.2× 375 1.4× 100 0.5× 514 2.5× 72 2.1k
Kaśka Porayska‐Pomsta United Kingdom 17 402 1.3× 105 0.4× 346 1.3× 385 1.8× 115 0.6× 41 1.5k
Marily Oppezzo United States 10 307 1.0× 165 0.6× 430 1.6× 204 0.9× 315 1.5× 33 1.1k
Xiangen Hu United States 26 366 1.2× 244 0.9× 607 2.2× 926 4.2× 222 1.1× 111 2.1k
Walter P. Vispoel United States 25 663 2.1× 435 1.5× 489 1.8× 112 0.5× 549 2.7× 85 2.4k

Countries citing papers authored by John T. Behrens

Since Specialization
Citations

This map shows the geographic impact of John T. Behrens'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 John T. Behrens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Behrens more than expected).

Fields of papers citing papers by John T. Behrens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John T. Behrens. 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 John T. Behrens. The network helps show where John T. Behrens may publish in the future.

Co-authorship network of co-authors of John T. Behrens

This figure shows the co-authorship network connecting the top 25 collaborators of John T. Behrens. A scholar is included among the top collaborators of John T. Behrens 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 John T. Behrens. John T. Behrens 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.
Behrens, John T., Kristen E. DiCerbo, & Peter W. Foltz. (2019). Assessment of Complex Performances in Digital Environments. The Annals of the American Academy of Political and Social Science. 683(1). 217–232. 6 indexed citations
2.
Cheng, Ying, et al.. (2016). A simplified version of the maximum information per time unit method in computerized adaptive testing. Behavior Research Methods. 49(2). 502–512. 14 indexed citations
3.
DiCerbo, Kristen E., Robert J. Mislevy, & John T. Behrens. (2016). Inference in Game-Based Assessment. 277–303. 3 indexed citations
4.
Cheng, Ying, Cheng Liu, & John T. Behrens. (2014). Standard Error of Ability Estimates and the Classification Accuracy and Consistency of Binary Decisions. Psychometrika. 80(3). 645–664. 10 indexed citations
5.
Mislevy, Robert J., John T. Behrens, Randy Elliot Bennett, et al.. (2013). On the Roles of External Knowledge Representations in Assessment Design: (643752011-001). Open Access Journals at BC (Boston College). 1 indexed citations
6.
Behrens, John T., et al.. (2012). Five Aspirations for Educational Data Mining.. Educational Data Mining. 7–8. 1 indexed citations
7.
Behrens, John T., Robert J. Mislevy, Kristen E. DiCerbo, & Roy Levy. (2012). Evidence Centered Design for Learning and Assessment in the Digital World. 13–54. 28 indexed citations
8.
Rutstein, Daisy, Robert J. Mislevy, Junhui Liu, et al.. (2010). A Bayesian Network Approach to Modeling Learning Progressions and Task Performance. CRESST Report 776.. 4 indexed citations
9.
Behrens, John T., Robert J. Mislevy, Kristen E. DiCerbo, & Roy Levy. (2010). An Evidence Centered Design for Learning and Assessment in the Digital World. CRESST Report 778.. 1 indexed citations
10.
Mislevy, Robert J., John T. Behrens, Randy Elliot Bennett, et al.. (2007). On the Roles of External Knowledge Representations in Assessment Design. CSE Report 722.. 1 indexed citations
11.
Behrens, John T., Robert J. Mislevy, Malcolm Bauer, David Williamson, & Roy Levy. (2004). Introduction to Evidence Centered Design and Lessons Learned From Its Application in a Global E-Learning Program. International Journal of Testing. 4(4). 295–301. 29 indexed citations
12.
Williamson, David M., et al.. (2003). Creating a Complex Measurement Model Using Evidence Centered Design.. American Educational Research Association Annual Meeting. 4 indexed citations
13.
Bauer, Malcolm, David M. Williamson, Robert J. Mislevy, & John T. Behrens. (2003). Using Evidence-Centered Design to Develop Advanced Simulation-Based Assessment and Training. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2003(1). 1495–1502. 6 indexed citations
14.
Blanchard, Jay, John T. Behrens, & Gary Anderson. (1999). The Effects of Concurrent Classroom and Home Instructional Video-Game Use on Student Achievement. Computers in the Schools. 14(3-4). 65–78. 3 indexed citations
15.
Behrens, John T.. (1997). Principles and procedures of exploratory data analysis.. Psychological Methods. 2(2). 131–160. 297 indexed citations
16.
Lewandowsky, Stephan & John T. Behrens. (1996). Visual detection of clusters in statistical maps. UWA Profiles and Research Repository (University of Western Australia). 1 indexed citations
17.
18.
Leach, Mark M., John T. Behrens, & Wayne Rowe. (1996). The Journal of Multicultural Counseling and Development: Then, Now, and in the 21st Century. Journal of Multicultural Counseling and Development. 24(3). 167–175. 10 indexed citations
19.
Behrens, John T., et al.. (1990). Judgment Errors in Elementary Box-Plot Displays. Communications in Statistics - Simulation and Computation. 19(1). 245–262. 8 indexed citations
20.
Kulhavy, Raymond W., et al.. (1990). RESPONSE FEEDBACK, CERTITUDE AND LEARNING FROM TEXT. British Journal of Educational Psychology. 60(2). 161–170. 9 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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