John T. Behrens

2.3k citations
56 papers · 1.3k indexed · h-index 17
Topics
Intelligent Tutoring Systems and Adaptive Learning (13 papers)Online Learning and Analytics (11 papers)Innovative Teaching and Learning Methods (6 papers)

In The Last Decade

John T. Behrens

55 papers receiving 1.1k citations

Peers

John T. Behrens
Comparison fields: 5 of 146
  • Education 318
  • Social Psychology 282
  • Developmental and Educational Psychology 270
  • Artificial Intelligence 219
  • Experimental and Cognitive Psychology 206
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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
#WorkIndexed citations
1 6
2 14
3 3
4 10
5
On the Roles of External Knowledge Representations in Assessment Design: (643752011-001)
1
6
Five Aspirations for Educational Data Mining.
1
7 28
8
A Bayesian Network Approach to Modeling Learning Progressions and Task Performance. CRESST Report 776.
4
9
An Evidence Centered Design for Learning and Assessment in the Digital World. CRESST Report 778.
1
10
On the Roles of External Knowledge Representations in Assessment Design. CSE Report 722.
1
11 29
12
Creating a Complex Measurement Model Using Evidence Centered Design.
4
13
Using Evidence-Centered Design to Develop Advanced Simulation-Based Assessment and Training
6
14 3
15 297
16
Visual detection of clusters in statistical maps
1
17 4
18 10
19 8
20 9

About John T. Behrens

John T. Behrens is a scholar working on Computer Science Applications, Developmental and Educational Psychology and General Psychology, having authored 56 papers that have together received 1.3k indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (13 papers), Online Learning and Analytics (11 papers) and Innovative Teaching and Learning Methods (6 papers). The work is most often cited by research in Computer Science Applications (200 citations), Developmental and Educational Psychology (270 citations) and Experimental and Cognitive Psychology (206 citations). John T. Behrens has collaborated with scholars based in United States, China and United Kingdom. Frequent 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. Their work appears in journals such as Information Sciences, Psychological Methods and Journal of Counseling Psychology.

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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