Benjamin M. Rottman

978 total citations
49 papers, 572 citations indexed

About

Benjamin M. Rottman is a scholar working on Developmental and Educational Psychology, Artificial Intelligence and General Decision Sciences. According to data from OpenAlex, Benjamin M. Rottman has authored 49 papers receiving a total of 572 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Developmental and Educational Psychology, 16 papers in Artificial Intelligence and 12 papers in General Decision Sciences. Recurrent topics in Benjamin M. Rottman's work include Child and Animal Learning Development (19 papers), Bayesian Modeling and Causal Inference (13 papers) and Decision-Making and Behavioral Economics (12 papers). Benjamin M. Rottman is often cited by papers focused on Child and Animal Learning Development (19 papers), Bayesian Modeling and Causal Inference (13 papers) and Decision-Making and Behavioral Economics (12 papers). Benjamin M. Rottman collaborates with scholars based in United States and Australia. Benjamin M. Rottman's co-authors include Reid Hastie, Frank C. Keil, Woo‐kyoung Ahn, Charles A. Sanislow, Nancy S. Kim, Micah B. Goldwater, Dedre Gentner, Timothy J. Nokes‐Malach, Alicia H. Chang and Catherine M. Sandhofer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Psychological Bulletin and PLoS ONE.

In The Last Decade

Benjamin M. Rottman

43 papers receiving 528 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Benjamin M. Rottman United States	12	213	173	104	85	68	49	572
Valerie Thompson United States	12	85 0.4×	60 0.3×	43 0.4×	97 1.1×	20 0.3×	36	397
J. Isaiah Harbison United States	11	204 1.0×	106 0.6×	52 0.5×	63 0.7×	166 2.4×	23	636
Daniel A. Wilkenfeld United States	10	82 0.4×	78 0.5×	37 0.4×	17 0.2×	58 0.9×	29	422
Laura Macchi Italy	12	98 0.5×	133 0.8×	15 0.1×	294 3.5×	77 1.1×	37	567
Amber Sprenger United States	10	94 0.4×	127 0.7×	16 0.2×	104 1.2×	139 2.0×	19	522
Ion Yarritu Spain	8	83 0.4×	28 0.2×	26 0.3×	82 1.0×	47 0.7×	12	371
David P. O'Brien United States	14	343 1.6×	301 1.7×	18 0.2×	165 1.9×	97 1.4×	38	682
Jean-Paul Caverni France	9	119 0.6×	130 0.8×	15 0.1×	173 2.0×	69 1.0×	21	505
Michaël Bishop United States	15	41 0.2×	34 0.2×	39 0.4×	48 0.6×	88 1.3×	55	684
Daniel Hausmann Switzerland	9	51 0.2×	50 0.3×	15 0.1×	101 1.2×	74 1.1×	12	447

Countries citing papers authored by Benjamin M. Rottman

Since Specialization

Citations

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

Fields of papers citing papers by Benjamin M. Rottman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin M. Rottman. 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 Benjamin M. Rottman. The network helps show where Benjamin M. Rottman may publish in the future.

Co-authorship network of co-authors of Benjamin M. Rottman

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

All Works

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20 of 20 papers shown

Nokes‐Malach, Timothy J., et al.. (2023). Cognitive perspectives on maintaining physicians’ medical expertise: V. Using a motivational framework to understand the benefits and costs of testing. Cognitive Research Principles and Implications. 8(1). 64–64. 3 indexed citations

Fraundorf, Scott H., et al.. (2023). Cognitive perspectives on maintaining physicians’ medical expertise: III. Strengths and weaknesses of self-assessment. Cognitive Research Principles and Implications. 8(1). 58–58. 3 indexed citations

Fraundorf, Scott H., et al.. (2023). Cognitive perspectives on maintaining physicians’ medical expertise: II. Acquiring, maintaining, and updating cognitive skills. Cognitive Research Principles and Implications. 8(1). 47–47. 10 indexed citations

Rottman, Benjamin M., et al.. (2023). Cognitive perspectives on maintaining physicians’ medical expertise: I. Reimagining Maintenance of Certification to promote lifelong learning. Cognitive Research Principles and Implications. 8(1). 46–46. 4 indexed citations

Fraundorf, Scott H., et al.. (2023). Cognitive perspectives on maintaining physicians’ medical expertise: IV. Best practices and open questions in using testing to enhance learning and retention. Cognitive Research Principles and Implications. 8(1). 53–53. 5 indexed citations

Zhang, Yiwen & Benjamin M. Rottman. (2023). Causal learning with delays up to 21 hours. Psychonomic Bulletin & Review. 31(1). 312–324. 2 indexed citations

Rottman, Benjamin M., et al.. (2021). Investigating causal inference difficulties with a simple, qualitative force-and-motion problem. The Physics Video Demonstration Database (Cornell University). 197–202.

Kuo, Eric, et al.. (2020). Using Causal Networks to Examine Resource Productivity and Coordination in Learning Science.. ICLS. 1 indexed citations

Rottman, Benjamin M., et al.. (2019). The Accuracy of Causal Learning over 24 Days.. Cognitive Science. 3107–3113.

10.

Rottman, Benjamin M., et al.. (2018). Causal Learning from Trending Time-Series.. Cognitive Science.

11.

Rottman, Benjamin M., et al.. (2018). Causal strength induction from time series data.. Journal of Experimental Psychology General. 147(4). 485–513. 13 indexed citations

12.

Rottman, Benjamin M., et al.. (2016). Causal Learning With Continuous Variables Over Time.. Cognitive Science. 2 indexed citations

13.

Rottman, Benjamin M., et al.. (2016). Temporal Causal Strength Learning with Multiple Causes.. Cognitive Science.

14.

Rottman, Benjamin M., et al.. (2015). Elemental Causal Learning from Transitions.. Cognitive Science. 4 indexed citations

15.

Rottman, Benjamin M.. (2014). Information Search in an Autocorrelated Causal Learning Environment. Cognitive Science. 36(36). 1 indexed citations

16.

Rottman, Benjamin M., et al.. (2014). Learning Causal Direction from Transitions with Continuous and Noisy Variables. Cognitive Science. 36(36). 2 indexed citations

17.

Rottman, Benjamin M. & Frank C. Keil. (2011). Learning Causal Direction from Repeated Observations over Time. Cognitive Science. 33(33). 4 indexed citations

18.

Rottman, Benjamin M. & Frank C. Keil. (2010). Connecting Causal Events: Learning Causal Structures Through Repeated Interventions Over Time. eScholarship (California Digital Library). 32(32). 1 indexed citations

19.

Rottman, Benjamin M., Nancy S. Kim, Woo‐kyoung Ahn, & Charles A. Sanislow. (2010). Can Personality Disorder Experts RecognizeDSM-IVPersonality Disorders From Five-Factor Model Descriptions of Patient Cases?. The Journal of Clinical Psychiatry. 72(5). 630–639. 15 indexed citations

20.

Gentner, Dedre & Benjamin M. Rottman. (2006). Expertise Effects on Sorting Strategies of Causal Phenomena. eScholarship (California Digital Library). 28(28). 1 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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