Doug Markant

428 citations
7 papers · 232 · h-index 5

Impact in

Papers in

    • Machine Learning and Algorithms 2
    • Artificial Intelligence in Games 1
    • Intelligent Tutoring Systems and Adaptive Learning 1
    • Educational Assessment and Pedagogy 1

Doug Markant

6 papers receiving 211 citations

Peers

Doug Markant
Comparison fields: 5 of 62
  • General Decision Sciences 26
  • Computational Mathematics 4
  • Cognitive Neuroscience 88
  • Developmental and Educational Psychology 40
  • Computer Science Applications 14
Replace Danilo Fum with:
Danilo Fum Italy
Shawn Betts United States
Frederick Callaway United States
Hee Seung Lee South Korea
Anna Coenen Germany
Lee-Xieng Yang Taiwan
Mayank Agrawal India
Yunn-Wen Lien Taiwan
Dan Bothell United States
Mark Blokpoel Netherlands
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Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Doug Markant

Since Specialization
Citations

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

Fields of papers citing papers by Doug Markant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Doug Markant, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Doug Markant Line = papers co-authored together Doug Markant links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2015141
2 200842
3
Active learning strategies in a spatial concept learning game
200926
4
Category Learning Through Active Sampling
201014
5 20198
6
The impact of biased hypothesis generation on self-directed learning.
20161
7
Navigating the "chain of command": Enhanced integrative encoding through active control of study.
20190

About Doug Markant

Doug Markant is a scholar working on Artificial Intelligence, Education, Developmental and Educational Psychology, Statistics and Probability and Pediatrics, Perinatology and Child Health, having authored 7 papers that have together received 232 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (2 papers), Artificial Intelligence in Games (1 paper), Fetal and Pediatric Neurological Disorders (1 paper), Intelligent Tutoring Systems and Adaptive Learning (1 paper), Statistics Education and Methodologies (1 paper), Behavioral Health and Interventions (1 paper), Educational Assessment and Pedagogy (1 paper) and Advanced Neuroimaging Techniques and Applications (1 paper). The work is most often cited by research in General Decision Sciences (26 citations), Computational Mathematics (4 citations), Cognitive Neuroscience (88 citations), Developmental and Educational Psychology (40 citations) and Computer Science Applications (14 citations). Doug Markant has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Todd M. Gureckis, Anna Coenen, Alexander Rich, Jay B. Martin, John V. McDonnell, Jessica B. Hamrick, Patricia P. Chan, David Halpern, Nancy J. Lobaugh and Stephanie H. Ameis. Their work appears in journals such as Cognitive Science, NeuroImage, Behavior Research Methods, The MIT Press eBooks and eScholarship (California Digital Library).

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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