Guillaume Durand

547 citations
42 papers · 321 indexed · h-index 9

Guillaume Durand

39 papers receiving 301 citations

Peers

Guillaume Durand
Comparison fields: 5 of 75
  • Computer Science Applications 125
  • Developmental and Educational Psychology 58
  • Clinical Psychology 86
  • Information Systems 71
  • Artificial Intelligence 73
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Jihyun Park South Korea
Mariel Musso Argentina
Marta Peña Spain
Tatsunori Matsui Japan
Yoshiko Goda Japan
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Citations per year

Countries citing papers authored by Guillaume Durand

Since Specialization
Citations

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

Fields of papers citing papers by Guillaume Durand

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Guillaume Durand, 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 Guillaume Durand Line = papers co-authored together Guillaume Durand links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20240
4 20221
5 20221
6 20211
7
Confident Learning Curves in Additive Factors Modeling.
20201
8
Standard error considerations on AFM parameters.
20181
9 20184
10 20188
11 20184
12 20175
13
A Probabilistic Model for Knowledge Component Naming.
20150
14
A Binary Integer Programming Model for Global Optimization of Learning Path Discovery.
201415
15 20122
16 20104
17 200911
18
Toward Simple Learning Design 2.0 Simple interoperability for learning activities
20092
19
LDL: a Language to Model Collaborative Learning Activities
200616
20
To Scenarize the Assessment of an Educational Activity
20062

About Guillaume Durand

Guillaume Durand is a scholar working on Computer Science Applications, Clinical Psychology and Developmental and Educational Psychology, having authored 42 papers that have together received 321 indexed citations. Recurring topics across this work include Psychopathy, Forensic Psychiatry, Sexual Offending (13 papers), Personality Disorders and Psychopathology (11 papers), Intelligent Tutoring Systems and Adaptive Learning (7 papers), Innovative Teaching and Learning Methods (6 papers), Personality Traits and Psychology (6 papers), Open Education and E-Learning (5 papers), Topic Modeling (3 papers) and Stalking, Cyberstalking, and Harassment (3 papers). The work is most often cited by research in Computer Science Applications (125 citations), Developmental and Educational Psychology (58 citations) and Clinical Psychology (86 citations). Guillaume Durand has collaborated with scholars based in Canada, Netherlands and United States. Frequent co-authors include Nabil Belacel, Hélène Fournier, Rita Kop, Stephen Downes, Serge Léger, Laurence Vignollet, Dan Tulpan, Joana De Calheiros Velozo, Cyril Goutte and Y. Choquette. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Marine Pollution Bulletin.

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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