Jean‐Philippe Pellet

550 total citations
14 papers, 299 citations indexed

About

Jean‐Philippe Pellet is a scholar working on Artificial Intelligence, Computer Science Applications and Education. According to data from OpenAlex, Jean‐Philippe Pellet has authored 14 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Computer Science Applications and 2 papers in Education. Recurrent topics in Jean‐Philippe Pellet's work include Bayesian Modeling and Causal Inference (5 papers), Teaching and Learning Programming (4 papers) and Mathematics Education and Teaching Techniques (1 paper). Jean‐Philippe Pellet is often cited by papers focused on Bayesian Modeling and Causal Inference (5 papers), Teaching and Learning Programming (4 papers) and Mathematics Education and Teaching Techniques (1 paper). Jean‐Philippe Pellet collaborates with scholars based in Switzerland, France and United States. Jean‐Philippe Pellet's co-authors include André Elisseeff, Francesco Mondada, Isabelle Guyon, Peter Spirtes, Morgane Chevalier, Alexander Statnikov, Gregory M. Cooper, Laila El‐Hamamsy, Christian Giang and Bernard Baumberger and has published in prestigious journals such as Computers & Education, Journal of Machine Learning Research and IBM Journal of Research and Development.

In The Last Decade

Jean‐Philippe Pellet

14 papers receiving 280 citations

Peers

Jean‐Philippe Pellet
Louis Massey Canada
Pramuditha Suraweera New Zealand
Penghe Chen China
John DeNero United States
Mihai Boicu United States
Alejandro Ramos-Soto Spain
Dietmar Rösner Germany
Zai Huang China
Sean Welleck United States
Weitao Ma China
Louis Massey Canada
Jean‐Philippe Pellet
Citations per year, relative to Jean‐Philippe Pellet Jean‐Philippe Pellet (= 1×) peers Louis Massey

Countries citing papers authored by Jean‐Philippe Pellet

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐Philippe Pellet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐Philippe Pellet. 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 Jean‐Philippe Pellet. The network helps show where Jean‐Philippe Pellet may publish in the future.

Co-authorship network of co-authors of Jean‐Philippe Pellet

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

All Works

14 of 14 papers shown
1.
El‐Hamamsy, Laila, et al.. (2023). A Research-Practice Partnership to Introduce Computer Science in Secondary School: Lessons from a Pilot Program. ACM Transactions on Computing Education. 23(2). 1–31. 3 indexed citations
2.
Pellet, Jean‐Philippe, et al.. (2023). Informatics in Schools. Beyond Bits and Bytes: Nurturing Informatics Intelligence in Education. Lecture notes in computer science. 1 indexed citations
3.
Pellet, Jean‐Philippe, et al.. (2023). Teachers’ mathematical problem-solving knowledge: In what way is it constructed during teachers’ collaborative work?. The Journal of Mathematical Behavior. 69. 101051–101051. 3 indexed citations
4.
Chevalier, Morgane, Christian Giang, Laila El‐Hamamsy, et al.. (2022). The role of feedback and guidance as intervention methods to foster computational thinking in educational robotics learning activities for primary school. Computers & Education. 180. 104431–104431. 46 indexed citations
5.
El‐Hamamsy, Laila, Barbara Bruno, Morgane Chevalier, et al.. (2020). A computer science and robotics integration model for primary school: evaluation of a large-scale in-service K-4 teacher-training program. Education and Information Technologies. 26(3). 2445–2475. 36 indexed citations
6.
Pellet, Jean‐Philippe, et al.. (2019). Three New Pillars of Digital Education. 1 indexed citations
7.
Pellet, Jean‐Philippe, et al.. (2019). How beginner-friendly is a programming language? A short analysis based on Java and Python examples. 3 indexed citations
8.
Pellet, Jean‐Philippe & Morgane Chevalier. (2014). Automatic extraction of formal features from Word, Excel, and PowerPoint productions in a diagnostic-assessment perspective. 5. 1–6. 1 indexed citations
9.
Brodersen, Kay H., et al.. (2011). Predicting Graduate-level Performance from Undergraduate Achievements.. Educational Data Mining. 357–358. 15 indexed citations
10.
Guyon, Isabelle, Jean‐Philippe Pellet, & Alexander Statnikov. (2010). Development Projects for the CausalityWorkbench. National Conference on Artificial Intelligence. 1 indexed citations
11.
Elisseeff, André, et al.. (2010). Causal networks for risk and compliance: Methodology and application. IBM Journal of Research and Development. 54(3). 6:1–6:12. 2 indexed citations
12.
Pellet, Jean‐Philippe & André Elisseeff. (2008). Using Markov Blankets for Causal Structure Learning. Journal of Machine Learning Research. 9(43). 1295–1342. 130 indexed citations
13.
Pellet, Jean‐Philippe & André Elisseeff. (2008). Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets. 21. 1249–1256. 12 indexed citations
14.
Guyon, Isabelle, et al.. (2008). Design and Analysis of the Causation and Prediction Challenge. 1–33. 45 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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