Educational Innovation
Orientation
Educational innovation is used here for a focused purpose: designing active, reproducible, and supported learning environments where digital tools support understanding rather than replacing it.
My projects are organized around three priorities: modernizing courses with open technologies, structuring student support, and integrating artificial intelligence within supervised teaching settings.
Main projects
Courses
Redesign of data science courses
Revision of introductory data science and scientific programming courses to strengthen case studies, practice with R and Quarto, and reproducible reporting.
Goals: contextualize learning, develop francophone case studies, provide formative feedback, and make workflows more explicit.
Student success
Training and resources for teaching assistants
Development of a support model for teaching assistants and an internal platform gathering shared resources, short videos, and procedures.
Supervised AI
GPT-CDA project
Development of a specialized conversational assistant to support reasoning in mathematics and statistics, use course notation, and redirect students to a human tutor when human support is preferable.
Open resources
site_ressources_SSD platform
Online library of Quarto templates, interactive tutorials, reproducible examples, GitHub procedures, and resources for data science teaching.
Educational software
tutorizeR
R package that automates conversion of .qmd or .Rmd documents into interactive tutorials for learnr or quarto-live, with conversion reports and feedback mechanisms.
Interactive tutorials
Interactive tutorials built with learnr allow students to manipulate R code in a guided environment with exercises and feedback.
Art, mathematics, and data
The Digital Drawing with R project explores the graphical potential of R and ggplot2 for producing generative images based on statistical processes. This work connects visualization, creative programming, and reproducible resources.
Outreach
I regularly share my practices in conferences and workshops devoted to university teaching, data science, and open digital tools.
- SSC 2026 - AI and teaching workshop: public gallery of prompts, teaching activities, AI-use rules, and reusable verification routines.
- EIOM 2025 - Statistical modeling workshops and website.
- ASSQ 2025 - What is new in data science?.
Guiding principle: connect statistical rigor, student autonomy, and reproducible resources.