PhD Open Position in Toulouse (France)

/ 4 junio, 2025

Os reenviamos información sobre una oferta de doctorado en Toulouse sobre los efectos de la inteligencia artificial en la regulación del aprendizaje y la carga cognitiva.

La Junta Directiva de la SEPEX

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PhD Open Position in Toulouse (South of France)


Topic: Thesis on the Effects of Generative Artificial Intelligence on Learning Regulation and Cognitive Load Funding: CNRS (National Scentific Center in France) – https://www.cnrs.fr/fr
Laboratories in Toulouse City (South of France):
Host Laboratory – CLLE (Cognition, Language, Ergonomics Laboratory), https://clle.univ-tlse2.fr/
IRIT (Institute of Research in Informatics of Toulouse), https://www.irit.fr/
Supervisors:
– Franck Amadieu, Professor et Director of CLLE, < franck.amadieu@univtlse2.fr >, website
– Mar Pérez-Sanagustín, Associate Professor at IRIT, TALENT Team, < mar.perez-sanagustin@irit.fr >, website
Salary: 2.200€/months (Gross Salary) during 2025 ; 2.300€/months during 2026.

The salary includes health coverage (through the French social security system) and paid vacation (6 weeks, with the possibility of negotiation for more).

Required Qualifications: Master Studies in Cognitive Psychology or related areas

Duration: 36 Months (Extendable under conditions) Starting date 1st October 2025

About the Host Institution
The CLLE laboratory is an interdisciplinary UMR in cognitive science at the University of Jean Jaurès (https://www.univtlse2.fr/). The recruited candidate will join the Language and Cognitive Processes team and will be part of the Education and Learning research theme. While primarily based at CLLE, the candidate will also be affiliated with the IRIT computer science laboratory in Toulouse, within the TALENT team. The PhD will be co-supervised by Franck Amadieu (Professor of Cognitive Psychology at CLLE) and Mar Pérez-Sanagustín (Associate Professor in Computer Science at IRIT and Pedagogical Innovation Officer at ANITI). The recruited candidate will work primarily at the CLLE laboratory, but also at IRIT with the TALENT team. They will carry out data collection both in the field with students and in laboratory settings. The candidate will also be expected to travel to national and international scientific conferences.

Description of the Thesis Objectives
The recruited candidate will carry out a three-year PhD project focused on the use of artificial intelligence to support learners in regulating their learning processes and cognitive load during learning activities. It is now well established that students increasingly rely on generative AI tools in their daily learning tasks, particularly chatbots based on large language models. While recent studies emphasize the importance of regulating these interactions to promote effective learning, few empirical investigations have thoroughly analyzed student-AI collaboration. Research on self-regulated learning and cognitive load suggests that certain technological tools can support these processes and provide a solid theoretical foundation for their study. AI, in particular, may facilitate self-regulation through personalized feedback. This project builds on a recent model describing the interactions between cognitive load and self-regulated learning (Wang & Lajoie, 2023 ; Wang et al., 2023), and aims to understand how AI can assist learners by analyzing their behavior and cognitive load, in order to guide them toward reducing unnecessary cognitive load and enhancing both self-regulatory processes and productive cognitive engagement.

The PhD candidate will work on two main objectives:

Objective 1: Investigating the effects of an intelligent chatbot system that delivers personalized feedback for regulating cognitive load during a learning task, and identify the most effective forms of interaction for supporting self-regulation (considering reported variations in cognitive load and learner performance).

Objective 2: Understanding the interrelations between cognitive load and self-regulated learning that are most conducive to effective learning in tasks supported by chatbots based on large language models.

For more details about the project: https://sites.google.com/view/franck-amadieu/projets/projet-aire

References

  • Wang, T., & Lajoie, S. P. (2023). How does cognitive load interact with self-regulated learning? A dynamic and integrative model. Educational Psychology Review, 35(3), 69.
  • Wang, T., Li, S., Tan, C., Zhang, J., & Lajoie, S. P. (2023). Cognitive load patterns affect temporal dynamics of self-regulated learning behaviors, metacognitive judgments, and learning achievements. Computers & Education, 207, 104924.

Activities

The recruited candidate will carry out experimental research, which will involve:

  • Conducting a systematic literature review on AI-supported learning, as well as on the regulation of learning and cognitive load
  • Designing experimental protocols
  • Conducting experiments with learner populations for data collection
  • Performing data analyses
  • Carrying out inferential statistical analyses
  • Writing scientific articles o Presenting research at scientific conferences
  • Participating in regular research meetings with the teams involved in the project
  • Collaborating with international partners

Required Competencies

  • Knowledge in cognitive science (primarily cognitive psychology)
  • Familiarity with the experimental method
  • Understanding of learning processes
  • Ability to conduct an experiment (designing protocols, analyzing data)
  • Ability to perform inferential statistical analyses
  • Ability to report scientific results
  • Ability to present one’s work
  • Ability to produce meeting reports
  • Openness to other research conducted within the lab
  • Rigor and attention to detail

Application: Application by the CNRS web site: https://emploi.cnrs.fr/Offres/Doctorant/UMR5263-FRAAMA1001/Default.aspx?lang=EN

Deadline for Application: 23th June

Auditions Planned (might vary): 24 June – 30 June

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