Professional Values, Decisions and Success:
A Gamified Workshop on Work, Responsibility and Personal Priorities -- in English, 3h
Riccardo Tommasini, Maître de conférences, INSA Lyon, LIRIS
Abstract
This 3-hour workshop invites final-year engineering students to examine the professional and personal values that shape their decisions at work. Rather than approaching values through predefined lists, essays, or abstract debate, the session uses a gamified simulation in which students must make concrete decisions under organisational constraints, incomplete information, and competing priorities. The objective is to make values visible through choices, compromises, refusals, and changing circumstances.
Students work in teams representing different professional environments, including a startup, a large enterprise, an NGO, and a university research group. Within each organisation, students take on roles such as project lead, technical lead, engineer, junior member, operations specialist, or external-relations representative. These roles define responsibilities and perspectives without prescribing what students should value.
The game is structured around several dilemmas shared across all institutions. Situations concern deadlines, recognition, unequal contributions, external opportunities, work-life boundaries, and disagreement with organisational direction. Students first make individual decisions, then negotiate collective decisions as a team. Organisational consequences are tracked via a common dashboard that measures quality, delivery, people, resources, and reputation or impact. Importantly, these dimensions are not combined into a single score: the aim is not to identify a winning organisation, but to reveal what each team has chosen to optimise and what it has been willing to sacrifice.
Throughout the workshop, students maintain a private Game Log that records their decisions, role changes, compromises, vetoes, and moments when a personally significant value became visible. Special response mechanisms distinguish between accepting a group decision, compromising, vetoing a decision that crosses a personal boundary, and abstaining from a discussion when participation would be uncomfortable. This makes the workshop not only a reflection on preferences, but also on the limits of compromise and the relationship between individual agency and collective responsibility.
The final part of the session moves from situational decisions to a more explicit reflection on success. Students compare the organisational outcomes produced during the game with their own criteria for a successful professional life. John Wooden’s Pyramid of Success is presented as an opinionated example of a framework in which success is defined by character, preparation, effort, relationships, and the realisation of one’s capabilities rather than by external achievement alone. Students then formulate their own definition of success and conclude by writing a short personal mission statement describing what they want to contribute, whom or what they want their work to serve, what they want to protect, and what they are unwilling to repeatedly sacrifice in pursuit of professional success.
By the end of the workshop, students will be able to distinguish personal values from professional roles and organizational pressures, identify trade-offs between competing values, recognize their own boundaries for compromise, and articulate a more explicit definition of professional success. More broadly, the session aims to help future engineers approach career choices not only in terms of opportunities, salaries, positions, or prestige, but also in terms of responsibility, autonomy, relationships, integrity, and the kind of professional life they want to construct.
Creativity Across Sciences, Engineering and the Arts: Responsible Data, Algorithms, Models -- in English, 3h
Genoveva Vargas-Solar, CR, CNRS, LIRIS
http://www.vargas-solar.com
Abstract
This 3‑hour tutorial invites advanced engineering students to rethink creativity through both engineering and artistic lenses. Instead of treating creativity as a purely human, artistic, or technical skill, it approaches it as a situated process shaped by constraints, materials, data, models, infrastructures, interpretation, and collective imagination (https://coda-madics.github.io). The goal is to reveal the shared foundations of artistic and scientific creativity: experimentation, abstraction, modelling, exploration, iteration, failure, and the production of new knowledge.
Methodologically, students will analyse creative processes using tools from computer science: problem framing, stakeholder and context analysis, situated data practices, reflexive design, and critical questioning. They will examine how creativity is influenced by available data, categories, models, computational infrastructures, and evaluation criteria.
Technically, the tutorial will draw on concepts from data management, modelling, querying, analytics, and AI. Students will explore how databases, metadata, provenance, knowledge graphs, similarity measures, clustering, classification, generative AI, and explainable AI can support or transform creative practices, and how technical choices make certain patterns visible while obscuring others.
The session will rely on concrete examples at the intersection of art, science, and computing. Students will compare an artistic creative process with an engineering design workflow, identifying common structures: formulating a question, building a corpus or dataset, choosing representations, exploring models, interpreting outputs, and communicating results. They will then design a short data-‑ and AI-driven creative inquiry, specifying data sources, queries, analytical methods, AI tools, evaluation criteria, and ethical or political considerations.
By the end, students will be able to describe creativity as a computationally mediated process, identify methodological bridges between engineering and the arts, and mobilise concepts from data management, analytics, mathematics, and AI to support creative inquiry. More broadly, the tutorial aims to help future engineers develop not only technical expertise but also the capacity to question, interpret, and responsibly design computational systems that shape artistic, scientific, and social creativity.
Research Ethics (Neutrality, Objectivity, Impartiality - Questioning approaches in teaching and research) -- in French, 1h30
Marie-Pierre Escudié, Institut Gaston Berger
L’intention de cet atelier est d’aider à clarifier le positionnement individuel de chaque participant·e.
Contexte :
- La neutralité désigne l’absence totale d’interférence avec le problème abordé. Parler des OGM, ne pas en parler, choisir ses arguments etc. rien de tout cela n’est très neutre en réalité.
- L’impartialité consiste à donner la parole à toutes les parties impliquées, syndicats, gouvernement ou encore ONG. Là encore la perfection est difficile à atteindre.
- L’objectivité renvoie à une connaissance sûre et certaine. Mais bon nombre de paramètres d’une controverse (volatilité, incertitude, ambiguïté, etc.) rendent cet objectif impossible à atteindre.
Déroulé de l’atelier :
- 20 minutes : A) Répartir la lecture des trois concepts entre les membres du groupe ; B) Partage des trois définitions ; C) Echange critique
- 40 minutes : Résolution des différents cas pratiques en mobilisant les trois concepts pour qualifier la situation et proposer une ou des solutions à débattre, en mettant au choix l’accent sur la partie enseignement ou la partie recherche ou les deux. Exemple de cas pratiques :
- Contrat de recherche avec une entreprise d'armement : dois-je accepter ?
- Cas d'undone science: la science qui n'est pas faite me questionne-t-elle ?
- Atelier de prérentrée animé par une entreprise partenaire sur l’IA et ou parrainage de promo par une entreprise : quelle interface de l’enseignant·e dans cette situation ?
- Un·e enseignant·e exprime son avis sur l'extinction de la biodiversité : est-ce acceptable ?
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- 30 minutes : Partage des réflexions et réponses aux cas pratiques
