Sensometrics tutorials

The Sensometric Society in collaboration with the scientific committee of the 18th Sensometrics Conference will organize three sensometrics tutorials on Wednesday 19 of May, 2026. One day previous to the conference. The cost of the tutorial is of 50€ and need to be paid in advance using the conference platform. See bellow in each tutorial description.

The Sensometrics tutorials will have a duration of 3 hours, and each tutorial have a capacity of 24 persons. Space on each tutorial will be limited and early booking is advised. Tutorials will take place at the conference venue (rooms to be comfirmed).

Click in each tutorial section to register, as they are split in morning or afternoon session. 

Tutorials:

Tutorial 1: Analysing relationships among various data blocks using GSCA-SEM

Instructors: Heungsun Hwang, Quoc Cuong Nguyen

Wednesday May 19, at 13h00 to 16h00

Register here

In the analysis of consumer data, researchers are often concerned not only with individual data blocks but also with the interrelationships among them. Insights gained from such multiblock analyses are crucial for product developers and marketers seeking to improve product communication and marketing strategies, particularly for new food products. Structural equation modelling (SEM) has long served as a general statistical framework for relating multiple data blocks. In SEM, constructs are statistically represented as either factors or components, giving rise to two distinct domains: factor-based SEM and component-based SEM. Historically, SEM methods have been applied exclusively within one of these two domains, allowing researchers to estimate models using either factors or components, but not both simultaneously. However, to a dequately capture a broad range of constructs drawn from multiple disciplines, researchers may need to incorporate both factors and components within a single model.

GSCA-SEM (generalised structured component analysis structural equation modelling) is an umbrella term encompassing three related SEM methods—GSCA, GSCA M , and IGSCA—developed to estimate models involving only components, only factors, or a combination of both factors and components, respectively. GSCA-SEM offers substantial flexibility in integrating these two statistical representations of constructs within a unified modelling framework.

This tutorial introduces the conceptual foundations of GSCA-SEM, highlights its distinctions from conventional SEM approaches, and discusses potential methodological extensions. Practical guidance will be provided through hands-on data analysis using GSCA Pro, a free software package available at www.gscapro.com. GSCA Pro features a graphical user interface that allows users to specify models as path diagrams, fit GSCA-SEM models, and obtain results with ease. Upon completion of the tutorial, participants will gain a deeper understanding of how to model and interpret relationships among multiple data blocks using the GSCA-SEM approach.

Duration: 3 hours

Audience: Sensory and consumer scientists who are interested in modelling and interpreting relationships among multiple blocks of consumer data.

Background:  An intermediate level of statistical knowledge is helpful.

Laptop: Attendees are encouraged to bring their personal computers with the latest version of GSCA Pro installed.

Tutorial 2: Introduction to R’s Shiny Applications Through Practical Examples

Instructor: Thierry Worch

Wednesday May 19, at 16h00 to 19h00

Register here

This tutorial provides an exploration into the integration of Shiny applications within the realm of sensory and consumer research using the R programming language. Shiny is an interactive web application framework for R that offers a dynamic and user-friendly environment for visualizing and analyzing data. The tutorial aims to empower researchers to leverage Shiny's capabilities for creating engaging and interactive tools to their needs (e.g. data processing, data analysis, data visualization, reporting, etc.). The tutorial will cover the key aspects of Shiny applications’ development (data processing and visualization, automated reporting) through real-life examples. Participants will gain hands-on experience, enabling them to create custom applications tailored to their needs.

Topics covered will include:

• Introduction to Shiny: An overview of Shiny's architecture and capabilities, with a focus on its relevance to sensory and consumer research.
• Building Interactive Dashboards: Step-by-step guidance on designing and developing interactive dashboards to visualize sensory data, consumer preferences, and trends.
• Data Integration and Processing: Techniques for integrating diverse datasets into Shiny apps, handling data (from processing to analysis/visualization and reporting).
• User Experience: Best practices for creating intuitive and user-friendly Shiny applications.

By the end of the tutorial, participants will possess the skills to harness the potential of Shiny applications for advancing their sensory and consumer research endeavors, ultimately facilitating more impactful data-driven decision-making in this dynamic field.

Duration: 3 hours

Audience: Sensory and consumer scientists who are interested in building their own analysis dashboard using a freely available/open-source software (R/RStudio).

Background: Basic knowledge in R and the tidyverse framework, as well as RStudio is preferred. Basic understanding of statistics is helpful but not required. We will email registered participants before the workshop with some basic setup requirements (R/RStudio software installation).

Laptop: This is a coding workshop, and so we ask all participants to bring a laptop with access to R, RStudio, and some of the relevant packages. We will ask for minimal pre-work (installation of R/RStudio).

Tutorial 3: Liking Data Analysis with XLSTAT: Methods, Applications, and Best Practices

Instructor: Fabien Llobel

Wednesday May 19, at 16h00 to 19h00

Register here

This tutorial provides a practical and comprehensive overview of the main methods used to analyse preference data. Participants will learn how to apply suitable approaches such as visualisation tools, ANOVA, internal preference mapping or cluster analysis techniques devoted to liking data.

Through real-life examples and live demonstrations in XLSTAT, attendees will discover step-by-step workflows for structuring data, running analyses and interpreting results. Special emphasis will be placed on best practices, common pitfalls, visualization strategies, and effective communication of findings to cross-functional teams.

By the end of the tutorial, participants will be able to confidently conduct analyses in XLSTAT, and translate statistical outputs into clear, actionable business recommendations.

Audience: Sensory and consumer scientists interested in understanding and applying preference data analysis using XLSTAT.

Background: Basic understanding of statistics is helpful but not required

Laptop: Required