Maîtrise en gestion (M. Sc.) – expérience utilisateur

Distinction between descriptive statistics and inference
Useful digital and visual indicators in UX
Sampling and data quality
Point estimation
Hypothesis tests
Effect sizes

Comparison of two means (parametric and non-parametric tests)
Comparison of several means from independent samples (parametric and non-parametric tests)
Two-factor ANOVA

Theoretical foundations of UX design
User-centered design in collaboration with all stakeholders including end-users
Implementation of the iterative design according to divergent (broad innovation) and convergent (concrete innovation) modes
Management of ideation activities in a "Lean" and Agile development framework
UX communication and support through the ideation phase
Multi-disciplinary collaborative work with the team upstream and downstream of the ideation phase

Managing a user experience project in a business context
Drafting of the mandate
Design of test plan and experiment
Identification of instruments and metrics relevant to the measurement of the user experience
Recruitment of participants
Realization of the data collection
Data analysis
Writing and presenting the evaluation report

UX maturity
UX strategy
UX teams structure
UX operations
UX culture
UX control

Theoretical bases of interface ergonomics
Implementation of the user interface design
Implementation of prototype development of all fidelity levels
Management of prototyping and UX evaluation activities in a "Lean" and Agile development framework
UX communication and support for the team throughout the prototyping phase

- Research types (descriptive predictive causal)

- Concepts of Measure reliability and validity

- Qualitative research concepts and methods in UX

- Quantitative research concepts and methods in UX

- Introduction to web analytics

Define a user research problem and identify the research steps necessary to resolve the problem.

Identification of the advantages and disadvantages of data collection methods considering the needs of the research team and the context.

Implementation of quantitative and qualitative research methods to collect user data (eg interviews task analysis)

Data analysis particularly from advanced UX methods (eg facial emotions).

Development of practical tools for the creation and implementation of a UX research process taking into account issues related to the industry the organization and the research team.

Multi-method approach in gathering and synthesizing design requirements
User-Centered Design in collaborating with design team members and end users
Management and organization of information to be made available on the digital artifact (i.e. Information Architecture)
Implementation of an iterative agile design of the digital interface ranging from prototype to the final version
Innovation and recent research related to interface design.

Multi-method approach in UX evaluation
User-centered evaluation in collaboration with stakeholders including team members clients and end users
Implementation of an agile evaluation process for testing a digital artifact
Development of evaluation protocols implementation of UX assessments interpretation of collected data and generation of takeaways for the benefit of clients
Advanced evaluation paradigms (e.g. accessibility; conformity; quality assurance) and methodology (e.g. remote testing and neuroscientific testing)
Management of the evaluation lifecycle
Innovations in UX evaluation.

- Define a user research problem and identify the research steps necessary to resolve the problem.
- Identification of the advantages and disadvantages of data collection methods considering the needs of the research team and the context.
- Implementation of quantitative and qualitative research methods to collect user data (eg interviews task analysis)
- Data analysis particularly from advanced UX methods (eg facial emotions).
- Development of practical tools for the creation and implementation of a UX research process taking into account issues related to the industry the organization and the research team.

Becoming familiar with scientific research and the M.Sc thesis in UX
Initiating the research: exploring avenues and specifying a research topic
Translating problems from industry into a scientific project
Motivating the research and formulating a research question
Reviewing the literature and conceptualizing a research problem
Using and developing theory in the thesis
Planning the empirical investigation
Understanding and respecting ethical and responsible research practices
Validating the consistency between the research intents the empirical plans and the practical problem being addressed.
Communicating research results to the relevant stakeholders

- The emergence of Western modern society
- The model of modern Western society and its social and environmental implications
- The economic and social foundations of business organizations
- The individual and collective driving forces of business organizations
- The business organization in the face of major social and environmental challenges

Characteristics of an e-commerce platform: Key features and their connection to the consumer lifecycle.
Industry and key stakeholders.
Business models and types of e-commerce platforms (e.g. online stores dropshipping marketplaces such as Amazon Etsy Fab Wanelo).
Review of three key concepts: Modularity customization and configuration.
Integration with internal management systems (synchronous asynchronous).
Understanding and critiquing new trends: Integration with social media (social commerce) and with other sales channels such as mobile or brick-and-mortar stores.

Business Model Canvas and the reality of mobile business.
Technologies and Possible Implementation Types: Hybrid native and progressive web apps.
Designing the Mobile User Experience: Understanding the limitations constraints and benefits of an effective design in a mobile context.
Organizational Perspective: How companies structure themselves to manage mobile app development.
Challenges expertise best practices and new team management methods.
Marketing a Mobile Application according to different scenarios and business realities.

Management of a UX research project
Preparation of data collection
Data collection
Writing the methodology
Data analysis
Writing the results
Writing the discussion

1. Human-Computer Interaction
2. Human Factors
3. Perception and cognition
4. Attention and memory
5. Usability engineering
6. User-centered design
7. Social aspects of HCI
8. Privacy and security
9. Ethics and responsibility
10. The dark side of HCI
11. Human-Centered Artificial Intelligence
12. Immersive Environments and Experiences
13. Research methods
14. Research papers and grant proposals
15. Disciplinary differences in HCI

1- Neuroscience methods in IT research: It includes research based on all types of neurophysiological tools such as functional magnetic resonance imaging (fMRI) electroencephalograhy (EEG) fNIRS (functional near-infrared spectroscopy) electromyography (EMG) hormone assessments physiological measures (e.g. skin conductance and heart rate measurement) and molecular genetics.

2- Topics of applications in IT: NeuroIS literature shows that papers address the following topics among others: employment of neurophysiological knowledge and tools to examine trust technostress website design technology adoption human-computer interaction emotions in e-commerce information behavior IS design science mental workload social networks usability software development and business process modeling and enterprise systems. Also software prototypes of NeuroIS applications which use bio-signals (e.g. EEG skin conductance pupil dilation) as system input are an essential topic in the field; such systems are referred to as neuro-adaptive information systems. Methodological and ethical discussions are also critical.

Introduction of Web Analytics and Business Models
Benefits and Applications of Web Analytics
Google Analytics: Introduction and Application
Clickstream Data Analysis and Applied Metrics
Electronic Commerce Models
Software As A Service Models
Social Media Models
Search Engine Optimization (SEO)
Customer Journey and UX Research
A/B testing and Website Experimentation
Analytics Dashboards and Visualization