Master of Science (MSc) – User Experience

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.

- 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.

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.

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

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

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