Teacher(s)
Language
French
Main themes
- Theoretical frameworks and disciplines for prototyping: (rapid) contextual design, rapid prototyping, cognitive engineering, usability engineering, agile method
- Interrelation between the design and evaluation processes of systems, products, and Web services
- Methodological principles used in prototyping: design and evaluation methods, prototyping techniques, user testing, validity of user tests, data collection
- Specificities of user testing compared to other empirical research methods such as interviewing, observation, laboratory experimentation, A/B testing, etc.
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | Explain and make connections between the different concepts associated with prototyping. |
| 2 | Compare different prototyping techniques in terms of specific objectives, expected results, procedures, constraints (time, resources, budget). |
| 3 | Select and sequence several prototyping techniques to produce a web prototype iteratively and incrementally |
| 4 | Effectively conduct a series of user tests to improve the Web prototype. |
| 5 | Analyze the relevance of the data collected and reorganize if necessary the experimental protocol used in the user tests. |
| 6 | Justify and argue the choice of design (prototyping) and evaluation (user testing) methods. |
Evaluation methods
Evaluation is based on continuous assessment, with no examination session.
- Continuous assessment: individual written knowledge test (40%) and project (60%), comprising an individual component (20%) and a group component (40%).
- September session: individual tailored assignment, based on the activities that were not passed, to be submitted on the first day of the session.
- Permitted without disclosure: language assistance; exploration and ideation; literature research. References must have been consulted and analyzed by the students and may not be used solely on the basis of a response provided by an AI tool.
- Permitted with disclosure: quantitative and qualitative data analysis; figure generation; generation, correction, or adaptation of computer code (Python, R, etc.). For these uses, students must indicate the tool used and provide a link to the conversation as well as the complete prompts. A non-functional link or a link that does not allow the declared use to be verified will result in a grade of 0 for the work concerned.
- Prohibited: simulation of participants; generation of data instead of actual data collection; and, more generally, any use of AI that would prevent the assessment of the student’s own knowledge, skills, and work process.
Faculty or entity
