The majority of data scientists are working for humans. It is challenging to determine how to use and present big data in innovative products and services in order to create good user experiences and support users’ choices that are in line with their – often unknown – values, needs and motivations. Such innovative designs require entrepreneurs to think creatively, acquire a deep understanding of their future users and apply innovation processes that integrate human values, technological feasibility and business goals. |
- To understand cognitive mechanisms related to human behavior, creativity, decision making, and human experiences
- To conduct research on existing data sets from a cognitive science perspective as input for creative/innovative design of new apps, services or visualizations
- To apply tools to identify user needs and to create user experiences for innovative products & services
- To understand and apply design thinking as a process towards innovative products & services (e.g. human-centered design process)
Students will work in groups over the entire course. These groups will work together during the different activities of this course. The course consists of four different type of activities:
- Design workshops
- Feedback sessions
- Professional skills
1. Lectures focus on theoretical background of cognitive science and applications to data science. Students are expected to come prepared to the lectures by reading relevant chapters or papers. Lectures are followed with discussion sessions on relevant academic papers.
2. Discussions focus on the application of cognitive science theories into topics relevant for data science, by studying and discussing relevant papers. Students prepare by reading a paper and post discussion points prior to the discussion meeting. In their discussion points, students try to integrate knowledge from the lectures in discussing the paper. Discussion points are peer-reviewed by fellow students prior to the debate to provide peer-feedback and graded by the teacher after the debates.
One group will chair and prepare the meeting using the discussion topics as posted by the students.
3. Design Workshops: During the semester the groups will work towards an innovative design of a new app, services or visualization. As part of the design process, students will analyze existing datasets from a specific cognitive science perspective to identify new innovative services or products. These analyses will help the ideation face in the design thinking part of the course. We will provide several topics related to current research projects at JADS (for example sensor data or recommender systems). Data and theory in cognition will act as inspiration for this process. Further steps will follow the user-centered design process in which the prototype is developed based on users’ and stakeholders’ requirements and validated with users. The outcome is not expected to be fully functioning software, but rather a prototype which can demonstrate the main activities with good quality and something which e.g. could be presented to investors. To support students in their design process, workshops combine theory and hands-on activities. These workshops go through the entire design cycle: 1. doing (qualitative) user research, 2. analyzing the resulting data , 3. ideation and concept design based on the findings, 4. prototyping the resulting idea(s), and subsequently repeating the cycle again by gathering users’s responses to the prototype, analyzing the results, etc.
4. Feedback sessions: as students work on the design project, we will have several opportunities for students to discuss their progress and get feedback from their peers and the teachers. These will typically involve a short presentation from each group followed by time for questions & feedback.
5. Professional skills: as part of the professional skills in the master, you will be able to follow a workshop on interviewing and a workshop on ideation, outside the regular lecture hours. These skills will be assessed separately.