During the programme

This first module of the Master in Data- Driven Design introduces you to an ever refining digital field in which networks are ubiquitous. With increasingly small sensors in our cities, our houses, our devices, on our skin and even in our bodies, people generate large amounts of data. Advancements in machine learning and artificial intelligence allow us to transform these large amounts of data into valuable information.

This module helps you prepare for your unique position as an intermediary between (academic) analysis and (practical) design. It trains you to fulfill your roles, in which your creative designs facilitate interaction between digital and human domains. Moreover, it teaches you to be aware of the circumstances in which you need to perform your job. The main perspective in this course is to link academic thinking to practical performance.

Digital communication technologies have penetrated many of our daily activities. Reading the newspaper, controlling household appliances, shopping for a pair of jeans, managing bank affairs, communicating with friends and family, monitoring our health, or going on a date. All of these activities, small and large, have been mediatized and digitized due to the digitalization of society. As a result, there is growing need to unravel the influence of media and (communication) technology on individuals, groups and society as a whole.

Media psychology is a burgeoning field, focusing on the psychology behind media and (communication) technology use and impact. Hence, it is also referred to as the “interface between media and the human response”(and in that sense a preparation for block 2: Designing for Interaction, which specifically focuses on interfaces). In New Media Psychology, you will learn to critically assess human interaction with media and (communication) technology, by using a psychological lens. Such a lens is essential in the preparation for your various job roles in various industries that involve mediated communications and information technologies, including but not limited to: media producers, interaction designers, (UX-)researchers, public relations and advertising specialists, content strategist but also health providers, educators and policy makers.

During this course, you will learn the fundamentals of data science. You will learn to program in Python to load, save, collect, scrape, process, clean, transform, analyse and visualize data. At the end of this course, you will know how to critically examine the opportunities and the limitations of data, code and basic algorithms. At the end of the course, you will know how to critically examine the opportunities and the limitations of data, code and basic algorithms. And you won’t be afraid when writing a few lines of code.

This course focuses on the human aspects of the interface: what are the hopes and expectations of the users that download, install, buy and use certain applications? We do not engage in digital media technology for the sake of using technology. We do so because it has something to offer: an experience.

In this course, students will learn to elucidate (a) the concept of user experience and engagement, (b) how they evolve in ecosystems of forces, and (c) how user experience and engagement can be operationalized in such a way that they can be measured. As such, student gain a better understanding of the ways in which a digital concept can be designed to enrich experiences, so that they (continuously) invite people to engage with it.

In the current digital landscape, the design of an interface is of crucial importance. After all, it is through the interface that we establish a meaningful interaction between human and computer. In this course you will learn to design an interface which is usable and delivers a  user experience which is engaging and motivating. Specifically we will focus on Smart interfaces, interfaces using data to personalize and improve the experience.

You will acquire knowledge and experience on user experience and interaction design with the goal to improve your designing skills in designing data- driven applications.

The user interface is at the heart of all data-driven concepts. While interacting with an interface, the user creates interaction data. This interaction data can be direct, e.g., filling in a form or choosing a movie and indirect, e.g., the location of the user or the type of device. These interactions are reciprocal: the user generates data and the data-driven concept in turn communicates with the user. Recommendation systems can be used to illustrate this concept. An interface can suggest which movie to watch, what newspaper article to read, what product to buy or how a game adjusts the level of difficulty. These are all examples of reciprocal interfaces. However, in order to be able to do so, the data-driven concept has to learn from the many user interactions in order to become more valuable over time.

The Fundamentals of Machine Learning course focuses on learning from the constant feedback loops between human and machine. We will employ traditional statistics and machine learning to analyse these feedback loops.

The process of digitization fundamentally changes the heart of any organization, whether it is a city, a government or a small company. This course is about how to initiate and deal with the digital transformation and scalability of organizations. At the same time, this course aims for a broader perspective: How will not just organizations but entire domains such as healthcare, journalism, education, politics, entrepreneurship, retailing, mobility change? What are the new business models? How can organizations create actual value for users and society and a what price?

There are many promises. Technologies such as Blockchain allow us to build decentralized networks that facilitate and capture any (value) exchange and that, via smart contracts, secure agreements and establish trust. On top of this decentralized network, dApps (decentralized applications) roam free. Holochain is already seen as the successor of Blockchain, offering an open-source framework for building distributed, peer-to-peer applications. In this module, you will learn how the right allocation of creativity, value, and technology may strengthen core processes. If these core processes are indeed well chosen, the combination of almost unlimited computation and (user) interaction may result in organizations and networks that scale. It is the combination of these kinds of strategies and technologies that gradually will lead to new kinds of Decentralized Autonomous Organizations (DAO’s).

Welcome to Creative Research, a course designed to prepare you for your graduation. The importance of preparation has been stressed in many familiar quotes, such as “Success occurs when opportunity meets preparation”, “By failure to prepare, you are preparing to fail”, and “Before anything else, preparation is the key to success”.

As you can imagine, this is a challenging task which requires a lot of preparation, dedication and hard work. For this reason, you already start the graduation process in Block C, by writing a convincing and feasible graduation proposal (i.e., a road map to guide you during the final stage of your education). The course Creative Research will support your writing process, and includes sparring on concept development and scoping, support in scholarly research (academic reading, writing, literature search, APA), methodology workshops, research planning and analytical thinking. In essence, the course focuses on writing a preliminary version of your academic paper: the more effort put into writing and planning during this course, the more time you have left during Block D to deliver a “kick-ass” academic paper and prototype that you are proud of!

The course State of the Art of Technology focuses on new technological innovations and how to quickly master them for your research. During this course students will master one technology whilst playing, experimenting, searching for the edges of the possibilities and pushing the limits of technology. Examples of state of the art technologies are deep learning algorithms (image recognition, natural language processing such as BERT, voice processing), voice controlled interfaces, augmented interfaces, extended reality, smart cities / IoT and quantum computing.

Students will become creative scientists and autonomous critical makers.

This course starts with a three week 'Technology Road Show'. During the Technology Road Show we will see and work with the latest technology, for example XR, Blockchain, IoT, Cloud/edge computing, AI, Smart Cities and natural interfaces. We will visit technology companies to work with the latest tech. Guest speakers will talk about ethics, innovation and what the job (your job) of a data wrangler/scientist/artist can look like. You will be assigned to learning teams to whom you present your progress (in a non-formal form) and discuss your difficulties (what do you need to continue) with.

In the graduation project, students show that they have become confident discourse participants with a sound academic understanding of datafication and the digital transformation but also practice-focused designers of data-driven solutions.

The learning goals include:

• the ability to research, analyse and understand the use of data in specific contexts of use;
• to develop data-driven concepts that fit the research problem and are potentially scalable for value-creation;
• to develop and test a data-driven prototype built in code with an engaging interface;
• to critically evaluate the development process and the potential impact of the proposed prototype on the domain in focus;
• to communicate this clearly to diverse audiences of relevant stakeholders.