The neurodesign work-group offers a portfolio of classes. All of them teach skills of creativity, innovation and collaboration. As an attendee of the classes you learn to conduct and manage your own creative processes in the field of digital engineering. You have great freedom to decide what topic you want to work on, and then the class offers process and community support to help you realize your vision, so that you can achieve astonishing solutions in your creative endeavour.
Beyond the overarching aim of facilitating creativity in engineering, each class pursues more specific purposes:
The lecture Design Thinking for Digital Engineering is concerned with theories and empirical research on design thinking (creativity, innovation, collaboration). Insights from research are probed and furthered in the domain of Digital Engineering. Attendees can choose to work in one or more of the following areas: creative people, creative processes, creative places and/or innovation modelling. This course was taught in 2018 for the first time. A sample project conducted in class analyses artefacts from digital engineering projects (e.g., e-mails, sketches, prototypes) and automatically captures some measures from different phases of the creative process, to predict characteristics of final project outcomes.
TheNeurodesign Seminar teaches research methodology and statistics both from social science and neuroscience. You learn to collect and analyse body-related data (EEG, fMRI, skin conductance, heart rate, body motion, eye gaze, facial emotion expression etc.). You become acquainted with varying devices to measure these parameters, learn to conduct experiments, quasi-experiments and time-series analyses. Creative projects in class work in some way with body-related data. A sample project in class explored what activity and mental state of the user could be detected based on measurements of the user’s eye gaze when looking at the computer screen.
The Neurodesign Lecture conveys insights from neuroscience regarding creativity, collaboration and innovation. Guest experts, who are leading scholars in their fields, provide an overview of their work domains and share latest research results. Participants learn to build on neuroscientific insights for purposes of worthwhile engineering innovation. From year to year, each lecture has a different focus topic. In 2019 a major emphasis was placed on the neuroscience of collaboration. In 2020 the topic was artificial intelligence and the neuroscience of creativity. In 2021 (upcoming in the winter semester) it is the neuroscience of empathy. A sample project that emerged from the Neurodesign Lecture harnessed the research insight of improved team collaboration after joint-coordinated body motion. In this sense, a warm-up exercise delivered via Nintendo Switch in remote interaction was found to improve remote team collaboration afterwards.
Further classes such as Visual Thinking and Sonic Thinking emerge from design thinking theory: In human-computer-interaction, team-collaboration or the process of developing novel engineering solutions, people use different representation systems to process information. For instance, information can be processed by means of visual thinking (working with images, 3D-models…), sonic thinking (working with sound) or symbolic thinking (working with mathematical expressions, verbal language or computer code). Over decades design thinking pioneers have probed the ways in which innovation projects are impacted by the choice of representation systems (McKim, 1972; Adams, 1974; von Thienen et al., 2021). A major research insight has been that people excel at problem solving and innovation when they are versatile in different representation systems, and choose these mindfully, sometimes alternating over time.
The seminar Visual Thinking is related to the design thinking motto “Be visual!” It provides experiences, skills and theory with regard to seeing, visual imagination, and idea/data visualization. The seminar was taught at the HPI in 2019 for the first time. At Stanford University, classes on Visual Thinking have been introduced by design thinking pioneer Robert McKim in the 1960s and they are taught up to the present day as part of Stanford’s design thinking curriculum for innovation engineering. Compared to Stanford’s classes, at the HPI we pursue a stronger focus on the neuroscience of vision. This includes a concern for the ways in which our human physiology impacts processes of understanding and sense-making when data or ideas are represented graphically. A sample project emerging from this class considers the resolution of visual prototypes (e.g, rough sketches vs. CAD-models) and the diversity of visual prototypes in a creative project to predict the novelty and effectiveness of final project outcomes.
While the human sense of vision is harnessed a lot in human-computer interaction, opportunities arising from other human senses are much less explored. The seminar and lecture Sonic Thinking are especially dedicated to the auditory sense and resulting design opportunities in the field of digital engineering. The classes provide basic knowledge, skills and experiences with regard to hearing, acoustic imagination, the expression of ideas and representation of data through sound. This includes an introduction to digital engineering tools for working with sound, such as SuperCollider, Pure Data, Faust compilers, audio-programming in C++, often-used algorithms, standard protocols etc. The classes offer an introduction to sound design both for applied and artistic purposes, sound installations and basics of composition. Examples of data sonification are treated from fields such as healthcare and biology. The courses touch on listening techniques and listening trainings. The neuroscience of hearing is discussed to elucidate the way in which our human physiology impacts processes of understanding and sense-making when data or ideas are represented acoustically. A class onData Sonification – Opportunities of Sound has been taught in 2020 for the first time. The Sonic ThinkingSeminar and Lecturecommenced in 2021. A sample project in class explores whether it is possible to construct audio-only videogames that are fun to play for broad audiences, notably including people with good eyesight.
A class on Symbolic Thinking is currently being prepared. This class will be dedicated to processes of understanding and sense-making when people work with symbol systems (mathematics, verbal language, computer code).
Classes offered by the neurodesign work-group are typically classes for master students. However, you need no particular prior knowledge to attend the classes. As a bachelor student, you can join as well. In case of interest please reach out to neurodesign [at] hpi.de.
- - - cited above - - -
McKim, R. H. (1972). Experiences in visual thinking. Belmont, CA: Wadsworth Publishing.
Adams, J. L. (1974). Conceptual blockbusting. Stanford, CA: Stanford Alumni Association.
von Thienen, J. P. A., Clancey, W. J. & Meinel, C. (2021). Theoretical foundations of design thinking. Part III: Robert H. McKim’s visual thinking theories. In H. Plattner, C. Meinel and L. Leifer (eds.), Design thinking research. Interrogating the doing (pp. 9-72). Cham: Springer.
