Summary of Chapter 14, 15 and 16.2/Week 6 of Human-Centered Design at TU/e 2023
Summary of Week 5/Chapter 12 of Human-Centered Design (DDB200) in TU/e 2023
Summary of Week 4/Chapter 11 of Human-Centered Design (DDB200) in TU/e 2023
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Schule, Studium & Fach
Technische Universiteit Eindhoven (TUE)
Industrial Design
Human-Centered Design (DDB200)
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Inhaltsvorschau
Chapter 8
8.1
● Data collection is vital to the design process to set requirements
● Both qualitative and quantitative are useful
● Three main types: interviews, questionnaire and observation
○ Interviews: series of questions, can be structured or unstructured, synchronous
(happen at one time), can be face-to-face
○ Questionnaire: series of questions, answered asynchronously, can be
paper-based or online
○ Observation: can be direct (spending time with individuals observing their
activities as they happen) or indirect (making a record of the user’s activity as it
happens, to be studied at a later date)
● Should use more than one type to avoid inherent bias
8.2
● There are 5 key issues for any data gathering session to be successful
● Goal Setting
○ Important to set goals before a data gathering session to influence the nature of
the session, the techniques that will be used and the analysis to be performed
○ Can be expressed formally or informally but much be clear and concise
● Identifying Participants
○ The people from whom the data will be collected are called the population or
study population.
○ it is likely that the participants to be included in data gathering need to be chosen,
and this is called sampling
○ The situation where all members of the target population are accessible is called
saturation sampling
○ If only a portion of population will be involved in data gathering there are two
options: probability sampling or non-probability sampling
■ Probability sampling uses simple random sampling or stratified sampling
● Random sampling is achieved by using a random number
generator or by choosing every nth person in a list
● Stratified sampling: dividing the population into groups and then
using random sampling
■ Nonprobability sampling uses convenience sampling or volunteer panels
○ Convenience sampling = situation where the sample includes those who were
available rather than those specifically selected
■ Snowball sampling = type of convenience sampling, one participants finds
another and so on
○ Crucial different b/w probability and non-probability sampling is with probability
you can apply statistical tests and generalise to the whole population and with
non-probability you can’t (not robust enough)
○ The more participants the more confident you can be with your results
, ○ Formally there are methods to determine how many participants you need. Four
of them are saturation, cost and feasibility analysis, guidelines, and prospective
power analysis
■ Saturation = data collected until no new relevant information emerges, no
set number beforehand
■ Numbers chosen based on cost and feasibility is common in industrial
industries and is a practical and justifiable approach
■ Guidelines = from experts or the “local standard”
■ Prospective power analysis = rigorous method (used in stats) that relies
on existing quantitative data about the topic, this info is often not available
for industrial design therefore unfeasible
○ Based on research, the “local standard” sample size for industrial design is
12
● Relationship with Participants
○ Relationship between the person doing the gathering and person providing the
data is a significant aspect of data gathering
○ Kept clear and professional will help clarify the nature of the study
○ How this is achieved varies in different settings/countries
○ Often includes a form which asks participants to confirm the purpose of the data
gathering, it explains what the data will be used for and asks if they’re willing to
continue. It explains their data will be kept private and secure and often that they
can withdraw at any time and their data will not be used
○ An informed consent form is intended to protect both the participant and the data
gatherer
■ The gatherer wants to know that the data they collect can be used in their
analysis, presented to interested parties, and published in reports. The
data provider wants reassurance that the information they give will not be
used for other purposes or in any context that would be detrimental to
them.
■ In the case of children their parents will sign on their behalf
○ This sort of consent form not generally required when gathering requirements
data for a commercial company where a contract usually exists between the data
collector and the data provider (ie. company hires someone to collect data on
their staff to design a new system)
○ Increasingly, projects and organisations that collect personal data from people
need to demonstrate that it is protected from unauthorised access
○ The European Union’s General Data Protection Regulation (GDPR, 2018)
applies to all EU organisations and offers the individual unprecedented control
over their personal data.
○ Incentives to take part in data collecting sessions may also be needed
● Triangulation
○ Triangulation = the investigation of a phenomenon from (at least) two different
perspectives
○ Four types:
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