We’ve made some prototypes — now what?
(Week 4 prototype demos from COMP3900 2025)
The purpose of this tutorial is to help you to design and conduct an
evaluation activity.
The intended learning outcomes for this tutorial are to:
Develop design evaluation goals
Design evaluation activities using qualitative and quantitative
methods
Understand how to facilitate an evaluation activity with technology
users
Critically reflect on which evaluation methods can address
particular kinds of evaluation goals and research questions
Pre-Class Tasks
You should complete the following activities prior to attending your
tutorial:
Review the lecture content on
Evaluation
Read the following chapters from Interaction Design: Beyond
Human-Computer InteractionChapter 14 Introducing
Evaluation, Chapter 15 Evaluation Studies: From
Controlled to Natural Settings(Rogers et al.,
2023).
Write a forum post (100-200 words) summarising your research plan in
preparation for Assignment 2. In your post, name the AI use context you
have chosen to investigate, and explain why you selected it. Then
briefly outline your research plan, including your strategies for data
collection and the analysis framework(s) you intend to use. You must
also include at least two references from relevant HCI literature—these
could relate to prior studies in similar areas, research methodologies,
conceptual frameworks, or other scholarly resources relevant to your
topic.
Following on from the assignment work last week you should have:
joined a group to complete your mini user studies
chosen an AI use context to investigate
For this week’s tutorial you need to create a plan for your
study. Use your research
skills to find examples of needs finding studies and studies of how
people use AI tools (e.g., at CHI) and use them to help plan your study.
Make sure your study plan is realistic.
Remember, for your study plan you need to collect quantitative and
qualitative data so that you can report on an analysis of each type of
data. You can choose what form that data is, e.g., quantitative data
could be rating scale questionnaire questions, timed task completions,
or number of clicks to complete a task. Qualitative data could be
interviews, written reflections, images, videos, sounds, observations.
For more ideas, see the lectures and the textbook!
Plan for the Class
Discuss pre-class tasks (10 mins)
Plan an evaluation (30 mins)
Consider ethics (20 mins)
Meet with your group to plan your needs-finding study (30 mins)
In-Class Tasks
0. Discuss pre-class tasks (10
mins)
Your pre-class task asked you to describe your planned study for
Assignment 2.
Recall that the research question you will investigate is:
“What are the unmet needs, frustrations, and desired capabilities
that students experience when using AI tools in a specific context of
their life?”
As a class, discuss the following questions:
How does your study plan address this research question?
How have you ensured your study plan is feasible within the time
constraints?
Why does your chosen AI use context make sense for this research
question?
1. Planning an evaluation (30
mins)
This section of the tutorial is about articulating an evaluation
plan, which is a different kind of study from the needs-finding you’re
doing for Assignment 2: instead of asking what people need, an
evaluation asks how well a particular interface meets a need. As a
group, pick one AI tool to evaluate. This could be a
tool from one of your Assignment 2 use contexts (e.g., ChatGPT for study
planning, Copilot for coding), or any other AI interface your group uses
regularly.
In groups, spend 10 minutes discussing each of the following aspects
of an evaluation plan. Use a sticky note for each aspect. Make sure that
everybody in your group has completed a sticky note for each aspect!
Evaluation Goal
Consider the goal of your evaluation and a task that you might ask
users to complete.
Choose a particular feature of your chosen AI interface that you
wish to evaluate, that can facilitate a task for the user to
complete.
Choose one user experience AND one usability evaluation goal to
focus on.
Choose a task for the user to complete that would address your
evaluation goals.
Data Collection
Now it’s time to consider your data collection. Recall that we are
expecting both quantitative and qualitative data collection and
analysis.
How will you collect your data? Why have you chosen these
methods?
Write up your means of data gathering. Consider what data you are
trying to gather and how it contributes to your evaluation goal.
What kind of data will you be collecting? Will this involve
identifiable information from participants?
Analysis Methods
After you have gathered your data, it’s time to analyse it.
What kind of analysis will you do for each type of data you
collect?
Are your chosen analysis methods appropriate within the context of
your research?
Would any personal
or sensitive data be stored as part of your analysis? Read the link
to make sure you know what those terms mean!
2. Considering Ethics (20 mins)
As makers/learners/developers/academics/humans, it’s important to
consider the ethical implications of any of our work. The key ethical
questions for an HCI evaluation with human participants are (National Health and Medical Research Council
(NHMRC) et al., 2025):
What is the research activity that the participant will do?
Does this activity have any risks or benefits?
How will the participant provide informed consent for the
activity?
Note that “risks” in HCI, are usually not of physical harm, but could
be related to privacy of the data collected or risk of being identified
as a participant. Small studies often do not benefit the researcher very
much, but it has been argued that we should expect more benefits to flow
to vulnerable participants (Brown et al.,
2016).
Informed consent for participation is a cornerstone of research on
humans (National Health and Medical Research Council
(NHMRC) et al., 2025). For some kinds of HCI research, the
concept of consent is complicated (Benford et al., 2015), but in your work,
you may wish to obtain consent in written form, or verbally. The idea is
to ensure that participants understand what the study involves and
clearly agree to participate given that knowledge. For Assignment 2, a
natural part of this process is asking each participant to write down
their uid and name for your Participants section
(- u1234567 Firstname Lastname) — consenting to be named in
your submission is part of what they are agreeing to, and it’s how
participation is verified.
In pairs, discuss how your study plan for the assignment aligns with
these questions:
What are the risks of your study? What will you do to mitigate
risks?
What are the benefits to the participant?
What would your process be for gaining consent?
Summarise your ethical considerations in 4-5 sentences and post it on
the forum. Your tutor will create a thread for your tutorial.
Research cluster meeting (30
mins)
The last 30 minutes of this workshop is dedicated to meeting with
your group and working out the logistics of completing your
needs-finding studies.
As a group you should:
Talk through your overall assignment research plans with your group,
and make sure to address any concerns your participants might have. You
don’t need to go into the details of your specific data collection
questions (that will come during the actual mini study), but be clear
about what you’ll be asking participants to do and what their
involvement will look like.
Decide on the time and place when you will conduct your data
gathering. Remember that every tutorial in the course is followed by a
30 minute drop-in — this means the room is booked and free to use for
this course!
Do your user research! If you have time and are prepared, you might
like to take turns to conduct and participate in your assignment
research activities in pairs.
Benford, S., Greenhalgh, C., Anderson, B., Jacobs, R., Golembewski, M.,
Jirotka, M., Stahl, B. C., Timmermans, J., Giannachi, G., Adams, M.,
Farr, J. R., Tandavanitj, N., & Jennings, K. (2015). The ethical
implications of HCI’s turn to the cultural. ACM Trans. Comput.-Hum.
Interact., 22(5). https://doi.org/10.1145/2775107
Brown, B., Weilenmann, A., McMillan, D., & Lampinen, A. (2016). Five
provocations for ethical HCI research. Proceedings of the 2016 CHI
Conference on Human Factors in Computing Systems, 852–863. https://doi.org/10.1145/2858036.2858313