Library of Things Service (UX and Conversation Design)
Overview
Our Library of Things (LoT) is a borrowing service that allows students to access practical hobbies such as sewing machines, hand tools, crafting kits, and small electronics that enable hands-on learning and hobby exploration, without the need for individual ownership.
Project Design Aims
Our service aims to enhance University of Melbourne campus engagement through accessible hobby resources, foster student wellbeing through creative engagement, promote environmentally-friendly living through shared consumption, and strengthening feelings of belonging and connectedness through accessible services and equipment.
Client
University of Melbourne Student Union, UniMelb Sustainability Office
Target Users
University students interested in practical hobbies, reducing living costs, or adopting a more sustainable and minimalist lifestyle. Students seeking social connections through collaborative hobbies are also considered.
Timeframe
Feb - June 2025
Group Members
Jesslyn Andriono (me) Jake De Andrade Nicholas Kurniasurja Bryan Susanto
PART 1: Library of Things Service Design Prototype
Problem Statement
To ensure that our service addresses user needs, we first conducted secondary research then from that, brainstormed "How might we?" statements to verbalize user needs. Examples include:
How might we save students from needing to purchase items?
How might we encourage the pursuit of practical hobbies?
How might we ensure students have access to tools and equipment at all times?
I was in charge of analyzing our group brainstorm and develop a problem statement, in consideration of the project's scope and client expectations:
Many University of Melbourne students are unable to pursue practical hobbies and connect with like-minded peers due to the prohibitive costs of purchasing equipment and the lack of accessible shared resources on campus.
Ideation
We first conducted 10+10 sketches, where we each create 10 quick designs, and then create another 10, that are an iteration of someone else's design.
Out of all our ideas, 3 ideas stood out, being innovative extensions/interpretations of a Library of Things service.
Locker system to borrow/return equipment
A "Hobby Master", staff that has extensive knowledge on hobbies
Articles relating to hobbies with equipment available
Within this discussion, I focused on accountability measures to ensure the LoT's longevity. What ideas can ensure that items are returned and kept in good condition?
My first idea was to disable Student IDs, but this is not feasible to protect student data.
As such, I thought about other measures, such as inspecting the product, by staff when possible, during return. Otherwise, submitting photos when putting the item back into the locker.
Storyboarding
To integrate our distilled physical and digital components from our ideation, we created storyboards and, as a group, interviewed two groups of students for feedback.
The first iteration, shown above, garnered the following key feedback:
Self-locker system effective and efficient
Need for improvements in inclusivity and clearer operational workflow to enhance usability
Main barriers identified: limited accessible lockers and staff dependency issues (especially on off-days and hours)
This feedback, paired with group reflection, was implemented as the following changes:
Web-based way to indicate accessibility needs during booking process
Create damanage accountability logs linked to user records (could impact booking eligibility)
Emphasizing on self-service experience, only staff support on special cases
Specify locker measurements to help wheelchair users and others with accessibility needs
Second storyboard iteration:
Desktop Walkthrough
A desktop walkthrough used a low-fidelity layout with key physical components; a simple, low-cost method to evaluate the spatial and service flow of our service. Below was our set-up, with a user on a wheelchair and staff behind the counter.
Throughout our iterative prototyping, we always try to summarize feedback in grid form, displaying what worked, what needs changing, outstanding questions, and new ideas.
Overall, we were able to discover weak points such as theft risks from valuables being visible at the counter, navigation challenges for, and staff dependency outside operating hours, to ensure that the self-service locker system remains inclusive, secure, and accessible for all users while ensuring the longevity of the service.
My main contribution to the project in Part 1 was to create a comprehensive customer journey map, summarizing all our findings thus far to identify the steps, touchpoints, and accessibility considerations required to use our Library of Things service.
Jesslyn - Developing the problem statement and creating the customer journey map Bryan - Taking, compiling, and summarizing notes into feedback grids, to motivate iterative prototyping Nicholas - Creating the storyboards and summarizing the desktop walkthrough Jake - Problem and accessibility statements, helping annotate graphics for the desktop walkthrough
All tutorial activities and user evaluation were conducted collaboratively in-person.
Reflection
In summary, a bulk of the iterations we designed were driven by the motivation to make the Library of Things service as effective, efficient, and accessible as possible, while ensuring that a wide range of users are able to utilize self-service features and that the service is sustainable long-term by avoiding theft, damages, and other similar disruptions.
I think what worked best was how communicative we were as a group, so we made joint decisions and combined feedback to iterate through ideas. When one of us struggles in completing a task, I felt that I could always rely on my group mates to help each other out.
In regards to areas for improvement, user evaluation could have been more comprehensive, missing diverse cultural backgrounds and technical comfort levels. If interviews are done with UniMelb offices, this may also have revealed additional constraints. Overall, there is also always more that can be done to iterate and develop the digital touchpoints within the service.
PART 2: "Hobby Master" Chatbot Extension
Rationale and Problem Statement
The core innovative element of our service is the “hobby master” set of articles, which is only becomes effective when the available information is both diverse and extensive, including specific accessibility features for users. This poses a new challenge: specific information may become difficult for users to find, when drowned in a sea of other information.
Part 2 explores the addition of a chatbot into the LoT, driven by a broad aim to enhance the “hobby master” to allows users to easily acquire the information they need. Our design methodologies are grounded on user feedback, iterative design principles, and conversational design theories, to create an intuitive chatbot interface that effectively caters to a wide range of users.
Ideation
To determine where in the customer journey the chatbot should be added, we conducted a "crazy eights-esque" method, where we brainstormed as many ideas as possible in 5 minutes, to incentivize divergent thinking. These ideas were plotted on the chart below:
After more group discussion, two promising paths emerged:
Paths
Pros
Cons
Helping people use an item and/or find items to borrow for a hobby
Straightforward and easy to implement, catered specifically to our service.
Is it necessary? users can find information regarding the item through our online catalog manually (Search)
Helping people find hobbies they’re interested in
Promotes exploration of practical hobbies, helps people connect over similar hobby interests
Doesn’t relate to the service (borrowing items), too broad and unfocused
Before deciding on which path to pursue, or how to effectively pursue both paths, we shifted focus to more general components of the chatbot, to gain more insight.
Chatbot Persona Design
We purposefully excluded the use of animals, robots, and inanimate icons as they are likely to remove the warm, welcoming human-like personality which was key to the journey feeling like being greeted by a hobby-shop owner.
Harold, the Hobby Master Encouraging, Approachable, Passionate
Harold prioritizes the user in every conversation, is proactive and is encouraged to think divergently. It guides conversations and relates suggestions based on user preferences and their accessibility needs, making each interaction feel tailored and personalised.
Figma Wireframe
To visualize how users will interact with the chatbot within our "Library of Things" service, a Figma prototype was developed, highlighting the following interaction points:
Using the wireframe, we interviewed other students to help discern between the two paths, item-centered help and hobby-centered help.
There wasn’t a clear consensus on which direction was better, with contradicting feedback given. After further consideration, our team decided to develop the concept for a chatbot designed to recommend items and assist users with information on how to use them.
This approach caters specifically to the service the Library of Things provides and is less similar to generic LLMs which can recommend hobbies.
Wizard of Oz Testing
Upon choosing the item-centered path, we created scripts and conducted Wizard of Oz testing on two different groups of students. I was in charge of summarizing this testing in our report. Below are the feedback and potential changes we implemented:
The next iteration diverged into considering various scenarios, such as potential happy paths, where users are satisfied, and unhappy paths. Below is a sample happy path:
This ideal/happy path was guided by the conversational sequence labels from Moore and Arar’s (2019) Natural Conversation Framework. For example, applying the C3 (Capabilities) pattern, when the chatbot clearly states its capabilities and limitations, addressed problems identified in previous iterations of users being unsure of what the chatbot is for.
Accessibility Review: Cognitive Walkthrough
I was responsible in conducting an accessibility review, in the form of a cognitive walkthrough, to evaluate the accessibility of the chatbot across varying user needs. 4 personas were utilized:
Alex, a student with low vision due to retinitis pigmentosa
Briana, a student who is blind and proficient in braille
Chloe, a student with cerebral palsy who uses a wheelchair
David, a Deaf student who uses Auslan and lip reads
There were 2 tasks to be completed for each user (1: Looking for items to borrow for their hobby, 2: Inquiring about a specific item in the library) each reflecting on:
Will this user know what to do?
Will this user see how to do it?
Will this user understand feedback?
What accessibility considerations are needed for this user?
Below are the feedback and potential changes we implemented:
Voiceflow
I was responsible of planning the Intents, Entities, and Exit Scenarios for various possible user queries. These were utilized to develop our Voiceflow chatbot.
Moderated user tests were conducted, pointing to the need for the following changes:
Make the opening question more open-ended
Suggest alternative hobbies or tools when an item is unavailable
Enable booking equipment directly through the chatbot
After the changes, Harold is now able to help you:
Ask about equipment using voice or text - Harold responds as your hobby master for Library of Things items
Write multiple queries in one message - ask about dimensions and availability together, or combine item name with your questions
Get instant equipment details - Harold pulls up model numbers, specifications, and technical information from the database
Check what's available to borrow - find out how many items are in stock when you want to get one for a friend
Harold is also can:
Understand what item you mean - mention "camera" or "digital keyboard" and Harold knows which equipment you're referring to
Answer complex questions - ask about accessibility features, physical size for travel, or multiple specifications at once
Keep conversations focused - when you mention several items, Harold guides you to discuss one at a time for clarity
Adapt to your style - whether you confirm the item first or jump straight to questions, Harold follows your lead
Harold's key distinctive features are that it can:
Recognize when you need help - if your message doesn't mention a specific item, Harold prompts you for clarification
Pull real-time information - gets current details directly from the equipment database
Provide practical details - focuses on information you actually need for borrowing and using the equipment
Summary of Group Contributions
Jesslyn - Delegate work, conduct the Accessibility Review cognitive walkthrough, summarizing the intents, entities, and exit messages, and summarizing the service overview in the report Bryan - Taking, compiling, and summarizing notes into feedback grids, planning and plotting the paths and conversation flow Nicholas - Creating the persona design, summarizing the accessibility considerations, and highlighting the conversational UX principles applied Jake - Voiceflow and Figma Prototying
All tutorial activities and user evaluation were conducted collaboratively in-person.
Reflection
What worked for me in this part of the project was the delegation of work. In the past, we have almost always worked collaboratively, which ends up taking longer as small details were also passed on throughout the group. In this part, we tried to have clearer sectioning, which made it more efficient. We would divide the deliverables needed into sections and have a meeting at the start of each section, dividing the work in that section. This allowed us to stay updated on how others are doing and work towards the same goal, without being overly collaborative.
Choosing between item-centered versus hobby-centered paths proved challenging, considering the contradictory feedback we received. At some point, we had to make a decision amongst ourselves, as the dilemma was slowing down our progress. We tried to make as informed as a decision as possible, with the risk that our biased perspective could lead to the wrong decision. However, in hindsight, I believe that the right decision was made, as we ended up creating a chatbot that is specific to our Library of Things service, that cannot be replicated by general LLMs.
Overall, I wish that there could have been more time and opportunity to conduct more thorough user evaluation, with similar reflections with the previous part's reflections of taking into account the user's cultural background or technical proficiency as a factor that may impact their experience. That said, I am incredibly happy with my groupmates and the work we have produced. We worked collaboratively, efficiently, and most importantly with kindness throughout. This has set a high bar, for me personally, of what great teamwork feels like and I hope to carry this in my future collaborative projects.
UX Research Example - Usability Evaluation of Triptile.com
Three groupmates (Michelle, Sean, Ileana) and I conducted a usability evaluation study on September of 2023, evaluating a trip-planning website called Triptile. The study was aimed to evaluate the website's functionality, effectiveness, learnability, and efficiency to gain a deeper understanding on how to improve the website's user interface.
The two methods utilized were in person interviews/live studies and online Optimal Workshop studies, using OptimalSort, Treejack and Chalkmark. A total of 3 participants took part in the live study, whilst 101 participants took part in the Optimal Workshop.
The study showed that:
Triptile lacks system feedback in response to a user’s action. 3 out of 3 participants agreed with this statement.
Misinterpretation of Triptile’s functionality happens often due to a lack of information to direct user flow. 3 out of 3 participants agreed with this statement.
Unclear/disoriented pricing labels made it difficult for users to understand the pricing page. 2 out of 3 participants agreed with this statement.
Descriptions are very vague and overall lack detail. 2 out of 3 participants agreed with this statement.
The Optimal Workshop tasks supported the finding that some tasks were difficult to perform.
The OptimalSort tasks and Chalkmark task 1, finding the create trip button, were deemed the most simple, with over 75% of participants able to successfully complete it.
Chalkmark task 2, finding the check out button, is regarded as moderately difficult, with 67% of participants able to complete the task.
The TreeJack task, navigating to a specific pre-made trip is regarded as the most difficult, with 31.8% of participants being able to complete it successfully.
Based on the findings, we concluded that to best increase Triptile's effectiveness, learnability, and efficiency, the following key recommendations should be implemented:
Adding a confirmation button and feedback message when a significant action has been taken by the user .
Provide a step-by-step guidance for users to gradually add experiences, accommodation, and transportation when first creating a trip.
Changing the price listed on the main trip page to the total price of the trip and adding a cost breakdown on the payment summary page.
By implementing the key recommendations listed above, it is anticipated that the following objectives would be met:
Users to have a clear understanding of their interaction with the website through confirmations of their actions and visibility of system status.
First-time users to acclimate to the layout and logic of the website, allowing them to easily and intuitively navigate the website and achieve their wants.
Users to find clarity about the pricing on specific trip expenses while also knowing the total price for multiple expenses.
Below is a more in-depth video summary of the findings and recommendations we acquired through our evaluation.
Triptile - Usability Evaluation Findings and Recommendations Summary
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