UX/UI Designer
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Overview of design process

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1 - Defining the problem


The Brief

“Childcare has grown due to the fact that many parents have full time jobs. Daycare workers are increasingly challenged with the demands of parents and the promise that their children's needs and learning are looked after.

Design an experience that helps daycare workers understand the needs of each individual child throughout the day. Consider AI and ML technologies to help in the overall experience you're designing for this user.”

Age of children:

6 months - 6 years


  • Your experience should target either phone, tablet or both on Android or iOS.

  • Provide a high-level flow, supporting wire frames and a high-fidelity visual design execution for at least one step of this experience.


1.a - Contextual Research


I started the exercise by gathering as much information as I could on day care workers, their role and responsibilities as well as some of their common pain points. Below is a high level summary of what I found that would help influence decisions throughout the process.


I: definition

“Childcare workers care for children when parents and other family members are unavailable. They care for children’s basic needs, such as bathing and feeding. In addition, some help children prepare for kindergarten or help older children with homework.”

Source: Truity: Childcare Worker Profile

II: Common activities

  • Improve children’s social skills by having them work together to build something

  • Creative activities, such as art, dance, and music.

  • Storytelling and rhyming games to teach language and vocabulary


  • Supervise and monitor the safety of children in their care

  • Organise activities or implement a curriculum

  • Develop schedules and routines to ensure that children have enough physical activity, rest, and playtime

  • Keep records of children’s progress, routines, and interest

Source: Truity: Childcare Worker Profile


1.b - User Research

I started with some background research on the biggest challenges for day care workers today. This would be followed up with my own user interviews and help with persona creation.

Common Pain Points:

  • Not enough time in the day to do everything

  • Too much paperwork

  • Not enough time spent with the children

  • Not getting enough support

  • Difficulties in communicating with parents

    Source: Early Years Careers, March 2016


1.c - User Interviews

It was important for me to speak with as many people as I can who have experience working as a daycare worker, with children or even parents who have some insights into the sector. I have no prior knowledge in daycare, so this step was really crucial in helping me assess what solutions currently exist, the pain points different people face and how I could address the next steps in the design process.


User Interview I

Marie Dewhurst
Early Learning Teacher for 30 years
Class of 30 - Ages 4-5
Session Length: 1 hour

Key Insights:

  • Biggest problems are around documentation, providing evidence of the development of each child and knowing what to do next. This is what takes most time away from the teacher and a suggestion was to develop a tool that can be used throughout the day as the teacher is observing the children, rather than doing it retroactively.

  • A lot of my initial ideas were proven to be either too complex or not suitable after learning more about what it means to work with children.


User Interview II

Jennifer Trigg
Kids 1st Steps
Level 2 Apprentice
Group of 8 - Ages 1-4

Key Insights:

  • Biggest problems are around documentation, providing evidence of the development of each child and knowing what to do next.

  • Suggestion was to develop a tool that can be used throughout the day as the teacher is observing the children, rather than doing it retroactively.


User Interview III

Catherine Stull
Parent of a 3 year old in nursery

Key Insights:

  • Discovered valuable information about the current tools on the market. (E.g Tapestry is leading in the documentation space)

  • It’s not a requirement to upload data every day, and it varies from daycare to daycare about how often they provide insights into child’s learning. Usually this is communicated at the end of each day in person


1.d - Persona Creation


I developed a set of lean personas to help me understand the customers better and ultimately make better decisions related to the product design and features. After my user interviews and contextual research, I had a much better understanding of the target users and found three common archetypes:

  • The Passionate Professional

  • The Innovative Educator

  • The Disheartened Doyen(ne)


1.e - Competitor Review


Before generating ideas, I wanted to learn more about what tools are currently on the market and how daycare centres utilise software tools. This will help me identify any current gaps in the market and to what extent AI and ML technologies are incorporated. Below is a very brief overview of this research.



  • Digital learning journal

  • Used by 1000s of nurseries and daycare centres across the U.K

  • Basic functionality: Evidence upload (photo/video), child database

  • Available as a web and mobile app

  • Available for both parents and staff

  • No voice notes or NLP available

  • EYFS 'tagger' allows assessments to be made down to statement level

  • Basic data: Child comparison



  • Parent sign-in and staff time clock

  • Parent billing

  • Calendar events and newsletters

  • Messaging and SMS for parents

  • Creation and tracking of custom developmental milestones for students

  • Meal reporting and tracking

  • Evidence upload and sharing options

  • Incident reporting

  • Focuses more on the administrative duties of daycare, and less about each child’s individual development journey.



  • Photo and video observations 

  • Administrative Reporting and Billing

  • Development assessments

  • Daily reports and sheets 

  • Program planning

  • Digital daily sheets with meals, naps, activities etc.

  • Email, text, and in-app communication

  • Focuses more on the administrative duties of daycare, and less about each child’s individual development journey.


2 - Diverge

At this stage in the journey, I began exploring multiple solutions, conducted ideation workshops and design thinking techniques to try and explore as many options as possible.

2.a - How Might We Statements

HMW statements help me frame the problem and position it in a way that helps me search for opportunities.
E.g: HMW...Help the worker notice trends and patterns in child’s behaviour? HMW...Help record children’s progress, interests and routines? HMW...Help the worker develop schedules and routines?


2.b - Crazy 8’s Workshop

I conducted an ideation workshop with 3 participants. Due to lack of time and resources, I invited friends and family who have worked with children, or have children of their own to help me come up with multiple solutions.

After discussing the problem statement, challenges and reviewing highlights of the user interviews, I conducted a Crazy 8’s style workshop (8 ideas in 8 minutes) and generated a total of 33 solutions. After voting, we selected the top 4 and did a deep dive session into additional features and requirements.


Sketches from the 1hr session

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2.c - Multiple Solutions


After the ideation session, I was left with a number of really exciting ideas. The goal of the session was to think abstractly and not think about limitations. The next step in my process was to refine the strongest ideas and try to validate them. Below are 3 of the strongest concepts with the general notes as well as the opportunities and challenges each one poses. If I had more time for this exercise, I would have created wireframes for each of these ideas and put them through another round of user testing. For now I will use my best judgement after weighing the pros and cons for each.



Voice-powered day worker assistant

Using voice recognition, Lily records notes, set reminders and timers for each child. The app can use this data and provide recommendations or learning development program for each child.

Opportunities: Solves multiple problems that came out of the research (time saving, less paperwork etc.) Existing technology (voice) that could power the project. Timers/reminders takes pressure off the worker to remember multiple things.

Challenges: Does this solution already exist? How easy would it be for the user to input information via voice - is this something that demographic would feel comfortable with?


Early Stage Learning Assistant

ESLA would be a mobile app that documents key milestones in each child’s development journey. The app would make recommendations for next steps and the evidence upload part would rely on labeled data and image recognition to help make the process seamless.

ML/AI Aspects: Labeled data improves recognition over time and makes it easier to upload evidence.

Opportunities: Adopting a pre-existing programme and making it more intuitive and efficient means the day care workers can build development evidence and be helped with next steps.

Challenges: My interviewees believed that the success of this app would rely on how easy and quick the interface was to use. “It would only work if it took less than a few seconds/clicks to note an observation.”


Tracks behavioural patterns and responses

TeachMe would aggregate data from dayworkers around the world and look for trends and patterns that have worked. DCW’s can search for solutions or tips and share their own learnings. It would tailor recommendations based on geographic location, age range etc.

Opportunities: The amount of data collected could be used outside of this functionality and potentially be used for scientific study as well.

Challenges: After interviewing an early years teacher, I was explained that it’s hard to look for patterns when it comes to behaviour because it’s reliant on so many other factors.


3 - Decide

I decided that at this point in time the AI possibilities are limited due to lack of structured data in the childcare sector. Hence the goal is to create an app which takes care of the organisational data in the process gathering labeled data which can be used to build features in the next iteration. I decided to go with ESLA, the documentation app.

3.a - Product road map & User Flow

Given the time constraints, I decided to produce a very high level user flow and focus on the first iteration of the app (evidence upload and recognition). The first iteration is needed, because before we can start introducing sophisticated ML and AI capabilities we need some structured labeled data to work with. I also wanted to highlight how the app could develop with additional release cycles in the future.


MVP User Flow (V1)


MVP User Flow (v2)


The first flow felt like too many steps to reach the most (likely) used function - evidence upload. Also my user interviews made it clear that for this function to be used in real time, it needs to be easily accessible. I refigured the flow to accommodate for this. As the labeled data continues to improve, the image recognition means that time spent captioning items can be reduced also.


4 - Build

4.a - Basic Wireframe


Before moving to hi-fidelity mock ups I wanted to start thinking about potential components and modules for the app based on the user flow I had developed. After pen and paper sketches, this is what I came up with. I used Sketch and some templates to help me quickly put something together.

Evidence Upload Flow Copy.jpg

4.b - Basic style guide & components

To speed up the process of creating the hi-fi prototype, I developed a colour palette, typography styles and some basic components. I also used some stock illustrations to help me create a realistic looking experience. If I was to develop this further, I would create a design system and Sketch library with reusable components and patterns.


4.c - Hi-fidelity prototype

After coming up with a brand and visual identity for the app, I moved on to creating the hi-fidelity prototype, taking into considering touch gestures, interactions and the overall experience.


5 - Retrospective & Future Iterations


If I had more time, I would have spent it interviewing more day care workers and learning more about their pain points. I think I got a good insight, but only scratched the surface of what’s involved in their day to day activities. I also would have spent longer figuring out the user flow and hi-fi screens. I chose a simple flow for the sake of this exercise, but I would love to explore the additional flows for this app, particularly looking at recommendations, clustering and reporting dashboards.

Finally, I would have liked to have involved a developer or ML/AI specialist to help work through this process. I found it difficult working in isolation as I am used to a collaborative environment where I can draw on the expertise of people around me.


Thank you!