UX/UI Designer
12 Weeks
Figma, Google Doc, Zoom


01 Overview


In today's fast-paced digital age, individuals with Attention Deficit Hyperactivity Disorder (ADHD) face unique challenges when it comes to learning effectively. Recognizing the importance of providing tailored solutions for this community, I embarked on a mission to design a mobile-first product specifically aimed at helping users with ADHD optimize their learning experiences.

The Problem and its Significance

ADHD often presents difficulties in maintaining focus, organizing thoughts, and managing distractions, making traditional and digital learning environments challenging for individuals with this condition. The impact of these challenges can lead to frustration, diminished academic performance, and decreased self-confidence. It became clear to me that addressing this problem was of utmost importance to empower individuals with ADHD and unlock their full learning potential.

With that in mind,

how might we help those with ADHD digest learning material more meaningfully?

Proposed Solutions

1. Streamlined and Clean Interface: The product boasts a minimalist and intuitive interface, free from unnecessary clutter, to foster a distraction-free learning environment. By eliminating visual noise and promoting a calm atmosphere, users can focus on the content at hand without unnecessary distractions.
2. One Course at a Time: Recognizing the overwhelm that multiple courses can bring, the product presents users with just one course at a time. This approach minimizes information overload, allowing learners to focus their attention, grasp concepts more effectively, and progress through the material in a structured manner.
3. Customized Learning Experience: The application enables users to input their learning preferences and harnesses the power of assistive technology to generate a customized learning experience.


02 Research

Understanding the Problem Space

In order to gain a comprehensive understanding of the needs, challenges, and preferences of individuals with ADHD in relation to learning, a multifaceted user research approach was undertaken. This involved a combination of user interviews, secondary research, and a competitive analysis of popular e-learning platforms.

User Interviews

Process: 6 users were interviewed, 2/6 of users were diagnosed with ADHD.

Key Findings:
1. Distraction is a Big Culprit
: Users with ADHD acknowledged the difficulties they faced in mastering new skills. Their condition presented additional obstacles in terms of focus, organization, and attention.

"Something will catch my attention and dominate my time; it's hard to balance multiple skills and it's hard to prioritize." - ADHD user

2. Diverse Information Processing: It appears all users with and without ADHD process and retain information differently. Certain individuals opted for more video, where as another preferred more a text based format.

"It'd be nice to have a more personalized selection of learning."

Secondary Research

5 Fast Statistics:
1. Males are almost three times more likely to be diagnosed with ADHD than females.
2. During their lifetimes, 13 percent of men will be diagnosed with ADHD. Just 4.2 percent of women will be diagnosed.
3. The average age of ADHD diagnosis is 7 years old.
4. Symptoms of ADHD typically first appear between the ages of 3 and 6
5. ADHD isn’t just a childhood disorder. About 4 percent of American adults over the age of 18 deal with ADHD on a daily basis.

ADHD (Attention Deficit Hyperactivity Disorder) can be classified into three different types, each with its unique characteristics and how it may affect their learning:

1. Predominantly Inattentive Presentation (ADHD-PI): difficulty with sustained attention, organization, task management, and easily distracted.
2. Predominantly Hyperactive-Impulsive Presentation (ADHD-HI): Restlessness and physical discomfort, impulsive decision making, difficulty waiting turns
3. Combined Presentation (ADHD-C): ADHD-C is characterized by a combination of inattentive and hyperactive-impulsive symptoms.

For the purpose of this project, Predominately Inattentive Presentaiton (ADHD-PI) will be addressed.

Competitive Analysis

Based on the analysis of Udemy, Coursera, Skillshare, and LinkedIn Learning, here are some areas of concern for ADHD users in terms of e-learning.

Complicated and Content Heavy Interface: Many e-learning platforms in the market suffer from information overload. Platforms typically offer suggestions to try new courses frequently, and have too much stimuli for a user wanting to just focus on the task at hand.

Rigid Learning Paths: Platforms generally lacked the freedom for users to design their own learning journey based on their learning needs, preferences and skill level. Furthermore, some platforms don't offer ways to reinforce the content learned (no application or assignments to test their skills) or it is under-developed.

03 Define

Identifying the Problem

An Affinity Map was created to cluster findings from the user interviews - each colour represents a single user.

Based on the insights from the Affinity Map and utilizing the POV (Point of View) statements, and HMW (How Might We) statements exercises, problem statement was defined as follows:

"How might we help those with ADHD digest learning material more meaningfully?"

This problem statement represents a real problem observed through user interviews and secondary research that is not currently addressed or is under-developed.

04 Ideating Solutions

Approach and Outcomes

Two methods of idea generation were used:
1. Creative Constraints (Time) - with 10 minutes on the clock, I generated 19 points and championed 2 ideas.

2. Analogous Inspiration - also called “lateral inspiration”, this brainstorming technique involved thinking about how other industries or entities are tackling a similar problem or achieving the same goal.

With more time and consideration, I was able to ideate an idea that would be the main feature of this product (Customized Learning).

Main Product Features (3):

These 3 ideas were chosen based on relevance, impact, and feasibility.

Prioritizing Features

Specific features were then ranked based on importance and relevance to the proposed solutions.

Must-haves included necessary components for data storage (account creation) and competitive advantages (learning preferences).

Nice to have consists of next-in-line features that would contribute to the solution after the P1 was taken care of.

Observation: "Rewards" was ranked the lowest in this list since it appeared users didn't rely on it to keep learning (based off user research).

05 Design

Placeholder text 1

06 Test

Placeholder text 2


07 Final Design

Placeholder text 3


08 Reflection

Placeholder text 4