CLIENT Meraki (Part of NavGurukul)
DURATION About 4-5 weeks
CONTRIBUTION Individual contributor (2 part-time volunteers helped with conducting 4 out of 7 interviews)
Note: This is user research part of the case study. UI design case study link can be found at the end of this part.
Meraki offers free Python programming education to young girls from low-income families in India. I joined Meraki when it had 100 students and was 6 months old. Meraki combines learning via self study material and online instructor-led classes.
The research aimed to uncover reasons for the following problems:
I led research plan, managed end-to-end research process, and conducted 3 out of 7 interviews with two part-time design volunteers.
Approximately, the research project took about more or less four weeks.
User interviews were used because the team wanted to learn student behavior of using Meraki. 7 students were interviewed for 30 minutes each via Google Meets, with a team member present to take notes.
The recruitment criteria for the research were:
Campus manager used Whatsapp group for easy coordination, and set up 1:1 sessions with the students.
Here is a link to the interview guide and notes. I used a semi-structured format with open ended questions and probed further according to the responses.
Held debrief sessions with design team, combined notes and identified critical pain points. Moved notes to EnjoyHQ and analyzed them with thematic analysis.
The main themes that emerged were:
From the themes, I worked on a journey map to label the pain points at various steps of the student's journey.
Major pain points were (These are not all pain points. Please check the detailed journey map):
Personas were created based on two criteria: exposure to technology and learning style (work in progress). Personas evolved to archetypes represent overall group of users, focusing on problems with Python programming learning.
Persona 1: The Beginner in Tech
Person 2: Headstarter in Technical Knowhow
Application map via insights from card sorting and interviews. The cards represented the information to be presented in the tabbed menu items from categories.
While we asked the development team to look into Mixpanel, we created a few short surveys to catch student engagement. They would be given by the teachers during the classes. However, it did not work as expected as there was a lot of manual work involved. Due to several other priorities, Mixpanel implementation has been delayed.
Six important tasks were identified that the student usually perform in their learning journey. The decisions to optimize them came from the insights from synthesis of data above.
Monitored batch-based courses.
Iterating on user personas and task flows as we learn more about the students.
Create and maintain a user research repository in EnjoyHQ (the process is complete now).