Mastery-Based Evaluation
Designed Scaler’s learning evaluation program, resulting in higher interview-cracking rates for participants.
Business Impact
This project delivered the following value:
Created a scalable framework connecting learners to mentors in an interview setting, improving placement confidence and employment readiness.
Achieved good user acceptance after the first module rollout.
The Ask
As Scaler wanted to add more value to their learners, there was a vision to help students with their interviews and job-readiness. The vision was to move beyond passive learning assessments and create a reliable system for validating interview performance at scale.
The ask was to design an evaluation platform that:
Evaluated the technical capabilities of budding software development learners through simulated interviews with mentors.
Connect learners with relevant job opportunities based on their readiness and skillset.
Understanding the Problem
While learners were completing modules and mock tests, there was a growing disconnect between what they learned and what they need to apply in a real-world scenario when they start working.
They lacked:
Contextual personalised feedback and a growth plan for improvement.
Visibility into where they stood compared to peers and how well they are aligned with hiring expectations.
Structured mentorship that translated into measurable career outcomes.
For mentors, it was equally challenging to standardise their feedback and ensure that it was actionable within the larger placement setting.
Challenges
Balancing learnability vs. judgment — learners needed to improve, not just be graded.
Creating tiered placement eligibility logic that was both fair and motivating.
Integrating the flow into Scaler’s existing learning and placement ecosystem without overwhelming students.
The Process
Worked with Mentorship and Placement teams to define success criteria: mentor engagement, evaluation clarity, learner visibility. Identified key UX metrics: time-to-feedback, clarity of rubric, and repeat participation.
Mapped end-to-end learner and mentor journeys: from interview scheduling → participation → rubric-based grading. Storyboarded learners' emotional states across the evaluation lifecycle to identify high-pressure moments.
Benchmarked interview evaluation systems used in real-world hiring scenarios.
Conducted interviews with 8 mentors and 30+ students to identify challenges and issues.
Built wireframes and prototyped the interview scheduling workflows, interview layouts, and evaluation and feedback systems on both learner and mentor portals.
Ran a pilot test with learners and mentors gathering feedback on: Stress vs. confidence balance, and Actionability of feedback.
Learning
One of the most effective UX strategies was building mentor-facing tools that automated and structured feedback, enabling consistency.
A simple “next steps” section helped reduce post-evaluation drop-off, proving that support after the test matters as much as before it.
