A proposed novel Khan Academy feature that focuses on creating a motivating learning experience. A new feature that works seamlessly with an existing platform.
ROLE
Product designer: Figma, research, writing
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TEAM
4 designers, Education Technology Course
​TIMELINE
10 weeks, Spring 2026
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TOOLS
Figma, Miro
DELIVERABLES
Clickable mobile prototype
Video of Final Screens
Interactive Embedded Prototype Below
01
THE PROBLEM
Khan Academy has thousands of free lessons, but when a student gets a quiz question wrong, the next step is up to them. Most students keep clicking through the quiz instead of going back to the skill they missed. The mistakes pile up, the score drops, and students lose motivation before the gap ever gets fixed.
AUDIENCE 01
Struggling Students
Hit a wall mid-quiz and don't know which earlier skill caused it, so they guess or quit.
AUDIENCE 02
Self-Driven Students
Intrinsically motivaated students who use Khan Academy on their own and want a faster way to find and fix weak spots before a test.
How might we help students catch the skill they're missing without breaking their momentum?
02
RESEARCH
Our team ran 15 semi-structured interviews with students.
FINDING 01
Wrong answers feel like dead ends.
Students active in the GTXR club found research roles through peers and referrals. Students without those networks relied on cold emails, which often went unanswered.
FINDING 02
Students don't know what to review.
Students pieced opportunities together from lab websites, research papers, club meetings and cold emails. That's a lot of work, and it discourages the students who are least connected.
FINDING 03
Progress keeps them going.
Many believed they needed advanced Unity or Blender skills before applying. Experienced members said professors care just as much about genuine interest, visualization skills and empathy for users.
02
BACKGROUND & PAIN POINTS
Students from underrepresented and low-income backgrounds often use learning platforms that assume consistent prior knowledge and high confidence.
When they struggle, these systems provide limited explanation and rely on rigid progression, which can reinforce feelings of failure.Without clear support for knowledge gaps, students may lose confidence and disengage. This is not due to a lack of ability, but because the system isn't built for their learning needs.
Polished for School. Eden Smith. Haiti. 2017.
03
UX RESEARCH
We conducted contextual inquiry interviews with 5 participants within our target demographic (college-aged learners from diverse educational backgrounds) to understand how they interact with existing learning platforms.
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Key findings highlighted several friction points. These challenges often led to frustration and decreased confidence.
FINDING 01
The interface felt overwhelming.
FINDING 02
Users struggled with gaps in foundational knowledge.
FINDING 03
There was no clear, actionable feedback when answering questions.
Affinity Diagram
Themes
We synthesized insights using affinity diagramming and identified the core themes. These findings directly informed the design direction, including the development of adaptive difficulty to better support personalized learning and confidence-building.
04
DESIGN
INSPIRATIONS
This feature is grounded in key learning science principles that emphasize personalized, confidence-building learning experiences.
THEORY 01
Constructivism
The design encourages learners to actively engage with their understanding by making strengths and knowledge gaps visible.
THEORY 02
Vygotsky's Zone of Proximal Development
Difficulty adapts to keep tasks just beyond a learner's current ability. Acting as a "more knowledgeable other," the system guides students toward targeted support where it's needed most.
THEORY 03
McGee & Martin
Students may internalize struggle as a reflection of identity rather than a solvable gap. Findings on educational inequality show how limited support and foundational gaps can impact learning outcomes.
Together, these insights informed a system that reframes mistakes, reinforces missing concepts, and supports both skill development and learner confidence.
05
DESIGN
We moved from paper sketches to a storyboard of the core flow, then into mid-fidelity screens in Figma.
LO-FI SKETCH
The core adaptive loop on paper
Sketches mapped the flow from choosing a problem set, through quiz questions, to a skill map and an adjusted set of questions targeting the gap.
STORYBOARD
Following Alex through a skill gap
Alex, 21, studies online from an off-campus apartment. He opens Khan Academy, gets several questions wrong in a similar way, and the system names the specific skill gap instead of just marking him wrong. A short module targets that gap, he returns to the original problem with more success, and his skill map updates to show growth.
MID-FI SCREENS
Question-by-question feedback
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Mid-fi screens brought the quiz into the Khan Academy app layout, with Home, Explore and Downloads in the tab bar.
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The skill map was removed in the mid-fi iteration, as it was a bit unrelated to core functionality.
06
USER TESTING AND EVOLUTION
Throughout the cycle of the project, my team conducted contextual inquiries to improve the feature.
ROUND I
Lo-fi prototype
Introduced the core adaptive difficulty flow. During the post-lesson quiz, the system identified patterns in missed questions, named the skill gap, and directed users toward the lesson area that needed more support.
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Feedback gathered
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Users wanted clearer explanations for what they got wrong.
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Users needed the app to explicitly name the skill gap.
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Automatically opening the related lesson felt useful, but needed more context so users understood why they were being redirected.
ROUND II
Mid-fi prototype
Added question-by-question feedback, visual cues for correct and incorrect answers, and clearer messaging around which skill needed improvement
Feedback gathered
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Explanations were helpful, but needed stronger reasoning for why answers were correct.
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The feature required more in-app guidance so users could understand it without verbal explanation.
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The visual design needed to feel more polished and engaging.
ROUND III
Hi-fi prototype
Refined the experience with clearer navigation, improved visual feedback, and a more responsive adaptive difficulty system.
Feedback gathered
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Users found the flow easy to navigate and understand.
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Immediate feedback after incorrect answers helped guide learning.
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Users appreciated that the system responded to their individual performance.
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Remaining feedback focused on adding deeper explanations and further improving the UI.
Interactive Prototype
