Problem
Parents are cautious about screen time and digital distraction. Educators need games to support, not compete with, instructional time. Kids’ engagement in the game needs to translate into actual reading behavior.
Understanding how much resistance existed across these groups, and what would make a feature feel acceptable to cautious adults while still genuinely engaging kids, required methods that could capture both the scale of attitudes and the reasoning behind them.
Parents
- Cautious about screen time and digital distraction
- Skeptical of AI-driven features, though not dismissive of their value
- Prioritize visible educational outcomes over entertainment
Educators
- Need games to support, not compete with, instructional time
- Focused on minimizing classroom disruption
- Evaluate new features through a pedagogical lens
Children
- Motivated by earning and unlocking rewards through reading
- Responded enthusiastically to hands-on prototype testing
- Express preferences directly and concretely when given a choice
Research Design
Survey (n=800+)
The survey came first, mapping the boundaries: how much resistance exists, where parents and educators diverge, what each group values. It showed where the lines were, not how to design within them.
- Answered: how much resistance exists, where groups diverge
- Left open: how to design within those boundaries
Interviews (10+ sessions)
The interviews came next, using interactive prototypes to test specific game mechanics against those boundaries. This answered what the survey couldn't: what makes a feature feel acceptable to adults and genuinely engaging for kids at once.
- Answered: what specific mechanics feel acceptable and fun
- Built on: boundaries established by the survey
1. Survey
Mapped baseline attitudes toward gamification and AI across parents and educators, and which features each group prioritized. I analyzed the data in Python, using descriptive statistics and cross tabulation to compare priorities across parents, educators, and children's enjoyment.
Sensory and ambient features split parents and educators sharply. AI showed something stranger: high resistance overall, but almost no one rated it as zero value. The two attitudes did not move together, and the survey alone could not explain why.
2. Interviews
Tested specific game mechanics within the prototypes directly with families and educators, structured around parent-child pairs. Including children as active participants, not just observers, gave direct behavioral evidence rather than reported preference.
I coded transcripts thematically across four areas: attitudes toward the prototypes, genre preferences, reward systems, and design parameters. Design parameters turned out to be the most actionable, comparing how adults evaluated educational value against how children responded to specific mechanics.
Synthesis
The survey identified where parents and educators diverged and flagged an unresolved tension around AI. The interviews showed how specific design choices could resolve that tension, by giving adults and children different reasons to value the same feature.
Together, they moved the research from "this group is skeptical" to a concrete design direction, one that addressed the skepticism without losing what made the feature work for kids.
Impact
The findings led to meaningful changes in how the feature was structured. Based directly on the boundaries the survey identified and the design parameters the interviews surfaced, the product team adjusted the feature's core mechanics, access model, and timing logic. The feature is currently in active development.