AI Tool for College Students
How can AI as an application be used by college students to support and enhance their academic performance?
.svg)
Scope
Tools
Team
Timeline
(3 months)
Project overview
Background
Opportunity
Goal
Resultid, an AI startup, developed a solution that helps corporations store, process, and analyze big data.
As college students juggle growing volumes of personal, social, and academic information, Resultid has an opportunity to repurpose its technology to meet their needs and tap a new market.
Design a well-defined MVP B2C app for Resultid to enter and become a top player in the AI edtech market space as the lead UX researcher in a team of 4.
Objectives
- Define the target user base
- Understand user pain points in their day-to-day lives and perceptions on using AI
- Determine which design features to prioritize within the B2C wireframe
- Evaluate the AI app for usability issues
- Recommend features for future product development
Format
- Phase 1: Discovery research via literature review, online survey, competitive analyses, and user interviews
- Phase 2: Evaluative research via usability testing on prototypes and high-fidelity wireframes
Key Findings & Insights
Discovery Research
College students are often most-frustrated and spend the most time with text-heavy classes.
User interviews revealed that text-heavy course content was a major pain point, with all participants citing it as time-consuming and difficult to manage. Our nationally launched survey confirmed that students spend on average 2–3 hours per liberal arts assignment, making it the top barrier to engagement. Designing workflows to reduce cognitive load and better support time-constrained students would alleviate this pain for our users.
Most college students are adopting AI tools into their daily workflows, but are hesitant when it comes to letting AI do all the heavy lifting.
The app should emphasize AI as a learning companion rather than a replacement and give users autonomy over the level of AI assistance they are receiving. To address academic integrity concerns, we also suggest educator-approved modes to build trust and promote responsible use. The tool should offer personalized solutions beyond simplifying course content to help college students enhance their academic performance through integrating interactive elements or performance-enhancing features.
Evaluative Research
Users struggled to learn how to use certain features and experienced confusion around the meaning of specific icons and interface elements.
Low learnability and ambiguous UI elements created friction during first-time use, leading to reduced confidence and slower task completion. The app should provide contextual guidance such as tooltips or microcopy and interactive walkthroughs during onboarding to support feature discover and initial understanding.
Snapshot of usability testing as the design evolved from mid- to high-fidelity
❗️ All participants had questions about the functions of the toolbar icons.
-->
💡 The toolbar icons need to have clearer labeling.
Conclusion
Through this research we were able to define the product vision and produce prototypes for 3 new AI education tools for college students with favorable results.
Future direction
As development continues, research with other user segments (professors, teaching assistants) would be valuable in uncovering new workflows and guiding educator-approved modes.
Limitations
- This research was conducted with zero budget. Users were recruited organically through word-of-mouth and social media.
- Due to limited resources and a short timeframe, prototypes for STEM students (number-heavy operations, scientific charts and graphs) were not tested.