Case Study

LearnWise: academic resource optimization for students under time pressure.

LearnWise ranks study actions by urgency, weak topics, learning preference, time available, and expected ROI, then turns the result into a strategy brief and study schedule.

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Problem

Students have limited study time and too many possible resources.

When a student is behind, the hard question is not whether to study. It is which action will help most: lecture review, tutoring, quizzes, practice problems, notes, or office hours.

Users

Students trying to improve course outcomes efficiently.

The target user is a college student balancing multiple classes, deadlines, weak topics, and limited time before exams or assignments.

Product

A recommendation engine for high-impact study actions.

LearnWise turns course risk, topic weakness, available time, and resource type into ranked recommendations, a strategy brief, and an exportable study plan.

Technology

Frontend recommendation logic with a student dashboard.

The project uses HTML, CSS, JavaScript, structured scoring logic, and dashboard design to model academic decision support without needing a heavy backend.

Architecture

How LearnWise ranks study recommendations.

Student Inputs Course, grade risk, weak topics, available time, and learning preference

Scoring Logic Urgency, expected impact, resource fit, topic weakness, and ROI weighting

Dashboard Ranked study actions, strategy brief, risk summary, grade impact, schedule, and resource options

Student Action Choose the highest-value study resource, follow a deadline-aware schedule, and export the plan

What I Built

Core features

Recommendation logic that ranks resources by urgency, topic weakness, time, and ROI.
Course risk dashboard for understanding where academic attention is needed.
Strategy brief and deadline-aware schedule that explain the recommended study path.
Copyable and downloadable study plan for saving or sharing the output.

What I Learned

Decision support design

How to create useful scoring logic without making the system feel complicated.
How to prioritize recommendations around user context instead of generic advice.
How to design a dashboard that explains risk, action, and expected impact.
How to turn recommendation output into a usable plan students can act on immediately.

Roadmap

Where LearnWise goes next.

User profiles Saved study plans Calendar deadlines Course history AI study planning Resource effectiveness tracking