MIND MENTOR
An Adaptive AI Learning Companion for Student Wellness
Mind Mentor Demo video
Click screen to watch demoMind Mentor is an AI-powered learning support system designed to help college students build emotional awareness, manage stress, and develop sustainable wellness habits.
The system uses an adaptive instructional model to personalize each interaction based on user mood, engagement, and goals. Through guided check-ins, micro-lessons, and reflective prompts, it supports real-time decision-making and long-term behavior change.
Each interaction follows a structured learning flow—check-in, reflection, strategy, and action—while also building on previous responses to reinforce progress and encourage consistency over time.
The system intentionally designed as a wellness support tool, not a clinical solution. It provides accessible, everyday guidance while maintaining clear boundaries around mental health support.
The Problem
Many students struggle with stress and task overload but lack accessible, personalized support tools that provide real-time guidance. Traditional resources are often static, reactive, or underutilized.
The Challenge
College students often experience high levels of stress, overwhelm, and difficulty managing academic responsibilities. While universities offer wellness resources, these supports are often static, reactive, or difficult to access in the moment.
As a result, many students lack personalized, real-time guidance to help them manage stress, prioritize tasks, and build consistent habits.
My Role
I designed and developed Mind Mentor as an AI-driven learning support system, including the instructional strategy, conversational flow, and prompt design.
I structured the experience to support adaptive, personalized learning through guided interactions that help users reflect, regulate emotions, and take actionable steps.
Design Approach
Mind Mentor was designed as an adaptive, conversational learning system grounded in instructional design principles such as Backwards Design and the ADDIE framework.
While the experience feels conversational, it is intentionally structured as a guided instructional system. Each interaction follows a flow of check-in, reflection, strategy, and action.
The system uses prompt design and conversational UX to scaffold thinking—helping users identify priorities, manage stress, and break down complex tasks into manageable steps.
It draws on principles of behavior change and self-regulated learning to support both immediate decision-making and long-term habit development.
Outcome
Mind Mentor demonstrates how AI can provide adaptive, personalized support in real-world situations.
The system helps students develop stronger self-regulation skills, reduce feelings of overwhelm, and build sustainable wellness habits. By breaking down tasks, guiding reflection, and supporting decision-making, it enables users to maintain focus and improve both academic performance and overall well-being.
Future Iteration
Future development will include user testing and data collection to evaluate effectiveness and refine the experience.