Why This? Why Now?

As a grad student juggling academics, design, and life, I noticed a common pattern: I had plenty of goals, but breaking them into manageable, motivating pieces took a lot of energy. And I wasn’t alone.

While researching personal productivity tools, I noticed a clear pattern: most apps were great at helping users track what they’d already planned, but offered little support when it came to structuring or initiating those plans. The gap wasn’t in reminders, it was in guidance.

Research Plan

To get started I utilized the methods below to get gain insights about the domain of my project and more importantly gain insights about college students.

Literature Review: Reviewed existing research on student goal setting, task management, and motivation to establish a theoretical foundation.

Competitive Analysis: Analyzed existing task management apps (Todoist, MyStudyLife, and Notion) to identify strengths, weaknesses, and gaps in the market.

User Research:

• Surveys: Distributed surveys to a broader student population to quantify findings and identify common trends. The survey included questions on current practices, pain points, and interest in AI-driven solutions.

• Student Interviews: Conducted one-on-one interviews with three college students to gather qualitative insights into their goal-setting behaviors and challenges.

Literature Review

Secondary research highlights the importance of effective goal setting, which significantly improves student outcomes. Key findings include:

Goal Setting:

• Effective goal setting involves making goals specific, measurable, achievable, relevant, and time-bound (SMART). This approach helps establish a clear direction for learning and enhances student motivation and performance. Marzano, Pickering, and Pollock (2001) emphasized that structured goal-setting techniques are crucial for academic success .

Self-Regulated Learning and Time Management:

• Time management, a critical aspect of self-regulated learning, involves planning and controlling how much time to spend on specific activities. Effective time management is linked to better academic performance and reduced procrastination. Zimmerman’s study (2002) highlights that self-regulated learners who manage their time and set specific goals tend to achieve higher academic success .

Interventions to Reduce Procrastination:

• Structured goal-setting techniques can help reduce academic procrastination by breaking down larger tasks into manageable steps. This aligns with systematic reviews suggesting that goal setting is essential in helping students manage their tasks and achieve their academic objectives .

Competitive Analysis

Is there a demand?

Market Viability: I began by assessing existing goal-setting apps to understand the current market and identify user pain points and unmet needs. This helped validate whether there was genuine demand for a new AI-driven solution. According to The Global Reports, the goal setting app market is valued at $289 million at 2022 with projected increase of $422.9 million by 2029. This shows a growing demand for productivity apps focused on goal management.

What is currently out in the market?

Through a competitive scan of leading productivity apps like Todoist, Notion, and MyStudyLife, a pattern became clear:

Most tools were optimized for tracking—not thinking. They helped users check things off, but rarely helped them plan in the first place.

Across the board, I found:

• Static checklists and calendar-based reminders

• Limited support for goal breakdown or adaptive structure

• No integration of AI to assist with strategy or personalization

Despite their polish, these tools expected the user to do all the cognitive heavy lifting.

Gap Identified

There was space for a tool that could:

• Reduce decision fatigue by breaking down large goals into smaller, actionable tasks

• Provide guided structure, especially for users who struggle with planning

• Leverage generative AI to personalize and adapt to each user’s context over time

Assumptions Mapping

Before conducting user research, I did an assumptions mapping exercise to identify what were my main concerns I wanted to uncover for my iteration of mobile app.

• Lack of Formal Goal Setting: Many students don’t use formal goal-setting methods and prefer to keep goals in their heads.

• Breaking Down Goals Increases Achievability: Breaking goals into smaller tasks increases their perceived achievability and leads to higher success rates.

• Reward Systems Increase Motivation: Implementing a reward system for achieving goals within the app will boost student motivation and commitment.

• Reducing Cognitive Load with AI Assistance: AI assistance in organizing and managing tasks will reduce cognitive load and improve task management.

User Research – Insights from Students

To validate my assumptions I conducted 3 interviews and 30 online surveys with college students (ages 18–23) at California State University, Long Beach.

Key Insight:

“I know what I want to do—I just don’t know how to start"

Patterns that emerged:

• Students struggled with turning goals into action plans.

• They wanted more guidance and automated planning.

• Motivation increased when progress felt visible and rewards were clear.

Personas & User Journey

I distilled survey and interview findings into a persona and user journey map to empathize with college students. I identified that they experienced the most friction at the beginning of the goal setting process.

Insights Summary

Based on comprehensive research, including user interviews, literature review, and competitive analysis, I identified the primary issues faced by college students in achieving their goals: lack of specificity and structure in goal setting, significant procrastination, constant distractions, and poor time management.

Specific Issues to Address in Design:

• Undefined Goals: Students often have goals that lack specific steps, deadlines, and measurable outcomes, leading to confusion and hampered progress.

• Procrastination: Many students delay starting tasks because they seem too large or daunting, resulting in rushed, last-minute efforts that compromise quality.

• Time Management: Students struggle with effective time management, leading to poor prioritization and inefficient use of time.

Developing the Idea

A mobile app with a flexible input system that will allow a LLM enough context to generate relevant tasks for college to students to achieve their academic goals.

Goal Creation – From Chat box to structured Inputs

Rather than locking users into a rigid form, Task Track uses free-form input combined with structured tagging: estimated time, due date, and personal reward.

Prompt Engineering as UX

I first wanted to know how much information a LLM would need to create a comprehensive plan for college students to follow for any related tasks towards their academic goals. Using large language models (LLMs), I tested dozens of structured prompt formats to generate task lists from user-defined goals.

Most effective format:

“I’m a college student and want to [goal]. I estimate this will take [X hours], and I need to finish by [date].”

This prompt yielded tailored sub-tasks, study schedules, and timelines that could be integrated into a task manager.

While users type…

A SMART Goal Preview appears in real time—generated by the AI—reframing their casual goal into something structured and achievable.

This feature:

• Maintains creative flexibility

• Builds user confidence in their plan

• Teaches better goal-setting through live feedback

It’s not just assistive—it’s educational.

Feature developments

Task Track’s interface was designed not just to function, but to motivate. Every visual and interaction decision was made to reduce friction, reinforce progress, and keep the user emotionally engaged with their goals.

Mobile App Features

• Home: Daily task tracker + completion ring

• Task Cards: Modular, expandable, AI-generated

• Goal Edit: Free-form goal input with structured tags

• Calendar: Monthly view with embedded AI-created tasks

• Rewards: Completion-based incentives

• Metrics: Visual history of goals completed and progress over time

Each interaction was designed to feel intuitive, fast, and motivating.

Delivering the Prototype

Usability Testing + AI Output Evaluation

1. AI Capability Test:

Result: Tasks generated were somewhat generic but still usable. Users indicated a desire for more personalization and ongoing learning from the AI to adapt tasks to individual schedules and preferences.

2. Design & Usability Test:

Result: Users found the interface clean, straightforward, and easy to navigate. They wanted insight into how tasks were generated and suggested gamification features to make the experience more engaging.

What I Learned

Potential for AI: Generative AI can streamline goal creation and management, but must evolve to offer deeper personalization and context.

User Intent Matters: AI cannot fully compensate for vague or poorly defined goals; users must still articulate clear intentions.

Delight & Engagement: As user flows simplify, the role of design in creating an engaging, delightful experience becomes even more critical.