Recommendation
According to the data input by the user, we will customize their recommendation page based on their major, daily routine, and preferences, finding the most suitable courses for them, enable students growth more professional.
Make Your College Life Easier
College students struggle with course selection due to fragmented information across multiple platforms, lack of peer reviews, and complex scheduling requirements.
Create a modern, unified class picking system that combines course information, professor ratings, and AI-powered recommendations in one intuitive platform.
Streamlined course selection process, better-informed academic decisions, and improved student satisfaction with their class schedules.
Conducted interviews with over 100 University of Utah students to gather feedback on the registration system, identify demands for new features, and understand the most important features and critical issues in the current system.
Designed the initial user interface for Acdemix, focusing on creating an intuitive and user-friendly experience. Collaborated closely with developers to ensure the successful delivery of the first edition, aligning the design with technical requirements.
Collaborated closely with developers to ensure the successful delivery of the first edition, aligning the design with technical requirements. Collected feedback from test users, analyzed their input, and implemented multiple iterations to enhance usability and address user needs effectively.
Students face uncertainty in course selection, struggling to find classes that match their:
The current registration system is:
Academix aims to create a comprehensive solution by:
Key objectives:
I wish I had better insights about courses before registering. Past students' experiences would really help me make better choices.
Undergraduate Student, 20
As a senior, I want to share my course experiences to help other students make better choices.
Senior Student, 22
I need to understand how my courses are perceived by students to improve the learning experience.
Professor, 45
According to the data input by the user, we will customize their recommendation page based on their major, daily routine, and preferences, finding the most suitable courses for them, enable students growth more professional.
We have developed several features in the search function. Students can use filters to select courses based on their preferences. The searching system is also smart enough to recommend courses that are similar to the ones they are looking for.
In the history section of the user profile page, students can add or edit the courses they have already taken. This allows them to better track their registered courses and receive more explicit course recommendations.
We have implemented a feedback system that allows students to provide feedback on the courses they have taken. This feedback is used to improve the course recommendation system and make it more accurate.
Final designs focusing on clarity, accessibility, and user experience