SHAO Linzhengrong (SHAO-Lin)
Academic AI is an innovative product designed to create a platform that assists people in the academic field with daily tasks. It aims to become the best assistant for researchers by offering comprehensive support. Our goal is to help researchers maximize their potential and achieve their academic objectives. This project is a collaborative startup with three PhD scholars from Peking University.
Client:
Professors and Students
My Role:
Project Manager & UX/UI Designer
Year:
2023.7-2024.01
Service Provided:
Product Management, Web Design
Pain Point
Based on the daily experiences of PhD and master’s students, we found that academic research is often hindered by various inconvenient challenges. Here are some common issues we’ve identified in our research routines.
User Journey
We gathered insights from researchers around us about their experiences in academic work. Using these insights, we developed user stories to better understand and address the challenges they face in daily academic life.
User Feedbacks
We developed an initial, simplified version of Academic AI with key features and conducted interview-based research by providing it to four researchers for testing. Through these interviews, we gained valuable insights into their actual needs, user experience, and suggestions for improvement.
Function Structure
Based on user feedback and our previous research, we discussed and outlined the core features we aim to develop for Academic AI. This process allowed us to refine our understanding of user needs and translate them into a structured feature set. Our discussions guided us toward building an Academic AI solution that effectively addresses researchers’ everyday challenges.
Wireframes
Based on the identified features, we created a basic wireframe to visualize the layout and flow of Academic AI. This wireframe outlines the main functionalities and provides a clear structure, helping us plan the user experience and ensure each feature is accessible and intuitive for researchers.
The creation of Academic AI has been an incredibly engaging journey. As researchers ourselves, we found shared insights across many aspects of the research process. Along the way, I explored the research practices and content from other disciplines, broadening my understanding of diverse academic needs. Through continuous product iteration and user feedback, we ultimately developed the final version of Academic AI.
