PortfolioMentor: Multimodal Generative AI Companion for Learning and Crafting Interactive Digital Art Portfolios
Project Overview
The document explores the application of PortfolioMentor, a multimodal generative AI tool tailored for non-technical design students, facilitating the creation of interactive digital art portfolios. By acting as a coding companion, PortfolioMentor offers proactive suggestions and assistance throughout the creative process, encompassing visual, audio, and interactive components. This innovative tool seeks to address the coding knowledge gap faced by art students by leveraging natural language processing and generative models, ultimately aiming to enhance their creativity while alleviating the mental strain related to coding tasks. The findings indicate that such generative AI applications in education not only empower students to express their artistic visions more effectively but also foster a more inclusive learning environment where technical skills do not hinder creativity. Overall, the integration of generative AI in educational contexts like PortfolioMentor demonstrates significant potential to transform the learning experience, encouraging innovation and reducing barriers for students in creative fields.
Key Applications
PortfolioMentor
Context: Educational context for non-technical design students in art schools.
Implementation: Developed as a chatbot integrated into creative coding environments to assist students.
Outcomes: Supports the co-creation of digital artworks, enhances student creativity, and simplifies coding processes.
Challenges: Students face information barriers, lack of community support, mental barriers with coding, and difficulties in translating artistic ideas into code.
Implementation Barriers
Information Barrier
Non-technical students struggle to navigate coding materials and forums, and have difficulties translating creative visions into code due to coding limitations.
Proposed Solutions: Incorporate generative AI to simplify technical content into natural and visual languages, and utilize generative models to assist in rendering artistic visions into code.
Lack of Community Support
Insufficient support from teaching assistants, peers, and instructors for art students learning to code.
Proposed Solutions: Create an easy-to-use chatbot that provides constant support and guidance.
Mental Barriers with Coding
Students find the debugging process overwhelming due to their limited technical experience.
Proposed Solutions: Use AI to simplify coding tasks and provide emotional support.
Project Team
Tao Long
Researcher
Weirui Peng
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Tao Long, Weirui Peng
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai