Promoting AI Literacy in Higher Education: Evaluating the IEC-V1 Chatbot for Personalized Learning and Educational Equity
Project Overview
The document highlights the application of the IEC-V1 chatbot, a generative AI tool designed to enhance AI literacy among future educators and facilitate personalized learning experiences. By enabling users to tailor responses to their specific needs, the chatbot addresses educational disparities and promotes equitable access to information. A pilot study demonstrated favorable user experiences, underscoring the necessity of integrating AI competencies into teacher training. The findings suggest that the chatbot not only aids in individual learning but also prepares educators to effectively incorporate AI into their teaching practices, ultimately contributing to a more informed and capable teaching workforce in the digital age.
Key Applications
IEC-V1 Chatbot
Context: Prospective teacher training students at Heidelberg University of Education, used in a seminar on digital media in foreign language teaching.
Implementation: The chatbot was tested in a seminar where students interacted with it after an introduction, using URLs and PDF files as sources for questions.
Outcomes: Students rated the chatbot positively for user-friendliness and the ability to customize response levels. It was seen as beneficial for supporting diverse learning needs.
Challenges: Issues with connectivity, PDF file recognition, and response speed were identified, along with the need for improved user interface design.
Implementation Barriers
Technical Barrier
Access restrictions due to firewall settings impacted the usability of the chatbot during testing.
Proposed Solutions: Potential solutions include disabling the firewall temporarily or using alternative hosting options such as HuggingFace.
User Experience Barrier
Some students had trouble accessing the chatbot, leading to interruptions during use.
Proposed Solutions: Improving connection stability and ensuring the application can be hosted on a reliable server without local installations.
Project Team
Stefan Pietrusky
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Stefan Pietrusky
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