Location
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Document Type
Event
Start Date
19-11-2024 4:00 PM
Description
Cogni-Resource is a unified platform enhanced by AI that merges the introspective analysis of Cogni-Reflect with the precise resource exploration functions of the Learning Resource Finder, providing a holistic tool to improve educational environments. The Cogni-Reflect component uses advanced Large Language Models (LLMs) to examine student reflections, giving educators instant insights into learning results, difficulties, and areas where students may require extra assistance. Cogni-Reflect allows instructors to adjust their teaching by analyzing key themes and topics in reflective narratives, leading to a more adaptive and successful learning atmosphere. Using both web scraping and OpenAI API integration, the Learning Resource Finder gathers educational content tailored to the specific needs of students. This tool sifts through and pairs up useful resources, like articles, tutorials, and research papers, with the exact topics and learning goals students are focusing on, getting rid of unimportant content and offering fast access to top-notch materials. Collectively, these instruments make up Cogni-Resource, a platform that not only simplifies the typically lengthy process of reflection analysis for teachers but also enables students to autonomously delve into selected, tailored materials. Cogni-Resource promotes an educational setting where both assessing learning advancement and finding personalized materials are made easier, emphasizing both instructional excellence and student independence. Educational institutions that utilize Cogni-Resource have the ability to take a comprehensive approach to analytics and content delivery. This allows educators to make informed, timely modifications to their teaching methods while also assisting students with their self-directed learning paths. In the end, Cogni-Resource connects reflective analysis and resource accessibility, improving educator interventions and student learning outcomes with the help of AI.
Included in
GMR-210 Cogni-Resource: AI-Driven Reflective Feedback Analysis for Enhanced Learning Insights and Resource Discovery
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Cogni-Resource is a unified platform enhanced by AI that merges the introspective analysis of Cogni-Reflect with the precise resource exploration functions of the Learning Resource Finder, providing a holistic tool to improve educational environments. The Cogni-Reflect component uses advanced Large Language Models (LLMs) to examine student reflections, giving educators instant insights into learning results, difficulties, and areas where students may require extra assistance. Cogni-Reflect allows instructors to adjust their teaching by analyzing key themes and topics in reflective narratives, leading to a more adaptive and successful learning atmosphere. Using both web scraping and OpenAI API integration, the Learning Resource Finder gathers educational content tailored to the specific needs of students. This tool sifts through and pairs up useful resources, like articles, tutorials, and research papers, with the exact topics and learning goals students are focusing on, getting rid of unimportant content and offering fast access to top-notch materials. Collectively, these instruments make up Cogni-Resource, a platform that not only simplifies the typically lengthy process of reflection analysis for teachers but also enables students to autonomously delve into selected, tailored materials. Cogni-Resource promotes an educational setting where both assessing learning advancement and finding personalized materials are made easier, emphasizing both instructional excellence and student independence. Educational institutions that utilize Cogni-Resource have the ability to take a comprehensive approach to analytics and content delivery. This allows educators to make informed, timely modifications to their teaching methods while also assisting students with their self-directed learning paths. In the end, Cogni-Resource connects reflective analysis and resource accessibility, improving educator interventions and student learning outcomes with the help of AI.