George Dombi

George Dombi
Chemistry Department

George Dombi leverages LibreChat to systematically analyze student feedback from his pre-semester Chemistry Boot Camp, revealing evolving patterns in student engagement and providing data-driven insights for continuous course improvement.

George has taught Chemistry at URI since 2010 and was promoted to the rank of Teaching Professor in June 2023. He has been a member of the Process Education Society since 2018 and uses many of their tools and techniques in his classes. He primarily teaches CHM 103: Introductory Chemistry. He has taught CHM 103 a total of 38 times across Fall, Spring and Summer semesters.

Introduction

Spotlight feature written by: Braden Hutchins

George Dombi is a Teaching Professor in the Chemistry Department at URI, specializing in introductory chemistry. With over 15 years of teaching experience and 38 sections of CHM 103, George has developed innovative approaches to enhance student engagement and learning outcomes. His recent focus has been on using AI to analyze student feedback from his 9-day pre-semester Boot Camp that helps students refresh their high school chemistry knowledge before diving into college-level coursework.

Quote

“LibreChat is a wonderful chatbot that allows for easy access to large language model reading and analysis models.”
– George W. Dombi

As George implemented his Boot Camp program for the Fall 2024 to Spring 2025 academic year, he recognized an opportunity to leverage artificial intelligence to better understand student experiences and improve the program. Rather than simply collecting feedback and manually reviewing it, he sought a more systematic approach to analyze student responses and identify patterns that could inform future iterations of the Boot Camp. This led him to explore LibreChat as a tool for comprehensive feedback analysis, allowing him to compare student responses across different semesters and extract meaningful insights about student engagement and learning preferences.

Usage

George utilizes LibreChat as a powerful analysis tool to systematically review and compare student feedback from his pre-semester Boot Camp activities. The process begins with collecting student responses through Brightspace, where participants provide feedback about their 9-day online Boot Camp experience. These responses are then downloaded and compiled into a Word document, which is imported into LibreChat for comprehensive analysis.

Q: Was the Boot Camp and its feedback mandatory or optional?

A: The Boot Camp is optional but incentivized through homework credit. It achieved high participation rates, while feedback collection was voluntary and had lower engagement.

George’s class is structured to give students the whole semester to complete 800 homework problems. The Boot Camp provides students with an additional 80 homework problems before the semester starts, giving them more time to get a head start on completing them. This structure achieves remarkable participation rates of 89-94%, demonstrating that students recognize its value when properly incentivized.

Q: How do you plan to improve student engagement with feedback analysis in the future?

A: Students showed less interest in the non-incentivized feedback, with only 20-30% providing a response. We discussed offering academic credit to increase these numbers if more responses were desired.

The feedback component of the Boot Camp remains entirely voluntary, resulting in much lower participation than the extra homework problems. This difference suggests that while students value the learning experience and the extra time to work on homework, without that incentive, it is much harder to get student interaction. Using the analysis of LibreChat, George noted interesting patterns in the feedback given, observing that Fall students (new to college) mentioned high school preparation more frequently, while Spring students (not new to college) provided more detailed and nuanced feedback about their learning experience. 

Q: What are the pros and cons of using LibreChat?

A: LibreChat offers free, accessible AI analysis capabilities for URI community members, though it lacks some advanced analytical features found in specialized tools like Insight Generator.

The primary advantages of LibreChat include its cost-free availability to URI faculty, staff, and students in the pilot, making it an accessible tool for educational analysis. George appreciates its straightforward interface and ability to process multiple sets of student responses simultaneously. However, George noted that LibreChat has some limitations compared to more advanced AI tools. One example he mentioned was Insight Generator, a ChatGPT feature that offers in-depth analysis of qualitative data such as student feedback. It highlights key themes, sentiments, and trends, providing structured summaries and visual insights. Unlike LibreChat’s general-purpose interface, Insight Generator is designed specifically for deeper data exploration and is available through a ChatGPT Plus subscription ($20/month) by uploading text and selecting it from the tools menu.

Student Experience & Feedback

While LibreChat serves as a valuable instructor tool for feedback analysis, direct student engagement with the AI-generated insights has been limited, though the tool’s indirect benefits are evident in course improvements. LibreChat effectively processes and analyzes student feedback to provide valuable insights for course improvement, however when George presented LibreChat’s comparative analysis of peer feedback to students, they showed minimal interest in the analysis.

However, the indirect benefits of LibreChat usage are more promising. The tool’s analysis has enabled George to make data-driven improvements to the Boot Camp structure and content delivery, which ultimately enhances the student experience even if students aren’t directly engaged with the analytical process. This suggests that LibreChat may be most effective as a behind-the-scenes instructor development tool rather than a direct student-facing resource, allowing faculty to refine their teaching approaches based on systematic analysis of student input.

Using LibreChat at URI

LibreChat is a pilot program that makes generative AI easy and accessible for the URI community. It offers a range of language models to support everything from content creation and brainstorming to data analysis and task simplification. You can request access to the LibreChat pilot with a brief justification. Once approved, log in via Microsoft MyApps Portal using your URI SSO and MFA. Visit the LibreChat service page for more details.

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