Year: 2024
Type: conference-paper
Study design: Observational Study
Abstract: First-year Electrical and Computer Engineering students from two institutions engaged in a collaborative project to develop a smart home device using sensors and actuators learned in their introductory courses.They reflected on the project, and their feedback was analyzed using unsupervised and Natural Language Processing techniques like K-means clustering and Latent Dirichlet Allocation.Key methods included data preprocessing and cleaning.AI tools like TF-IDF vectorization and ChatGPT helped identify key themes such as "PROJECT," "PARTNER," "WORK," and "LEARNED."This study highlights NLP's role in enhancing educational strategies and understanding student experiences.
DOI: 10.18260/1-2--48593
Authors: Toluwani Olukanni, Majd Khalaf, Michael Cross, David Feinauer, Ali Al Bataineh
Institutions: Norwich University, Virginia Military Institute
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4401834161