Developing an AI and Engineering Design Hybrid-Remote Summer Camp Program for Underrepresented Students (Evaluation)
- Conference
- Location
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Portland, Oregon
- Publication Date
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June 23, 2024
- Start Date
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June 23, 2024
- End Date
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July 12, 2024
- Conference Session
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Mr. Burns' Brainchild: AI in the Springfield STEM Classroom, Release the Hounds!
- Tagged Division
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Pre-College Engineering Education Division (PCEE)
- Tagged Topic
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Diversity
- Permanent URL
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https://strategy.asee.org/47157
Paper Authors
Alvin Talmadge Hughes IV University of Florida
Alvin (TJ) Hughes is a graduate of the University of Florida with a Bachelor of Science in Materials Science and Engineering and a minor in Engineering Innovation. He has interests in additive manufacturing, materials analysis, and data analytics. He is the Data Science/AI curriculum lead for the EQuIPD grant at the University of Florida currently manages teams working on Python Professional Development for teachers interested in Data Science, as well as school and camp curriculums centered around Artificial Intelligence. Previously, he has worked as an instructor at Mathnasium, where he taught math to K-12, and as a lab assistant in an undergraduate laboratory at the University of Florida.
Jacob Casey Yarick University of Florida
Jacob Yarick is an undergraduate student at the University of Florida pursuing a Bachelor of Science in Aerospace Engineering and Bachelor of Science in Astrophysics. He works under the EQuIPD program where he designs, creates, and teaches lessons related to Python programming and Artificial Intelligence. Previously, he has worked at the Kika Silva Pla Planetarium, and the Calusa Nature Center & Planetarium. He has also tutored math and physics at Santa Fe College, and was the Teaching Assistant for Astrophysics 1 at the University of Florida.
Nancy Ruzycki
University of Florida
orcid.org/0000-0001-7516-2985
Dr. Nancy Ruzycki, is the Director of Undergraduate Laboratories and Faculty Lecturer within the Department of Materials Science and Engineering at the University of Florida Herbert Wetheim College of Engineering. Her focus is on developing curriculum ba
Hajymyrat Serdarovich Geldimuradov University of Florida
A native of Ashgabat, Turkmenistan, Hajymyrat grew up in Bolivia and moved to the United States in 2012. Since the beginning of his computer science studies and after obtaining his bachelor's in computer science at the University of Florida, he has gained quite a bit of knowledge on data science and machine learning, spurred by the wide range of emerging applications. Through various projects, he has gained extensive experience with deep learning models and data interpretation. As such, with an emphasis on theory and a strict adherence to the machine learning pipeline, he is always keen on delivering tried and tested products.
Sarah Louise Langham University of Florida
Sarah Louise Langham is a graduate of the University of Florida with a Bachelors of Science in Materials Science and Engineering. She is a format and content reviewer for EQuIPD grant Data Science/AI curriculum development. She has researched polyelectrolytes and rheological behavior under Dr. Neitzel at the University of Florida. Her interests are polymer chemistry, additive manufacturing, and data analytics.
Katherine Miller University of Florida
Katherine Miller is a graduate of the University of Florida with a Bachelor’s of Science in Materials Science and Engineering. She is a content and format reviewer for EQuIPD Data Science and AI curriculum. Her other research is in biomaterials, focusing on naturally derived hydrogels under Dr. Josephine Allen at the University of Florida. Her interests are additive manufacturing, STEM education, and remote sensing of hazardous materials.
Abstract
This paper evaluates creation and implementation of a hybrid-remote (the partial remote instruction of in-person students) summer camp curriculum developed using an Inquiry-Based Conceptual Model for underrepresented students to gain relevant Data Science and Artificial Intelligence (AI) concepts. In the field of AI, diversity is key to improving data sets and are crucial to avoiding detrimental bias outcomes, making it essential that underrepresented students are provided with opportunities to participate.
In the Summer of 2023, the EQuIPD grant from the University of Florida assisted Upward Bound/UNITE with curriculum creation and remote delivery for a camp serving underprivileged minority (URM) students, being held at the Miami Dade College Homestead Campus, located in one of the largest education districts in the Southeastern United States. Upward Bound is a US Department of Education grant program aimed at serving low-income underrepresented middle and high school students. The camp served 30 students from the school district, selected by Upward Bound at Miami Dade College college. While the camp presented four educational topics, the EQuIPD grant was responsible for development of two sections covering Artificial Intelligence (AI) and Python Programming, which each took place twice a week for one period each on the same day. The grant developed curriculum for AI and Programming sections, created teacher instruction guides and resources for the AI section, and remotely instructed the Programming section to in-person students at Miami Dade College.
The goal of curriculum developed by the EQuIPD grant was to seamlessly tie concepts and real-world applications of AI with the practicality and creativity of programming. Students were taught a variety of problem-solving methods and design concepts, ethics and responsibilities as they relate to AI, conceptualization of AI processes and chatbot principles, Python programming basics, and constructing their own programs. These sections worked alongside each other, culminating in students being able to develop and present their own personalized rules-based chatbot. Afterwards, students were surveyed on their experiences and desire to continue education in the field of Programming and AI, which was analyzed and reflected upon to determine possible alterations for future iterations of this curriculum.
This paper will focus on the following aspects of this cooperation: (1) How can we utilize an Inquiry Based-Conceptual Model to encourage future learning and retainment of information? (2) How can we use cloud-based interactive tools to expand student access and serve the underrepresented youth in order to provide confidence to pursue data science careers through relevant industry knowledge? (3) How can we incorporate various methods of thought such as systems thinking, engineering design, computational and algorithmic thinking to teach students efficient problem solving and draw the connection between the art of programming with the concepts of AI? (4) What parts of the developed curriculum were found adequate by students, and which areas need to be improved?
Feedback was obtained from student qualitative post-survey data via Qualtrics and communication with in-person instructors of the AI curriculum to determine the effectiveness of the hybrid-remote structure in order to refine the course for future implementation.
Hughes, A. T., & Yarick, J. C., & Ruzycki, N., & Geldimuradov, H. S., & Langham, S. L., & Miller, K. (2024, June), Developing an AI and Engineering Design Hybrid-Remote Summer Camp Program for Underrepresented Students (Evaluation) Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://strategy.asee.org/47157
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