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.
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