Computing Identity Development for Mixed Experience Students in Hispanic Serving Community College Artificial Intelligence Courses

• In Event: Technology and Student Learning

Abstract

This qualitative phenomenological study investigates computing identity development in introductory AI courses at one of the largest Hispanic Serving Community Colleges in the country. Due to the community college context and the introductory nature of the courses, students have a broad range of prior expertise and/or ability in computing, which influences the classroom experience of students enrolled in the courses. This study uses an identity framework consisting of interest, competence/performance, and recognition. Preliminary findings indicate that the mixed classroom has both benefits and hindrances to identity development for both groups of students. Recognizing the presence and the influences of mixed ability classrooms allows educators to employ pedagogical strategies to maximize the learning of all students in the course.

Authors

• Paul Charles Bigby, Virginia Tech

• Sarah Rodriguez, Virginia Tech

• Antarjot Kaur, Virginia Tech

• kylee Shiekh, Virginia Polytechnic Institute and State University

• Benjamin Chaback, Virginia Polytechnic Institute and State University