Discipline: Computer Sciences & Information Management
Subcategory: STEM Science and Mathematics Education
Kinnis Gosha - Morehouse College
Co-Author(s): Chance Lewis and Jennifer Albert
Morehouse College will conduct a research project to uncover new insights regarding the effect of culturally relevant career exploration resources on high school students’ career interests. The researchers propose a mixed-methods research design using quantitative and qualitative data to examine the effects of using embodied conversational agents (ECAs) in virtual career exploration fairs with rural and urban high school students. Building on previous research that shows that ECAs are as effective as humans when used to mentor undergraduate students interested in pursuing graduate school, the researchers will explore whether the research extends to high school students considering computing careers. Guided by the ‘possible selves’ and ‘social cognitive career theory (SCCT)’ frameworks, researchers will examine students’ perceptions of computing and computing careers before and after each career exploration fair, noting the effect and impact of questions and answers (Q&A), storytelling, and culturally relevant storytelling. The ECAs will represent minority individuals in authentic computing professions. The specific research questions are: 1) In what ways do students’ career interests and perceptions change following virtual career exploration fairs using ECAs? 2) How do culturally relevant ECAs differ based on student perceptions and identities? and 3) What roles do gender, race, ethnicity, grade level, and location (rural/urban) play in students’ career identities? Survey data will be analyzed to determine the relative impact of the virtual career exploration fair on student self-efficacy, interest in computer science careers, and predictive factors of the SCCT. The project presents a potentially sustainable solution for motivating urban and rural high-need school districts to explore computing careers. Data collected on student attitudes, interests, and self-efficacy will help guide improvements to the ECAs and ensure they are broadly applicable for future uses.
Funder Acknowledgement(s): National Science Foundation
Faculty Advisor: None Listed,