Building AI Learner Identity Across Career Aspirations: An Expectancy-Value Perspective

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  In Roundtable Session: Generative AI, Identity, and Cognitive Partnership

Abstract

As artificial intelligence (AI) shapes diverse fields, fostering students’ AI learner identity has become increasingly critical. This study examines how secondary school students develop AI learner identity through the Exploring AI in English Language Arts with StoryQ curriculum. Drawing on expectancy-value theory, we analyzed pre- and post-surveys from 470 students. Results revealed significant gains in expectancy and value beliefs after the curriculum. Students aspiring to AI-related careers demonstrated greater growth in AI learner identity. Value beliefs significantly predicted post-intervention identity, especially for those with low initial AI aspirations, whereas expectancy did not predict identity development. These findings highlight value construction as a key pathway to identity development and underscore the importance of aligning AI learning with diverse career goals.

Authors

• Fan Xu, N/A

• Shiyan Jiang, North Carolina State University

• Suzhen Duan, Towson University

• Liu Dong, Purdue University

• Chi-Jia Hsieh, Purdue University

• Dan Sun, Hangzhou Normal University