iChat-Job: Designing Self-Determination Theory-Grounded System with Digital Humans for Increasing University Graduates’ Employability

Abstract

University students often struggle to craft effective
resumes, build portfolios, identify suitable career
directions,
prepare for interviews and find a satisfactory job. While
commercial AI job tools provide resume polishing and job
matching, they are typically optimised for short-term
conversion rather than education-oriented development. This
paper
presents the design and system of iChat-Job, an AI-powered
career development platform grounded in self-determination
theory (SDT). The system supports (1) resume and portfolio
development through resume upload, curated templates, and
AI-assisted content refinement; (2) career pathway
recommendations aligned with labour-market demand using
real-time
search over an online job database; and (3) digital-human
interview simulation using speech-to-text interaction with
formative feedback. This system aligns with SDT’s three
sub-dimensions (i.e., autonomy, competence, relatedness), a
privacy-preserving local analysis pipeline, and a
lightweight “growth” mechanism for goal setting and
progress tracking
to make SDT visible in the system. This paper provides
insights for a theory-driven system for scalable
employability
training in higher education and outlines planned formative
evaluation.