2026 ASEE Annual Conference & Exposition

This full research paper describes an empirical study investigating the efficacy of an AI-driven career feedback tool in enhancing students’ self-regulated learning competencies related to professional development. Engineering students often face challenges in translating academic experiences into career pathways aligned with industry expectations, compounded by limited access to personalized career advising. Grounded in Zimmerman’s Self-Regulated Learning (SRL) framework, an AI-driven career feedback tool is presented that provides resume analysis, job match assessment, and personalized career roadmaps with timeline-aligned development plans. This mixed-methods study involved 24 students from computing and engineering programs at a large Midwestern university. Students completed a baseline survey assessing goal clarity, gap awareness, strategic planning, and self-efficacy, then interacted with the AI tool. Post-intervention surveys evaluated tool quality and changes in metacognitive awareness, planning intentions, and professional development ownership, supplemented by qualitative reflections. Results demonstrated substantial improvements in metacognitive awareness, with 91.7% reporting increased understanding of employer competency expectations and 95.8% reporting clearer career trajectories. Students rated the tool highly across all quality dimensions (M = 4.25-4.46), with particularly strong actionability ratings. Qualitative analysis revealed students valued the tool’s specificity, personalization, and accessibility while viewing it as complementary to human advising. Students committed to diverse developmental actions including certifications, coursework, projects, and networking. Findings suggest AI-based career feedback systems can operationalize SRL principles at scale, serving as metacognitive scaffolds supporting goal setting, gap identification, and strategic planning. Implications include curricular integration, tiered advising models combining AI and human expertise, and democratized access to personalized career guidance for students lacking professional networks.