Structured human resource development with AI support is associated with higher expert rated recruitment task quality among education graduates

Graduate employability programmes are usually evaluated with self-report measures. We compared a structured human resource development programme supported by generative AI with career guidance matched on topics, duration and facilitator contact. Twelve intact cohorts of graduates seeking education-sector posts in Guangdong, China (N = 186), were allocated as whole units, six per condition, crossed with institution, facilitator and schedule.

Blinded experts gave a global rating (0–100) of recruitment-task materials produced on site, under invigilation and without AI, before and after the programme. Ratings were made without a pre-specified rubric, which limits their interpretation. Among 168 participants with post-test data (overall attrition 9.7%), the adjusted difference favoured the AI-supported programme by 5.38 points (95% CI 2.76 to 8.01; d = 0.60) and was stable across eight specifications.

Four new self-report scales showed smaller differences (d = 0.12 to 0.29), none significant after Holm correction; each scale could detect only differences of about d = 0.4. The effect on expert ratings exceeded the mean effect on self-report by 0.37 standard deviations (95% CI 0.10 to 0.63). Component analyses were exploratory.

The design cannot separate the contribution of AI from structured practice and feedback. The authors thank the participating institutions and graduates, and the expert raters who assessed de-identified performance materials. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Azman Hashim International Business School (AHIBS), Universiti Teknologi Malaysia, 54100, Kuala Lumpur, Malaysia South China Normal University, Guangzhou, Guangdong, China The authors declare no competing interests. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Below is the link to the electronic supplementary material.

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