BRIDGING THE EMPLOYABILITY THRESHOLD BEHAVIOUR GAP: A MIXED-METHODS PILOT EVALUATION OF LAUNCH-SESSION RECEPTION AND EARLY PLATFORM USABILITY OF AN AI-ENABLED PRACTICE ARTEFACT

This pilot study evaluates attendee reception of the launch session and early user experience of the associated app/website platform for Human Assetize, an AI-enabled Employability Threshold Behaviour (ETB) practice artefact. As an early-stage, exploratory evaluation, the study is deliberately scoped to the first cohort of respondents available immediately post-launch (session survey n = 41; platform survey n = 27); findings should be read as preliminary indicators to be confirmed with a larger follow-up sample, not as final, generalisable conclusions. Using two independently collected feedback instruments, the study applies descriptive statistics, inferential testing (Pearson correlation, independent-samples t-test), and inductive thematic coding of open-ended responses to characterise attendee and user sentiment. The launch session was well received (M = 3.88/5, SD = 0.87; 97.6% found the core message clear). Platform usability ratings were similarly positive (navigation ease M = 3.33/5; visual design M = 3.96/5), and navigation ease and visual design were both strongly and significantly correlated with recommendation likelihood (r = 0.69 and r = 0.70 respectively, p < 0.001). However, the platform's Net Promoter Score was −7.4 (25.9% promoters, 33.3% detractors), and 48.1% of users reported encountering a bug or error, most frequently freezing or restart failures within the interview-simulation module. Thematic analysis converged across both feedback channels on a shared technical-defect pattern — session timeouts, repeated/non-advancing questions, and network instability — providing methodological triangulation between independently collected qualitative sources. The paper concludes with prioritised, evidence-based recommendations for technical remediation and platform refinement.