Abstract

This article examines the IntegreviseTM platform through a repeated cross-sectional, multi-cycle pilot case study of viva-based verification in AI-mediated assessment environments. IntegreviseTM pairs a submitted written artifact with a short adaptive viva in which students explain their work, reasoning, and application in their own words. Rather than functioning as an AI detector or automated grading system, the platform operates as a diagnostic assessment layer intended to surface comprehension, authorship confidence, and disengagement risk before final grades become the only available signal. The pilot was conducted across Fall 2025 and Spring 2026 at a private liberal arts college in the Midwest; these phases involved different student groups and are therefore treated as iterative implementation cycles rather than a longitudinal cohort. Results should be interpreted as preliminary pilot evidence. In Spring 2026, 52 vivas were completed, but formal student survey data were limited to seven respondents and showed mixed perceptions: only 14.3% agreed that the oral assessment helped them think more deeply about the assignment, whereas 57.1% disagreed or strongly disagreed. Platform feedback was also incomplete, with 20 of 52 vivas (38.5%) producing no student feedback record. Qualitative feedback, tutor observations, and implementation notes nevertheless suggest that viva-based verification may help identify some comprehension gaps and implementation barriers that written artifacts alone may not reveal. The findings, therefore, support continued investigation of IntegreviseTM as a process-rich assessment intervention, but not broad claims of efficacy or scalability without larger, more systematic validation.

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