Document Type

Article

Publication Title

Trends in Higher Education

Abstract

This article examines the Integrevise platform through a repeated cross-sectional, multicycle pilot case study of viva-based verification in AI-mediated assessment environments. Integrevise 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 Integrevise as a process-rich assessment intervention, but not broad claims of efficacy or scalability without larger, more systematic validation.

Research Highlights

  • The Problem: Generative AI has destabilized traditional academic assessment by making fluent, knowledge-like production fast and inexpensive, which weakens the chain of inference between a submitted written artifact and genuine student competence.

  • The Method: The researchers conducted a repeated cross-sectional, multi-cycle pilot case study across Fall 2025 and Spring 2026, pairing student-submitted written artifacts with a short adaptive oral viva via the Integrevise platform.

  • Quantitative Finding: In Spring 2026, 52 vivas were completed; 22 sessions produced positive student feedback; 10 sessions produced negative student feedback; 20 sessions generated no feedback record; formal survey data from 7 respondents showed that 14.3% agreed the oral assessment helped them think more deeply, whereas 57.1% disagreed or strongly disagreed.

  • Qualitative Finding: Positive student comments emphasized deeper reflection and contextual questioning beyond the written text; negative feedback clustered around technical issues like voice lag, application freezing, and general AI resistance; tutor observations indicated the process successfully surfaced hidden comprehension gaps, incorrect material application, or student disengagement.

Publication Date

7-2026

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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