Department of Information Systems and Operations Management University of Florida, Warrington College of Business
Gainesville, FL, USA.
International Journal of Science and Research Archive, 2025, 17(03), 793-796
Article DOI: 10.30574/ijsra.2025.17.3.3325
Received on 15 November 2025; revised on 20 December 2025; accepted on 23 December 2025
Clevika is an AI-driven tutoring marketplace that pairs students with tutors using a scientifically grounded, multi-dimensional compatibility engine built on four dimensions repeatedly proven to predict educational success: personality traits measured by the Big Five model, religious and cultural worldview, dominant teaching/learning style assessed through the VARK framework, and gender identity or preference. Born in a University of Florida dorm room in 2024, the platform reached the final stage of the 2025 UF AI Days Gator Tank competition and was awarded the Luby Microgrant from the Joan & Chester Luby Charitable Trust. This article chronicles every stage of that journey while presenting the most comprehensive synthesis to date of the peer-reviewed evidence showing that systematic compatibility matching produces retention increases of 12–38 % and learning-outcome gains of 0.18–0.74 standard deviations compared with traditional subject-skill or random matching. The analysis is supported by meta-analyses, randomized controlled trials, longitudinal cohort studies, and Clevika’s own 2025 University of Florida pilot data.
Artificial intelligence in education; Personalized tutoring; Personality congruence; Religious compatibility; VARK learning styles; Gender matching; Student retention; Academic achievement; University of Florida; Gator Tank; Luby Microgrant; Educational psychology
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Tetiana Cheberko. Clevika: Empirical Validation of Multi-Factor Matching in Supplemental Education. International Journal of Science and Research Archive, 2025, 17(03), 793-796. Article DOI: https://doi.org/10.30574/ijsra.2025.17.3.3325.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0







