DOI: 10.3390/educsci16081229 ISSN: 2227-7102

Exploratory NLP Analysis of Ideathon Presentation Content: Cambodia (2023–2025) and Thailand (2025)

Toshiharu Igarashi, Shinya Takei

Ideathons and pitch competitions have expanded rapidly as experiential learning devices, but the textual artefacts they produce—presentation slides—remain under-examined. This study applies interpretable computational text analysis to 104 ideathon decks (1289 content slides) from four cohorts: Cambodia 2023, 2024, 2025 and Thailand 2025. Measures include lexical frequency, TF-IDF, lexicon-based sentiment, a ten-component pitch-completeness proxy, numerical density, and Jaccard similarity. Because sector designation was absent in Cambodia 2023 and present from 2024 onward, the longitudinal Cambodian data support an observational cohort comparison with an institutional change between cohorts; year effects, programme evolution, and sector designation cannot be separated. The Cambodia 2025 vs. Thailand 2025 contrast is a single-year cross-country comparison, not a longitudinal one. Between Cambodia 2023 and 2024, presentations show large Cohen’s d differences with 95% bootstrap confidence intervals (CIs) in total words, unique words, slide count, pitch completeness, and market-related vocabulary, alongside a small decline in type–token ratio. At fixed sector composition, Cambodia 2025 and Thailand 2025 differ sharply in surface vocabulary (top-50 Jaccard = 0.176): Cambodia leans toward agriculture, rural markets, and community development, while Thailand leans toward AI, learning, and cassava-centric agronomy. AI use was not directly measured, so all claims about generative AI are hypothesis-generating; the drop in within-cohort pairwise Jaccard from 2024 to 2025 (0.061 → 0.041) is consistent with—but does not establish—an augmentative rather than homogenising effect of AI assistance. Findings are reported as descriptive associations and interpreted through the lens of constraint-based creativity and institutional theory. We discuss implications for curriculum designers who wish to balance structural templates with exercises that promote diverse problem framings.

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