Curiosity Over Hype: Modeling Motivation Language to Understand Early Outcomes in a Selective Quantum Track

Saldana D.A.C.V.; Cueva F.H. · Proceedings of the 2025 IEEE 5th International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2025 (2025) · DOI: 10.1109/icalter69698.2025.11355072

Resumen

We study whether latent motivation signals in short Spanish admission responses predict engagement and performance in an early quantum computing pathway run by QuantumHub Perú. We analyze N = 241 applicants' open responses and link them to outcomes from two selective modules: Module 1 (secondary; mathematics and computing foundations; n=23) and Module 2 (secondary + early undergraduate; quantum fundamentals; n=36, including M1 continuers). To ensure baseline comparability, the M2 university entrance exam matched the difficulty of the M1 final. Final grades followed the program's official cohort-specific weightings (attendance/assignments/exam), which we retain to preserve ecological validity. Methodologically, we model text with Latent Dirichlet Allocation (LDA, k=8) and, for robustness, with sentence embeddings from a small multilingual language model, EmbeddingGemma-300M, projected via UMAP and clustered with HDBSCAN. This combination leverages the transparency of bag-of-words topics and the semantic richness of small language model (SLM) embeddings. Descriptively, curiosity/learning topics show higher grades and attendance than technology/career-oriented topics; inferential tests are underpowered (e.g., linear R2 0.03; logistic pseudo.R2 0.04) so effect-size estimates should be viewed as preliminary rather than confirmatory. Embedding-based clustering yields seven clusters with 1 1. 2 % noise and modest agreement with LDA (ARI =0.068; NMI =0.163). Results suggest that brief motivation responses encode promising signals that could support early mentoring in rigorous STEM pipelines, while highlighting the need for larger, pre-registered studies.

Instituciones: Universidad Peruana de Ciencias Aplicadas