Work

BoostedCats at BEA 2026 Shared Task 1: What Makes a Word Hard to Learn? Modeling L1 Influence on English Vocabulary Difficulty

Year: 2026

Type: conference-paper

Abstract: What makes a word difficult to learn, and how does the difficulty depend on the learner's native language?We computationally model vocabulary difficulty for English learners whose first language is Spanish, German, or Chinese with gradient-boosted models trained on features related to a word's familiarity (e.g., frequency), meaning, surface form, and crosslinguistic transfer.Using Shapley values, we determine the importance of each feature group.Word familiarity is the dominant feature group shared by all three languages.However, predictions for Spanish-and German-speaking learners rely additionally on orthographic transfer.This transfer mechanism is unavailable to Chinese learners, whose difficulty is shaped by a combination of familiarity and surface features alone.Our models provide interpretable, L1tailored difficulty estimates that can be used to design vocabulary curricula. Code repository and interactive demo

Source: Workshop on Innovative Use of NLP for Building Educational Applications

DOI: 10.18653/v1/2026.bea-1.74

Authors: Jonas Mayer Martins, Zhuojing Huang, Aaricia Herygers, Lisa Beinborn

Institution: University of Göttingen

Language: English

Topic: Second Language Acquisition and Learning

Subfield: Developmental and Educational Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Funder: Nederlandse Organisatie voor Wetenschappelijk Onderzoek