L2 grit and age as predictors of attrition in mobile-assisted language learning

Author: Ekaterina Sudina, Yasser Teimouri, Luke Plonsky · Type: academic · Status: draft · URL: https://www.sciencedirect.com/science/article/pii/S1041608025000809

Licence: Learning and Individual Differences (Elsevier), 2025, DOI 10.1016/j.lindif.2025.102704; paywalled; abstract quotable

Summary

A rare longitudinal attrition study in mobile-assisted language learning: 601 beginners learning Spanish or French on Duolingo were tracked over six months, with logistic regression testing age, target language, L2 motivation, both L2 grit facets, self-rated proficiency, and C-test scores as predictors of quitting. The best-fitting model retained only L2 grit (perseverance of effort) and age: older and more persevering learners were less likely to abandon the app. The authors note attrition had been largely unstudied in the MALL literature. For Immersive this identifies who retains (older, gritty adults) and implies onboarding should scaffold persistence rather than assume it.

Insights

• In a 6-month study of 601 app-based beginners, perseverance of effort (L2 grit) and older age were the only meaningful predictors of not dropping out. (medium, draft) dropout motivation adult learners

  Paraphrase of abstract: a logistic regression on Duolingo attrition found the best-fitting model included L2 grit perseverance of effort and age as meaningful predictors. — Abstract

• Proficiency and general motivation measures did not predict app abandonment once grit and age were accounted for, suggesting retention design should target habit and persistence support rather than skill level. (medium, draft) dropout motivation product design

  Paraphrase: predictors tested included L2 motivation, self-rated proficiency and C-test scores, but these were not retained in the best-fitting attrition model. — Abstract

• Attrition is a research blind spot in mobile-assisted language learning, so commercial retention data (like Immersive’s own cohorts) can genuinely add knowledge and credibility. (low, draft) dropout retention research gap

  Paraphrase: the authors highlight a lack of research on attrition in the mobile-assisted language learning literature. — Introduction / framing