Comparing Concepts for Embedding Second-Language Vocabulary Acquisition into Everyday Smartphone Interactions

TL;DR

This study compares three mobile language learning apps with different integration levels into daily smartphone use, revealing that seamless embedding increases engagement but varies in user preference and experience.

Contribution

It introduces and evaluates novel embedding concepts for vocabulary learning integrated into everyday smartphone interactions, a first in direct comparison.

Findings

Embedding learning into daily interactions increases answer frequency.

User preferences vary for different embedding methods.

Trade-offs exist between content exposure and disturbance.

Abstract

We present a three-week within-subject field study comparing three mobile language learning (MLL) applications with varying levels of integration into everyday smartphone interactions: We designed a novel (1) UnlockApp that presents a vocabulary task with each authentication event, nudging users towards short frequent learning sessions. We compare it with a (2) NotificationApp that displays vocabulary tasks in a push notification in the status bar, which is always visible but learning needs to be user-initiated, and a (3) StandardApp that requires users to start in-app learning actively. Our study is the first to directly compare these embedding concepts for MLL, showing that integrating vocabulary learning into everyday smartphone interactions via UnlockApp and NotificationApp increases the number of answers. However, users show individual subjective preferences. Based on our results, we discuss the trade-off between higher content exposure and disturbance, and the related challenges and opportunities of embedding learning seamlessly into everyday mobile interactions.