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UnlockLearning : Investigating the Integration of Vocabulary Learning Tasks into the Smartphone Authentication Process

Title data

Schneegass, Christina ; Sigethy, Sophia ; Mitrevska, Teodora ; Eiband, Malin ; Buschek, Daniel:
UnlockLearning : Investigating the Integration of Vocabulary Learning Tasks into the Smartphone Authentication Process.
In: i-com : Journal of Interactive Media. Vol. 21 (2022) Issue 1 . - pp. 157-174.
ISSN 1618-162X
DOI: https://doi.org/10.1515/icom-2021-0037

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
AI Tools - Continuous Interaction with Computational Intelligence ToolsNo information

Abstract in another language

Frequent repetition of vocabulary is essential for effective language learning. To increase exposure to learning content, this work explores the integration of vocabulary tasks into the smartphone authentication process. We present the design and initial user experience evaluation of twelve prototypes, which explored three learning tasks and four common authentication types. In a three-week within-subject field study, we compared the most promising concept as mobile language learning (MLL) applications to two baselines: We designed a novel (1) UnlockApp that presents a vocabulary task with each authentication event, nudging users towards short frequent learning session. 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.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 15 Jun 2022 08:06
Last Modified: 15 Jun 2022 08:06
URI: https://eref.uni-bayreuth.de/id/eprint/70108