AI-supported analysis of Japanese language learning : motivation and gamification

Dangubić, Sara (author)

This study examines how gamification elements in Japanese language learning apps and platforms align with motivational theories. Building on established motivational models, it proposes an analytical framework that maps common gamification features (e.g., progress tracking, rewards, and customization) to motivational factors such as competence, achievement, and self-efficacy. The framework is applied to two widely used mobile apps (LingoDeer and Renshuu) and two online platforms (WaniKani and MaruMori). In addition, a large language model is used as an AI-assisted evaluator within the proposed framework to independently assess and rank the selected apps and platforms, with its output compared to the researcher’s analysis as a validation step. The findings suggest that effective motivation depends not on isolated reward mechanisms but on a balanced integration of gamification elements.

• Language: English
• Keywords: Japanese language learning, gamification, motivational theories, AI-supported analysis
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FF - Faculty of Arts
• Publication status: Published
• Publication version: Version of Record
• Year: 2026
• Number of pages: Str. 137-164
• Numbering: Vol. 16, no. 2
• PID: 20.500.12556/RUL-190492
• ISSN on article: 2232-3317
• DOI: 10.4312/ala.16.2.137-164
• Publication date in RUL: 04.11.2026

Record is a part of a journal

• Title: Acta linguistica asiatica
• Publisher: Založba Univerze v Ljubljani
• ISSN: 2232-3317
• COBISS.SI-ID: 255902464

Licences

• License: CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
• Link: http://creativecommons.org/licenses/by-sa/4.0/
• Description: This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.

Secondary language

• Language: Slovenian
• Title: Analiza učenja japonščine, podprta z umetno inteligenco : motivacija in igrifikacija

Abstract

Raziskava preučuje, kako se elementi igrifikacije v aplikacijah in spletnih platformah za učenje japonščine ujemajo z motivacijskimi teorijami. Na podlagi uveljavljenih motivacijskih modelov predlaga analitični okvir, ki elemente igrifikacije (npr. spremljanje napredka, nagrajevanje in prilagajanje) povezuje z dejavniki, kot so kompetentnost, dosežek in samoučinkovitost. Okvir je uporabljen za analizo dveh mobilnih aplikacij (LingoDeer in Renshuu) ter dveh spletnih platform (WaniKani in MaruMori). Velik jezikovni model je kot z umetno inteligenco podprt ocenjevalec uporabljen za neodvisno vrednotenje in razvrstitev izbranih aplikacij in platform, njegove ugotovitve pa so primerjane z analizo raziskovalke. Rezultati kažejo, da učinkovita motivacija ne temelji na posameznih mehanizmih nagrajevanja, temveč na uravnoteženi integraciji različnih elementov igrifikacije.

• Keywords: učenje japonščine, igrifikacija, motivacijske teorije, z umetno inteligenco podprta analiza