Authors:
Sigrid L. Klinger
and
Sven Strickroth
Affiliation:
LMU Munich, Munich, Germany
Keyword(s):
Etymology-Based Learning, Self-Regulated Learning, Graph-Based Interfaces, Kanji Learning.
Abstract:
Learning Kanji is a complex and critical component of Japanese language acquisition, requiring learners to understand its semantics, morphology, and phonology. Traditional rote memorization methods often overlook Kanji’s etymological and structural nuances, limiting their effectiveness. This paper presents an etymology-driven, adaptive Kanji learning tool designed to visualize Kanji relationships, reduce cognitive load, and enhance learner engagement. The tool features interactive graph visualizations, personalized learning recommendations, and integration with Anki flashcards for explorative, self-regulated learning (SRL). The tool was evaluated for its usability and adaptivity in a field study with 19 participants. Overall, the tool’s usability was well-received, with the detailed Kanji graph and Anki integration being commended for their clarity and ease of use. Personalized learning recommendations were particularly valued for providing adaptive and targeted learning paths. Howev
er, the macro-level perspective provided by the overall graph was found overwhelming by some users. Results also indicate that learning goal motivation strongly influenced engagement, with motivated users benefiting more from the tool’s adaptive features. Key contributions include methods for visualizing interconnected knowledge, recommendations for personalized learning paths, and supporting tools for encoding and retrieval stages.
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