Prioritizing User Preferences in Language Learning Applications: A Kano Model Approach to Feature Satisfaction and Prioritization

초록

This research investigates user preferences in language-learning applications by applying the Kano Model to categorize features based on their impact on satisfaction. A survey of 100 participants, selected through purposive sampling, revealed that interactive lessons (mean = 4.62) and multimedia content (mean = 4.54) are the most valued features, while communication with native speakers received mixed feedback (mean = 3.02). Statistical analysis, including mean scores and standard deviations, highlighted the importance of personalization and interactivity in enhancing user engagement. The study addresses the research gap in feature prioritization by providing actionable insights for developers to improve app design and user satisfaction. Key findings indicate that features such as personalized study plans (mean = 4.42) and vocabulary sections (mean = 4.22) are highly valued, while gamification elements (mean = 3.84) and offline mode (mean = 3.42) require careful integration to meet diverse user needs. This research demonstrates the utility of the Kano Model in identifying user priorities and offers a framework for future studies on feature optimization in digital education.

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