Evaluation of the Effectiveness and User Feedback of the AR Vocabulary Card Application for English Vocabulary Learning

This is the authors' abstract. We don't add key points for this paper.

The aim of this study is to develop an application utilizing Augmented Reality (AR) technology to enhance English language learning.Employing the Quality Function Deployment (QFD) method and instructional steps involving Concept Mapping (CM), we identified important design elements and learning content.Firstly, user requirements concerning interface style, CM application, and AR interface were explored through brainstorming sessions.Subsequently, employing the Point of View method, we established vital user requirements, and the How Might We method was used to transform them into design elements.The most significant design elements were selected through an evaluation of a relationship matrix.Based on the most important design elements and instructional steps involving CM, the primary design direction was determined, involving the amalgamation of physical word cards and AR visual effects in the form of AR Vocabulary Card.To assess the application's effectiveness, 9 users aged between 20 and 31, with over five years of English learning experience, participated in 10-15 minutes of learning.Their feedback was collected through vocabulary assessment and semi-structured interviews.Results indicated that users held a favorable impression of the vocabulary learned through AR Vocabulary Card.User recommendations mainly centered around the AR interface and its features, as well as CM learning.In summary, this study has created the AR Vocabulary Card, offering English learners an innovative learning tool.It also underscores the promising role of AR in design education, personalized learning, and user engagement, shaping more interactive and effective learning experiences in the future.Subsequent research can focus on enhancing features, integrating it into authentic learning contexts, and broadening the sample size for more comprehensive user feedback.