| Summary: | 碩士 === 國立臺北護理健康大學 === 資訊管理研究所 === 103 === Technological advancement has brought about diversified information and multi-media development. It gives rise to applications combining technology and education that provide today’s learners more ways to learn. Among emerging technologies, augmented reality (AR) can be an interactive tool for learning, which integrates real world with virtual 3D objects. AR provides real-time two-way learning and fun, thus it is widely used in many teaching fields. Context awareness is an important element for making smart devices. By combining AR and context awareness, different learning contents can be presented based on learners’ learning behaviors.
In this study, the Cognitive Theory of Multimedia Learning (CTML) proposed by Mayer was employed to design interface for the teaching system. Using the Suzuki method as the teaching concept, teaching material design and system development were carried out to achieve experience-based music learning, arouse leaners’ interest in music theory, and improve learning outcomes.
This system combines context awareness and AR technology, and learning behaviors are recorded in the database. As for the teaching mode, music theory related knowledge is presented through AR technology. Under the test mode, data obtained from context awareness is adopted to reach the smart question-setting goal. In addition, it deploys listening questions in the test mode to examine user’s learning outcomes. In the study, Lua Script was the development language for generating AR using D’fusion software. JavaScript codes were embedded in HTML5 webpages for streaming data into the server side. The jQuery functions, combined with AJAX technology, were then applied to store data in the backend database through the PHP program.
After completing system implementation, 34 respondents were recruited during the assessment stage to undergo a satisfaction survey. Using the 5-point Likert scale, the mean satisfaction of the learning mode is 3.89 points, the test mode is 3.94 points, and the overall system is 4.1 points, which all exceed the medium score of 3 points. This means the system is affirmed. The mean score of overall satisfaction is 7.38 (out of 10 points), which is well above medium score of 5 points. In order to gain an insight into the effectiveness and perception of smart question setting, this study divided the respondents into two groups: A and B. For Group A, “set more questions for units which were learned longer” is the strategic principle; and the contrary holds true for Group B. From the Spearman correlation coefficient analysis, it has showed that respondents’ knowledge levels can be better detected using the strategy for group B. In Group B, “knowledge level about music theory” and “test score” showed a highly positive correlation (r=.662**,p=004) and reached the significance level. This means the scores obtained using the Group B question setting method are more in line with learners’ knowledge level about music theory, and thus it is considered a policy worth continuing.
From the research results, it shows that AR can be employed to build teaching and evaluation systems with musical outputs. In addition, evaluation can be done more thoroughly through individualized question setting using context awareness and through listening question setting in the test mode. Thus, context awareness and musical outputs benefit the AR teaching system.
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