{"title":"基于专家共识的增强现实应用MetAR框架的设计与开发","authors":"Siet Fah Lim, Yusri Kamin","doi":"10.1504/ijlt.2023.132750","DOIUrl":null,"url":null,"abstract":"This study aims to design and develop a framework for designing a metacognitive-supported augmented reality application for teaching and learning basic pneumatic systems. This multi-method study with the fuzzy delphi method (FDM) and interpretive structural modelling (ISM) approach involved 12 experts in multidisciplinary fields. The data was collected using seven Likert-type scale questionnaires. The design phase of the framework using the FDM found that the expert consensus for all principal components and the elements is greater than 75% with the threshold value, d ≤ 0.2. In contrast, the development phase of the framework was performed based on experts' voting using the ISM approach. The Concept Star software was used to develop the sequence of the elements based on their priority from every principal component to produce the MetAR design framework.","PeriodicalId":43818,"journal":{"name":"International Journal of Learning Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.4000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The design and development of the MetAR framework for designing an augmented reality application based on experts' consensus\",\"authors\":\"Siet Fah Lim, Yusri Kamin\",\"doi\":\"10.1504/ijlt.2023.132750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to design and develop a framework for designing a metacognitive-supported augmented reality application for teaching and learning basic pneumatic systems. This multi-method study with the fuzzy delphi method (FDM) and interpretive structural modelling (ISM) approach involved 12 experts in multidisciplinary fields. The data was collected using seven Likert-type scale questionnaires. The design phase of the framework using the FDM found that the expert consensus for all principal components and the elements is greater than 75% with the threshold value, d ≤ 0.2. In contrast, the development phase of the framework was performed based on experts' voting using the ISM approach. The Concept Star software was used to develop the sequence of the elements based on their priority from every principal component to produce the MetAR design framework.\",\"PeriodicalId\":43818,\"journal\":{\"name\":\"International Journal of Learning Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Learning Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijlt.2023.132750\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Learning Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijlt.2023.132750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
The design and development of the MetAR framework for designing an augmented reality application based on experts' consensus
This study aims to design and develop a framework for designing a metacognitive-supported augmented reality application for teaching and learning basic pneumatic systems. This multi-method study with the fuzzy delphi method (FDM) and interpretive structural modelling (ISM) approach involved 12 experts in multidisciplinary fields. The data was collected using seven Likert-type scale questionnaires. The design phase of the framework using the FDM found that the expert consensus for all principal components and the elements is greater than 75% with the threshold value, d ≤ 0.2. In contrast, the development phase of the framework was performed based on experts' voting using the ISM approach. The Concept Star software was used to develop the sequence of the elements based on their priority from every principal component to produce the MetAR design framework.
期刊介绍:
IJLT is an international, refereed, scholarly journal providing an interdisciplinary forum for the presentation and discussion of important ideas, concepts, and exemplars that can deeply influence the role of learning technologies in learning and instruction. This unique and dynamic journal focuses on the epistemological thrust of learning vis-à-vis instruction and the technologies and tools that support the process. IJLT publishes papers related to theoretical foundations, design and implementation, and effectiveness and impact issues related to learning technologies. Topics covered include: -Communities of learners (practice), computer-mediated communication -[Social] constructivism, computer-supported collaborative learning -Cognitive tools, intelligent agents, semantic web -Distributed/intelligent learning/tutoring, multimedia/interactive learning environments -Virtual reality environments, human-computer interface issues -Learning objects for personalised learning, building learning communities -Technology-facilitated learning in complex domains -Learning technology systems'' evaluation, technological standardisation -Simulation-supported learning/instruction -Learning technology in education and commerce -Disciplinary-related inquiry, e.g., learning technologies for science inquiry -MOOCs, social media and cloud computing in e-learning -Data analytics and big data in education -E-learning evaluation and content; e-portfolios -Smart education; internet of things/technology adoption and diffusion for learning