Toc‐Tum mini‐games: An educational game accessible for deaf culture based on virtual reality

Chaves, Edilson M.; Braga, Paulo; Montenegro, Yuri Fontenelle Lima; Rodrigues, Vitória B.; Munguba, Marilene Calderaro; Albuquerque, Victor Hugo C. de

doi:10.1111/exsy.12470

Cited by 11 publications

(8 citation statements)

References 23 publications

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“…The Objects of the reviewed studies were to enhance learners' (a) particular skills, including motor skills (e.g., Contreras et al, 2019 ; Lau et al, 2020 ), cognitive skills (e.g., Ojeda-Castelo et al, 2018 ; Avila-Pesantez et al, 2019 ), engagement and attention (e.g., Jung and Sainato, 2015 ); visual skills (e.g., RuŽičková and Hordějčuková, 2015 ) and listening skills (e.g., Hatzigiannakoglou and Okalidou, 2019 ); (b) social interaction (e.g., Bernardini et al, 2014 ; Al Mahmud and Soysa, 2020 ); and (c) learning outcomes, which include science, technology, engineering and mathematics (STEM, e.g., Bakker et al, 2016 ), reading (e.g., Görgen et al, 2020 ), music (e.g., Chaves et al, 2021 ), and languages (e.g., Pontes et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

“…Both objective (e.g., Sitra et al, 2017 ) and subjective measures (e.g., Al Mahmud and Soysa, 2020 ) were used when evaluating learners' interest (e.g., Sari et al, 2019 ), engagement (e.g., Cassar and Jang, 2010 ), psychomotor and cognitive development (e.g., Karal et al, 2010 ), and language development (e.g., Malekian and Askari, 2013 ). The usability (e.g., Ghanouni et al, 2020 ), effectiveness (e.g., Goker et al, 2016 ), and accessibility (e.g., Chaves et al, 2021 ) of game-based learning were also examined using selected measuring scales.…”

Section: Resultsmentioning

confidence: 99%

“…Even though educational games in the 96 studies were designed for learners with disabilities, a few studies invited learners to join the design team (van der Stege et al, 2010 ; Othman et al, n.d. ) or test the games (Chaves et al, 2021 ). Only 14 studies involved parents' participation, of which 8 gave parents an active role while 6 studies had parents merely share their information and excluded them in the treatment process.…”

Section: Resultsmentioning

confidence: 99%

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Game-Based Learning for Learners With Disabilities—What Is Next? A Systematic Literature Review From the Activity Theory Perspective

et al. 2022

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The design, implementation, and outcome of game-based learning for learners with disabilities have not been sufficiently examined systematically. Particularly, learner-based and contextual factors, as well as the essential roles played by various stakeholders, have not been addressed when game-based learning applications are used in special education. Therefore, a systematic literature review using the Activity Theory (AT) was conducted to analyse studies about game-based learning for learners with disabilities. Content analysis of 96 studies reported relevant information with respect to each activity component—(a) subject (learners with disabilities), (b) technology (game-based learning applications), (c) object (target skills or behaviours), (d) rules (implementation procedure and performance measures), (e) community (learners with disabilities, special education professionals, and parents), (f) division of labour (among learners, professionals, and parents) and (g) outcome (performance of target skills or behaviours). Furthermore, this study identified existing gaps from the reviewed studies, including occasional lack of parental engagement, difficulty of standardising performance measures due to the heterogeneity of learner profiles and contradictions (e.g., opposing views among experts on the role of educational games in social interactions). Finally, recommendations were made under each activity component. The study concluded that both general and domain-specific guidelines should be created for each disability category proposed in this review to assist practitioners who wish to use game-based learning with learners with disabilities.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Game-Based Learning for Learners With Disabilities—What Is Next? A Systematic Literature Review From the Activity Theory Perspective

et al. 2022

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“…Joint (2005) argued for focusing on customer service improvements rather than technological solutions. Current work in the field of XR accessibility has focused on developer toolkits and software plugins (e.g., Accessibility Toolkit For Unity , 2021; UI Accessibility Plugin [UAP] , 2021; WalkinVR , n.d.; Zhao et al, 2019), and on finding ways of using XR for therapeutic or pedagogical benefits (e.g., Chaves et al, 2021; Garzotto et al, 2018, 2017; Kellems et al, 2021; McMahon et al, 2020; Yiannoutsou et al, 2021).…”

Section: Literature Review and Backgroundmentioning

confidence: 99%

XR Accessibility Initiatives in Academic Libraries

Lischer-Katz

Clark

2021

Proceedings of the Association for Information Science and Tech

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Virtual reality and other extended reality (XR) technologies are being integrated into academic libraries to support research and teaching in innovative ways; however, new technologies are often adopted without considering disabled users. XR accessibility depends on establishing appropriate policies and best practices. This paper examines the current state of XR accessibility initiatives in academic libraries by reporting findings from a survey sent to the academic library community from February to May 2021.

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“…The second paper by Chaves et al (2019) has developed a novel medical expert system based on virtual reality, called Toc-Tum mini-games, applying basic concepts of music in an accessible way to the deaf culture. The intelligent proposed method is validated in two different tests: (a) with the target audience to evaluate the interest in the game and (b) with professionals knowledgeable in the field of music or who have had contact with the deaf, evaluate the impact of the game teaching music to the deaf.…”

mentioning

confidence: 99%

Special issue on intelligent biomedical data analysis and processing

2020

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Today the human lives in the age of information and technology. Information is the key, the power, and the engine that moves the world's economy. The world is moving with market data, medical epidemiologic sets, Internet browsing records, geological survey data, complex engineering models, and so on. Health Sciences are fully embedded in information technology. Health science and Biology are very complex fields and have made a long walk from ancient times. In the early 80's, AI in medicine was the primary concern while developing medical expert systems in specialized medical domains to support diagnostic decision-making. The main problems addressed at this early stage of expert system research concerned knowledge acquisition, knowledge representation, reasoning, and explanation. Now there are many modern hospitals and health care institutions, which are well equipped with monitoring and other advanced data collection devices. The need for knowledge on the domain or the data analysis process becomes essential in biomedical applications, as medical decision making needs to be supported by arguments based on basic medical and pharmacological knowledge. The new tool for analyses of biomedical applications is "Intelligent Data Analysis (IDA)." Intelligent Data Analysis can be defined as specialized statistical, pattern recognition, machine learning, data abstraction, and visualization tools for analysis of data and discovery of mechanisms that created the data. The main idea underlying the concept of Intelligent Data Analysis is extracting knowledge from a vast amount of data with many variables, that represents very complex, non-linear, real-life problems. Moreover, Intelligent Data Analysis can help to start from the raw data, coping with prediction tasks without knowing the theoretical description of the underlying process, classification tasks of new events based on past ones, or modelling the aforementioned unknown process. Deep learning is one of the fast-growing technologies, which could learn, reason, and understand the data around. Recently, we have observed several significant breakthroughs in research on artificial intelligence, including self-driving cars, computer Go, image recognition, speech recognition, and machine translation. Deep learning has been tremendously successful at object recognition and detection, localization, scene classification, action recognition, and caption generation. For example, convolutional neural networks (CNNs) have become powerful machine-learning models for various vision-based applications to represent mid-level and high-level abstractions obtained from raw data (e.g., medical images). Deep neural networks have also gained considerable commercial interest due to the development of new variants using high-performance GPUs. This special issue focuses on recent advances, challenges, and future perspectives about intelligent data analysis methods applied in biomedical studies in different domains of knowledge. From around 50 submitted articles to this particular section, 12 pa...

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Toc‐Tum mini‐games: An educational game accessible for deaf culture based on virtual reality

Cited by 11 publications

References 23 publications

Game-Based Learning for Learners With Disabilities—What Is Next? A Systematic Literature Review From the Activity Theory Perspective

Game-Based Learning for Learners With Disabilities—What Is Next? A Systematic Literature Review From the Activity Theory Perspective

XR Accessibility Initiatives in Academic Libraries

Special issue on intelligent biomedical data analysis and processing

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