Using augmented reality with speech input for non-native children's language learning

Dalim, Che Samihah Che; Sunar, Mohd Shahrizal; Dey, Arindam; Billinghurst, Mark

doi:10.1016/j.ijhcs.2019.10.002

Cited by 92 publications

(66 citation statements)

References 33 publications

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“…Nowadays, other languages apart from English language [1] paying attention to researchers in order to evaluate the applicability of Natural Language Interaction (NLI) methods to other languages [2].…”

Section: Related Workmentioning

confidence: 99%

Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network

Mechti¹,

Alroobaea²,

Krichen³

et al. 2020

IJACSA

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This paper focuses on identifying the Arabic Language learners. The main contribution of the proposed method is to use a deep learning model based on the Gated Recurrent Unit Network (GRUN). The proposed model explores a multitude of stylistic features such as the syntax, the lexical and the ngrams ones. To the best of our awareness, the obtained results outperform those obtained by the best existing systems. Our accuracy is the best comparing with the pioneers (45% vs 41%), considering the limited data and the unavailability of accurate tools dedicated to the Arabic language.

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Section: Related Workmentioning

confidence: 99%

Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network

Mechti¹,

Alroobaea²,

Krichen³

et al. 2020

IJACSA

View full text Add to dashboard Cite

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“…The solving problems were formed through personal experience, deep exploration activities, complexity, and dynamic learning [61], [62]. The use of MAR provides a better evaluation of problem identification [63]. The process of integrating, synthesizing problems, and analyzing data could directly develop CPS abilities.…”

Section: Discussionmentioning

confidence: 99%

Effect of Mobile-Augmented Reality (MAR) in Digital Encyclopedia on The Complex Problem Solving and Attitudes of Undergraduate Student

Putra

Sumarmi

Sahrina

et al. 2021

Int. J. Emerg. Technol. Learn.

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The study aimed to determine the effect of mobile aug-mented reality in the digital encyclopedia on complex problem-solving ability and responsible decision making attitude of first-year students. The research was a quasi-experiment (quantitative research) with pre-test and posttest methods. The population was first-year students of 2019/2020 in the Geography Education program, Faculty of Social Sci-ences, State University of Malang. The experimental group was from the PGEO6006-L class, and the control group was from the PGEO6006-A class, totaled 73 participants. Data were collected using a qualitative method using interviews and a quantitative method using a questionnaire for 4 weeks. The data analysis used an independent t-test to determine the effect of mobile augmented reality on students' complex problem-solving ability and responsible decision making atti-tude in Cosmography class. The results indicated that mobile augment-ed reality in the digital encyclopedia has a significant effect on stu-dents' complex problem-solving ability and responsible decision mak-ing attitude.

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“…Furthermore, Bacca, et al [21] stated that the most reported limitations involved maintaining superimposed information, paying excessive attention to virtual information, and considering AR as intrusive technology. In general, the most reported disadvantage concerned technical issues, specifically design flaws in the user interface [25][26][27][28] such as inconsistent responses in AR applications [25,28], unexpected programme exits, delayed responses [27,29] and inaccuracies of sensor detection [28]. As the research on AR integration in education is still developing, the resulting limitations could be overcome by fully exploring potential AR technologies with an adequate timeline for technological stability and maturity.…”

Section: 2mentioning

confidence: 99%

A Systematic Review of Augmented Reality Applications in Language Learning

Majid

Salam

2021

Int. J. Emerg. Technol. Learn.

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Augmented reality (AR) is one of the emerging technologies gradually venturing into the education field. Although AR is strongly linked to subjects related to Science, Mathematics, and Technology in schools and tertiary education, there is no mention of AR in non-technical subjects, such as language. Thus, this study aims to discover the AR application trends in language learning and the language skills prevalent in AR usage. In this systematic literature review, AR-related research in language learning began in 2016 and has continued to be on the rise. Furthermore, the preferred language skills used with AR technology required lower cognitive levels, such as identifying words, understanding meanings, and spelling, and pronouncing words. Based on the gap indicating the rare usage of AR for more complex and critical language skills, such as reading and writing, this study hopes to enlighten the researchers, educators, and application developers to focus on developing AR applications for languages other than English, incorporate higher-order learning outcomes in the language learning activities, and pursue qualitative investigations.

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Using augmented reality with speech input for non-native children's language learning

Cited by 92 publications

References 33 publications

Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network

Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network

Effect of Mobile-Augmented Reality (MAR) in Digital Encyclopedia on The Complex Problem Solving and Attitudes of Undergraduate Student

A Systematic Review of Augmented Reality Applications in Language Learning

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