Mobile Assisted Language Learning (MALL): Trends from 2010 to 2020 Using Text Analysis Techniques

Arvanitis, Panagiotis; Krystalli, Pinelopi

doi:10.26417/461iaw87u

Cited by 10 publications

(7 citation statements)

References 5 publications

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“…Mobile-Assisted Language Learning (MALL) is characterized by portability, interactivity, connectivity, and privacy and is carried out in real time. Many studies thus have applied it to the process of learning English to create appropriate contextual learning scenarios ( Wu et al, 2011 ; Panagiotis and Krystalli, 2020 ). These studies illustrate that mobile technology can help learners extend English acquisition to familiar environments outside the classroom, as well as presenting other contextual learning situations.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Influence of Artificial Intelligence Markup Language-Based LINE ChatBot in Contextual English Learning

Chien

Lai

et al. 2022

Front. Psychol.

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This study is intended to create an innovative contextual English learning environment making use of the widely used communication software, LINE ChatBot, based on the Artificial Intelligence Markup Language (AIML), in order to improve speaking and listening ability among learners. A total of 73 students were invited to participate in learning activities involving a 4-week English conversation exercise including both speaking and listening. Additionally, in order to explore the influence of competition on language acquisition, we added competition characteristics to the learning activities in the experimental group to enhance learning motivation and learning outcomes. The results showed that with the help of the LINE ChatBot contextual learning environment, the performance of both groups of students was slightly enhanced, but no significant differences were found. Meanwhile, extrinsic motivation in both the experimental and control group was improved if they spoke anonymously. That is, the contextual learning environment based on the LINE ChatBot significantly improved the learners’ English speaking and listening ability. In addition, the results showed that the addition of a competition element effectively enhanced the learners’ intrinsic motivation to learn English on the LINE ChatBot.

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Section: Introductionmentioning

confidence: 99%

Investigation of the Influence of Artificial Intelligence Markup Language-Based LINE ChatBot in Contextual English Learning

Chien

Lai

et al. 2022

Front. Psychol.

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“…For the past ten years, the research topics of MALL such as improving speaking, pronunciation, listening, vocabulary skills, and users' perception and attitudes remain vibrant [15] among which the application and study of MALL on vocabulary and grammar are on the top of the topic list [6], [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring Chinese EFL Teachers’ Acceptance of Mobile-Assisted Language Learning (MALL)

Lin¹,

Abdullah²,

Samad³

2022

IJIET

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Mobile-Assisted Language Learning (MALL) has emerged as an important domain since mobile devices are widely used by the current generation of learners. This study emphasizes that the successful implementation of MALL for language education relies heavily on its acceptance by teachers. This study intends to investigate the acceptance of using MALL for teaching English among college EFL teachers in China. The Technology Acceptance Model (TAM), a frequently used model in technology acceptance studies for m-learning settings, was adopted in this study. A questionnaire survey was administered to collect data on teachers’ demographic information and acceptance of MALL. The respondents were 30 in-service college-level EFL teachers from universities in Yunnan, China, and the data are analyzed using SPSS. Respondents’ MALL acceptance level, their demographic variables associated with intentions to use MALL, and the relationship of Perceived Usefulness (PU), Perceived Ease of Use (PEU) with Behavioral Intention (BI) were investigated. The results suggested that Chinese EFL teachers have a rather high level of MALL acceptance. Their BI to use MALL differs according to the teaching experience. Both PU and PEU significantly influenced BI which further predicted the Actual Use (AU) of MALL. The findings of the study provide insights into the usefulness of TAM in predicting the acceptance of MALL among college EFL instructors and may assist in explaining the factors influencing their intentions to utilize mobile technology for language teaching.

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“…Like other mobile devices, mobile phones, provided with internet access services and different applications, are considered as widespread tools and are used in language learning. Using mobile phones in language learning as MALL is still a great interest and a steady preoccupation of researchers over these 10 years (Panagiotis & Krystalli, 2020) including the MALL approach to enhance speaking.…”

Section: Related Literature About Mall-based Interventions In Efl Spe...mentioning

confidence: 99%

Effectiveness of Mobile Assisted Language Learning (MALL)-Based Intervention on Developing Thai EFL Learners’ Oral Accuracy

Phetsut

Waemusa

2022

IJTE

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With the rapid growth of digital technology, mobile phones are widely used for EFL teaching and learning. However, little is known about the effectiveness of integrating a mobile application into EFL classrooms to improve oral accuracy in Thai school contexts. An instructional intervention grounded with Mobile Assisted Language Learning (MALL) and dynamic assessment in Thai EFL contexts needs to be further investigated. This quasi – experimental study aimed to investigate the effectiveness of a mobile-based intervention to develop Thai EFL learners’ speaking. Thirty students from a secondary school in southern Thailand were assigned to complete five oral tasks through the dynamic assessment process as an intervention on WhatsApp in order to develop their oral accuracy. Quantitative data were collected from the oral pre-test and post-test to examine the students’ speaking development by utilizing the paired samples t-test. The results showed a significant difference between the pre-test and post-test after the implementation of the MALL-based intervention. It could be suggested that the application of the MALL-based intervention could develop EFL learners’ oral accuracy in Thai school contexts. Implementations and recommendations of this study are discussed.

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Mobile Assisted Language Learning (MALL): Trends from 2010 to 2020 Using Text Analysis Techniques

Cited by 10 publications

References 5 publications

Investigation of the Influence of Artificial Intelligence Markup Language-Based LINE ChatBot in Contextual English Learning

Investigation of the Influence of Artificial Intelligence Markup Language-Based LINE ChatBot in Contextual English Learning

Exploring Chinese EFL Teachers’ Acceptance of Mobile-Assisted Language Learning (MALL)

Effectiveness of Mobile Assisted Language Learning (MALL)-Based Intervention on Developing Thai EFL Learners’ Oral Accuracy

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