Holistic and dynamic: teacher-researcher reflections on operating mobile-assisted learning tasks supported by WeChat for Chinese as a foreign language

Tong, Peiru; An, Irene Shidong; Zhou, Yijun

doi:10.1007/s11251-020-09524-3

Cited by 14 publications

(32 citation statements)

References 49 publications

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“…The five papers T. H. Chen & Lin, 2018;Jiang & Li, 2018;Morgana and Shrestha, 2018;Tong et al, 2020) that focused on perceptions explored the students' and teachers' perceptions of integrating mobile technologies into task-based language learning. The students' perceptions of mobileassisted tasks (MAT) included effectiveness and performance of tasks, as well as levels of challenges and motivation when carrying out tasks.…”

Section: Research Areas and Research Focimentioning

confidence: 99%

“…With regards to sample size, except for one paper (Tong et al, 2020) that did not specify the sample size, the sample size in the remaining 15 papers ranged from below 20 (n=6), 20 to 50 (n=7), to more than 50 (n=2). It ought to be pointed out that four papers (McLellan et al, 2021;Morgana & Shrestha, 2018;Park & Slater, 2015;Tong et al, 2020) included both teacher and student participants, and 11 papers included only student participants, compared to one paper (Pellerin, 2014) that involved only teacher participants. With a relative sample size, the limitation of the studies is apparent, and therefore the findings cannot be generalized.…”

Section: Participantsmentioning

confidence: 99%

“…Both Park and Slater (2015) and Gasparini (2018) had conducted interviews to investigate learners' needs analysis. In addition to interviews, observations were also carried out for data triangulation by Morgana and Shrestha (2018), Tong et al (2020), McLellan et al (2021), and Pellerin (2014. Other instruments in various forms, such as written drafts, recordings etc.…”

Section: Data Collection Techniquesmentioning

confidence: 99%

“…With respect to technology or approach evaluation, comparisons between a control group and an experimental group were made. As for technology evaluation, thematic data analysis by Tong et al (2020) on WeChat-supported tasks revealed two overarching themes, i.e. holistic of the implementation model and dynamic of teachers' active motivation.…”

Section: Learning Outcomesmentioning

confidence: 99%

“…Next, specific contextualization, i.e., limit to private schools or to a certain type of mobile technology, was pointed out in two papers Morgana & Shrestha, 2018) as an issue that can limit the generalization of the findings. Tong et al (2020) reported that reliance on teachers' perspectives is a major issue, as subjective reflections limited the generalizability of findings. In addition, lacking in-depth investigations constitute another issue.…”

Section: Issues In Mobile-assisted Task-based Learningmentioning

confidence: 99%

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Systematic Review of Mobile-Assisted Task-Based Learning Based on WoS (2013-2022)

Jia

Harji

2022

JITE:Research

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Aim/Purpose: The aim of this paper is to present a systematic review of studies conducted on mobile-assisted task-based learning between 2013 and 2022. The primary objectives of the review are to elicit educational and learning contexts, research areas and foci, research trends, methodologies, data collection techniques, mobile technology used, learning outcomes, and issues in mobile-assisted task-based learning. Background: Conventional task-based learning has evolved over the last decade with numerous researchers incorporating various mobile technologies and devices to enhance the task-based approach. This paper presents a systematic review of task-based learning, specifically with the adoption of the mobile-assisted method in delivering tasks. Methodology: To provide viable discussions and maintain the accuracy of the review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Liberati et al., 2009) protocol items were adhered to. The papers for review were sourced from ISI Web of Science within the last decade from 2013 to 2022. The outcome of screening based on the inclusive and exclusive criteria as well as from the backward search resulted in 16 papers out of 276 papers that were eventually reviewed and analyzed. Contribution: This study is of significant value, especially during the post-pandemic period, as mobile task-based learning provides for flexibility and portability, and to date, no systematic reviews have been conducted specifically on mobile-assisted task-based learning in the last decade. This review looked at the study characteristics, educational and learning contexts, research areas and research foci, research trends, methodologies, data collection techniques, mobile technology used, learning outcomes, and issues in the papers on mobile-assisted task-based learning. In addition to attributing to the existing body of knowledge, this paper provides insights for researchers, educators, as well as mobile technology developers for consideration. Findings: Major findings are that all papers are on language learning, with English as a foreign language being the most frequently researched area, and most of the studies are conducted in higher education contexts. Informal learning has become a critical learning setting, and language proficiency and participant perceptions are the two major foci. In addition, no studies have been found to combine mobile learning and social media platforms together to promote language acquisition. Recommendations for Practitioners: This systematic review provides practitioners with an overview of mobile technologies that have been found to be effective in the task-based approach for different educational levels and language skills. These effective mobile technologies could be considered for adoption in their respective contexts. Recommendation for Researchers: For researchers, the time frame for a systematic review could be expanded to increase the number of papers for review. In addition, to ensure the comprehensiveness of findings, big data analysis software could be employed to analyze the research foci, research trends, and research shifts. Additional databases could be added for more extensive review. Impact on Society: The research findings of this paper can provide benefits for researchers, educators, and mobile technology developers for them to collaboratively promote the development of mobile-assisted task-based learning. Future Research: Future researchers could conduct in-depth empirical studies on mobile seamless learning, research with tasks that are designed based on learners’ needs analysis and explore cognitive load as well as learning anxiety which are not extensively researched.

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Section: Research Areas and Research Focimentioning

confidence: 99%