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

Abstract

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.

Benefits and Challenges of Mobile-Learning Brought to Student Learning Outcomes in Higher Education: A Systematic Review from 2014-2023

“…Ifeanyi and Chukwuere (2018) found out that mobile learning efficiently promotes student engagement. Despite benefits, existing studies also indicate that ML also imposes challenges and negative influences on student learning (Jia et al, 2022). In order to optimize ML and improve student learning, it is necessary to review the benefits.…”

“…Published Online: 29 February 2024 perspectives, including student learning motivation, learning process, and cognitive development (Jia et al, 2022).…”

A Bibliometric Analysis of English for Specific Purposes from 2011 to 2023 Using Citespace: Visualizing Status, Themes, Evolution, and Emerging Trends

“…The literature quantity with the time distribution figure can shed light on the research status and development of the discipline or the field, which works as a prediction for future research trends (Diao et al, 2022;Fu et al, 2021). This review This review obtained data from the Web of Science Core Collection (WOSCC) on September 25, 2023, because the WOSCC included high-quality journal literature widely recognized and influential worldwide, and is suited for extensive and bibliometric analysis on a large scale (Jia &Harji, 2022). The ESP classification of Dudley-Evans and St. John (1998) was adopted in the process of the search queries.…”

“…As suggested by Jia and Harji (2022), and Wang et al (2023), some inclusion and exclusion criteria were adopted in data collection and screening. The literature database was obtained from the WOSCC.…”