Mobile-Assisted Language Learning Strategies

Mobile-assisted language learning (MALL) encompasses pedagogical approaches that leverage smartphones, tablets and related applications to facilitate the acquisition of a second or foreign language. Strategies range from in-class integration—where learners use devices to access interactive exercises or pronunciation guides—to self-directed activities outside the classroom in which personalised apps deliver vocabulary drills, real-time feedback and authentic communicative tasks. Key theoretical underpinnings draw on technology-acceptance models and self-regulated learning frameworks, emphasising the importance of perceived ease of use, perceived usefulness and facilitating conditions in shaping learner engagement. The ubiquity and portability of mobile devices support contextualised learning, enabling students to practise speaking in everyday environments, enrich vocabulary through image-to-text tools and collaborate via social features. Practical applications span scripted lesson plans, gamified platforms and adaptive algorithms that tailor content to individual proficiency levels. Globally, MALL strategies have been shown to enhance learner autonomy, motivation and linguistic performance, while offering educators scalable, data-informed means to personalise instruction and sustain lifelong language development.

Research from Nature Portfolio

No recent Nature Portfolio content available.

Mobile-Assisted Language Learning Strategies publication trend

The graph below shows the total number of articles in mobile-assisted language learning strategies across all publications each year (not limited to Nature Index journals).

Technical terms

Mobile-assisted language learning (MALL): The use of mobile devices to support language acquisition through tailored activities and resources.
Perceived ease of use: Learners’ judgement of how effort-free it is to employ a technology in their studies.
Perceived usefulness: Learners’ belief that using a technology enhances their language learning outcomes.
Facilitating conditions: External factors, such as technical support and infrastructure, that enable technology integration.
Self-regulation skills: Learners’ capacity to plan, monitor and adjust their own learning activities.
Automatic speech recognition (ASR): Technology that converts spoken language into text to aid pronunciation and speaking practice.
Text-to-speech (TTS): Technology that generates spoken output from written text to support listening and pronunciation tasks.

References

1. Investigating the facilitating conditions, perceived ease of use and usefulness of mobile-assisted language learning. Smart Learning Environments (2023).
2. Investigation of Facilitating English Speaking of Elementary School Students in Authentic Contexts with UEnglish. Human-Centric Intelligent Systems (2023).
3. University students’ use of mobile technology in self-directed language learning: Using the integrative model of behavior prediction. Computers & Education (2022).
4. Using image-to-text recognition technology to facilitate vocabulary acquisition in authentic contexts. ReCALL (2020).