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This study aims to investigate a unique approach to learning languages through self-directed online learning. Specifically, it explores the self-management abilities and skills learners need while learning a language outside traditional classroom settings when using mobile-assisted learning technology.

A mixed-methods approach was used in this study, including an online survey of 84 people and 10 semi-structured interviews.

Findings reveal the significant role of specific and well-defined learning goals in enhancing learners’ performance. These goals can be either self-initiated by the learners themselves or defined by the technological features of the learning platform. However, the presence of distractions in learners’ daily lives presents challenges to effective time management, affecting learners both physically and psychologically. A key aspect of self-directed language learning lies in the learners’ ability to seek out relevant human and material resources beyond the confines of a single mobile-assisted language learning (MALL) tool. The authenticity of these resources is crucial in ensuring meaningful and effective learning experiences.

Understanding how learners navigate and discover valuable resources is a central focus of this study. This research offers valuable insights into the field of self-directed language learning, revealing the pivotal role of self-management skills with mobile-assisted learning technology. The findings contribute to the broader field of language education and offer practical implications for educators and developers seeking to optimize self-directed language learning experiences through innovative and technologically driven approaches.

MALL is often ideal for individualized informal learning, but the existing literature focuses heavily on formal learning situations, underestimating the importance of MALL practices in various informal settings. Most research reports on MALL-based self-directed learning primarily sample traditional English-learning university students. Therefore, there is a need for research on how nontraditional older adult learners self-direct their language learning with mobile technology outside the classroom.

The search for new techniques to teach English nowadays has been more than ever. These techniques have to be interesting and enjoyable in order to lower the anxiety levels of students when learning English (Bakhsh, 2016). That is why many scholars and teachers look forward to integrating technology into language teaching. Social media platforms (SMPs) are among these techniques since millions of people around the world utilize them for daily interaction. Yet, teaching English for specific purposes (ESPs) relies on learners’ needs and employs an eclectic approach in delivering its course content. For this reason, the current study reviewed articles that tackled the topic of teaching or learning ESP from SMPs so as to uncover their effect and the attitude or motivation of learners.

The researchers used the PRISMA flowchart model in order to identify, screen and include articles in the study.

The results revealed that SMPs are effective in teaching and learning ESP writing, speaking and vocabulary. Yet, the included studies showed that learners’ attitude toward SMPs is positive as they believe that they are motivating and interesting.

Some aspects of social media have turned out to be beneficial in the learning process and they need further investigation from ESP practitioners and scholars.

According to the study, it is crystal clear that the various social networks and platforms are beneficial and helpful for improving ESP productive skills.

The proliferation of ChatGPT, as in many other digital technologies and social media, has increasingly impacted many aspects of modern life, including second and foreign language education. This study, building on a common theoretical position of all these advances in Artificial intelligence (AI), seeks to establish a model for ChatGPT research on English language learning. It specifically explores the dimensions in which ChatGPT aids students in their English language learning.

The study adopts grounded theory in collecting and analyzing data from 20 ResearchGater (RG) through a two-week RG discussion about ChatGPT uses in their language learning contexts. Data collected via the discussion was analyzed thematically.

Preliminary findings show that ChatGPT can be used in developing learners' language skills; scaffolding the learning process by providing feedback to students on their language use and acting as partners in practicing language with recommended activities for more language practice.

The study contributes a five-dimension model for artificial intelligence assisted language learning (AIALL). The model involves flexible teacher's role to consolidate learner autonomy and provide enjoyable learning, urges future innovation, and celebrates various applications. Examining the AIALL model of ChatGPT for language learning, teachers should provide some directions for properly using this new application.

This study aims to explore customer perceived value (CPV) dimensions in the context of free mobile educational applications (EduApps) which are paramount in learning-based digital start-ups and are essential for the implementation of circular economy (CE). The purpose of the present study is to identify dimensions of CPV specifically for EduApps and propose a conceptual model that would assist the digital start-up decisions which in turn can be a catalyst in navigating to a CE.

The study uses the Netnography approach by analyzing online user-generated content. A total of 13,147 reviews posted on the Google play store after using top free education apps were coded using ATLAS.ti 9 software.

Major dimensions of context-specific CPV are identified as technical value, content value, pedagogical value, gamification value and learning value. Subdimensions and items are extracted for each of these dimensions.

The larger subscriber base drives sponsorships, advertisements and donations which underpin the business model of free EduApps. This can be obtained through an attractive value proposition. Identifying context-specific value dimensions would aid entrepreneurs in optimal value mix development decisions. The proposed framework can be utilized by both researchers (for scale creation, comparative studies and quantitative studies) and practitioners (for entrepreneurial decisions on better value propositions).

CPV successfully describes consumer decision-making, but less attention is paid to linking the theory to the setting of mobile learning apps, where the bulk of research is focused on techniques like TAM, UTAUT, etc. In addition, studies identifying CPV from mobile apps with a specific focus on EduApps are sparse. Extant literature in this context is either based on a foundation of in-store business value dimensions or dominated by technical aspects when focused on the context of mobile apps. The current study bridges this gap.