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This response paper aims to comment on specific aspects of the position paper.

In this paper, the author presents a response to Fischer et al.'s contribution on “The Challenge for the Digital Age: Making Learning a Part of Life.” While imperatives and narratives of learning in the future have been well articulated in the literature, their paper provides insights into lifelong learning in the digital age.

The author raises comments on the comprehensiveness of the lifelong learning perspectives and the calls to action. Over the years, with multiyear efforts on the research-based evolution of the design, implementation and adoption of technology-supported learning environments in some parts of the world, the author believes well-researched innovative pedagogy and design principles have already to some extent impacted transformation of learning and teaching in normal schools. By referring to the work in the running of a model school in Taiwan, the author demonstrate some of the pathways that can guide innovation and work towards operationalizing a futuristic vision that is resonant with the one painted in the paper. The paper will end with some comments on how narratives on the future of learning will evolve.

In trying to understand the lens that the vision would bring to learning on the digital edge, the author has provided commentaries to probe into the comprehensiveness of their vision of future learning. From an Asian perspective, the author describes one effort that can help make progress in moving towards this vision. It involves realizing the vision by grounding our designs in real experiments or instantiations, such as the interest-driven creator (IDC) experimental school in Taiwan, and highlight past research efforts which have been successful in transformation of classrooms and schools such as developing seamless learning for connecting learning in different spaces afforded by mobile digital devices.

Networked learning facilitates collaboration and learning interactions. This study aims to explore networked learning in the workplace (knowledge sharing and connection building) and gain insights into the contextual factors (learner and environmental) of learning interactions.

Thematic analysis was conducted to explore how learning interactions were facilitated among healthcare workers in a large hospital in Singapore. This study examined both the learner and environmental factors of learning interactions. Interview and focus group discussions qualitative data were included in the analysis.

The findings of this study reveal that more emphasis can be placed on the environmental factors, and targeting these factors would provide a good foundation for networked learning in the workplace, whereas learner factors could be promoted to enhance additional learning interactions. This study also found that workers learn most frequently from experienced seniors, indicating the value of mentorship programmes in fostering high-quality learning interactions.

This paper sheds light on the comprehensive set of factors that encourage networked learning among healthcare professionals and provides empirical findings that might direct future studies in similar domains.

This study aims to contribute to literature on mobile learning (m-learning) by proposing four research clusters whereby scholars can expand m-learning research to facilitate effective learning experiences for students.

This study reviews student-centric literature on m-learning since 2010 and presents insights on m-learning while applying well-established bibliometric techniques. Consequently, 722 articles published in the past decade were evaluated by identifying key research areas, most influential authors, countries, journals and organisations. Most influential studies based on number of citations were also examined.

Through article co-citation analysis, four clusters representing m-learning literature were identified: concept of m-learning, application of m-learning in education, designing framework for model learning/acceptance and emerging technologies.

As mobile learning (m-learning) has undergone an evolution from being an emerging field to a significant teaching and research tool, it is pertinent to explore and identify the trends of m-learning research.