BLOG POST: Deciphering M-learning

M-learning is a term coined to cover a complex array of possibilities opened up by the convergence of new mobile technologies, wireless infrastructure and e-learning developments.  As with any emerging paradigm, there are many attempts to define its essence. M-Learning can basically be defined as the intersection of mobile computing and e-learning: accessible resources wherever you are, strong search capabilities, rich interaction, powerful support for effective learning, and performance-based assessment.

Because mobile phones are increasingly becoming part of the everyday lives of the poor, it is argued that they have potential to become a low cost accessible delivery channel for learning services, thus facilitating innovations including m-learning. Existing initiatives (Keegan, 2003) are already demonstrating the viability of such services in developing country environments. Research also suggests that the poor majority are in need of, and are increasingly demanding, a broader range of micro-learning services that could potentially be delivered via mobile phones or via mobile phone operators. These have been specified as low cost solutions that can underpin regular savings, facilitate informal learning, reduce the digital divide and deliver knowledge. However, studies also caution that the learning needs of the poor are fungible and embody a complex set of interactions across a broad portfolio of predominantly informal learning settings. There is a primary requirement, therefore, to more fully understand the interrelationship between the suggested potential for mobile phone applications and the reality of the educational preferences and behaviours that the poor majority exhibit.

There is an indication, with some exceptions, that knowledge and understanding of the learning needs of poor communities have not been sufficiently linked to existing m-learning research or to the development and implementation of initiatives.  This may be due to the fact that most, if not all, m-learning initiatives are commercially driven by the mobile phone industry as a value added service that is primarily designed to expand market share and generate revenue.  Consequently research has been informed by business models that emphasise market development rather than social models that may put greater emphasise on community needs assessment.  This orientation is followed by the current actors in the field of research, whose primary focus is system functionality and business value, focusing on technical and organisational aspects, rather than on the disruptive or ripple-effects.

Despite a rapid expansion of research into mobile phones and learning applied to developing countries, there has been no systematic attempt to review how this research has progressed both conceptually and methodologically.

Overall, the existing research body suggests the following practical implications as stated by this article:

  • A high level of practitioner involvement and the high level of positive interaction between the donor community and the mobile phone industry. This has set in motion a research agenda that seeks to seriously address the potential of new technologies to serve the needs of poor communities via m-learning.
  • Specific attempts to develop theoretical models, and create a deeper understanding of m-learning applications, most noticeable in the area of application development and technology adoption.
  • A small number of primary research studies that have developed rigorous methodologies for data collection and analysis, and where those approaches and lessons learned have been documented and shared.

The following remarks should be taken into account for the progress of m-learning:

  • That the research area has become too overtly ‘technology-led’ and driven by a mobile industry-donor nexus which (and in the absence of a strong evidence base) has tended to over-‘hype’ the potential of m-learning applications for poor users.
  • There has been lack of focus on assessing learning needs a priori to specifying m-learning solutions, and by and large importance has not been attached to analysing the relationships between the technical and systemic aspects of m-learning services and the behaviours and preferences of poor users.
  • In this respect there has been lack of focus on methodologies that emphasise user involvement such as participatory methods and action research, or where these approaches have been used they remain undocumented.
  • The research area overall is unbalanced in terms of methodological approach, with use of surveys and quasi-experimental techniques outweighing qualitative approaches – which could be used to build in-depth case studies that can form the basis for theorising.  With a few notable exceptions, the research reviewed tends to lack depth of evidence and analysis.  Issues of validity of findings and attribution of causality have yet to be addressed sufficiently.
  • Overall, there is lack of geographical diversity, with the state of current knowledge based upon a relatively narrow evidence base.  There is also lack of published research being conducted by developing country institutions and researchers.

Maybe it is time to tap into the potential of mobile phones for m-learning.

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