By Niall Winters
Let’s start by asking what is an appropriate technology? In many cases in ICT4D, it refers to the technology that is readily available to communities, and in the case most relevant to the mCHW project, this technology would be low-end mobile phones. Therefore, the usual starting point for many participatory and community-focused projects is: what can we co-design with the community that will work on their phones? This often leads to projects that focus on SMS-based solutions, leading to interventions that scale to many users easily. Such a solution is seen as an “appropriate” technology and is a position well supported by the HCI community. However, is this the right starting point? Those working in social justice, perhaps controversially to some, strongly critique this position.
Let’s take a different starting point. In our project, we’re focused on the interaction of health and education. If you were a community health worker, what kind of tools would you like to use? Would the most interesting solution to you be an SMS-based solution that premises short text messages and interactive voice systems? Or might you be interested in an educational app that runs on a smartphone and allows for a much richer set of learning activities and interactions. The key question to ask is what is the highest standard to intervention that can be developed? In our project, this meant asking what should the intervention look like from both pedagogical and technical viewpoints. This places our intervention design in stark contrast to many other mobile learning or mobile health initiatives.
If we examine the literature for mobile learning for development (ML4D), for example, we find that the modus operandi of mobile learning interventions has been to “get learning” directly into the hands of health care workers by means of information-centric implementations delivered via SMS (or as content on smartphones). This has resulted in over-simplistic “solutions” that are extremely limited in their ability to support learning and training for complex tasks such as diagnosis. It positions health workers as ‘low-level’ users by promoting a codified view of knowledge, which is well known to have limitations when applied to practice. In assuming simple uses of mobile learning and training, mobile health has inadvertently supported structural inequality, undermining the very challenges it seeks to address. Consequently, this project rejects the ‘top-down’ approach, opting for a participatory approach that enables detailed investigation of health workers’ training needs, attending to the process of integrating mobile-based training and supervision into community programmes. It moves beyond the “what health workers need to know about technology”, a deficient view of educational technology, to re-position health workers as core participants in the development process. This is the first part of our “highest standard” approach.
The second part concerns a technical point of view. In order to design and implement a complex, practice-based intervention, such as our REFER app, there is no other choice but to use smartphones. The simple fact is that the quality of training experience that we wish to develop is not possible with low-end phones. Appropriate technologies then need to be redefined as those that provide the highest standards possible without recourse to reductionist financial modelling that seems increasingly to be applied to the poor but not the nonpoor.