Imagine that the airline whose flight you just took has a crash record of 6 out of 10 scheduled flights. So your flight was one of the four that stayed in the sky and did not return to terra firma as debris.
Despite this horrific safety record, you open your newspaper and learn that the airline is expanding its fleet, recruiting more pilots and aggressively marketing to grow its customer base. And what is most bizarre is that nobody seems to be concerned that the airline is essentially seeking to kill more people.
The deplorable rates of numeracy and literacy and drop out rates among our children are in my view analogous to airplanes dropping from the skies, with irreversible fatal consequences. I am mindful that the analogy is morbid.
As a student of systems ecology and complexity, I have always argued that understanding what determines learning outcomes and student achievement is a wicked challenge. Wicked problems do not have simple cause-effect explanations. Wicked problems often have non-linear causal pathways. They are characterized by complex interactions among myriad interacting variables. Such interactions produce complex feedback, which in turn re-define how the original factors interact and the outcomes they produce. Hence, when we frame interventions for wicked problems around a linear input – output paradigm we often get frustrated when the outcomes are vastly different from what we envisioned.
Although primary education is free, more than two million Kenyan children of school going age are out of school. We also know that retention rates are deplorable, especially among children in upper primary school, from grade six and above. Many studies have shown that competence in reading, writing and math for a many children leaves a lot to be desired. Nearly 30 percent of children who complete grade eight cannot read or write or do math at the level of a child in grade four.
Why are our children not learning? For many years we have tried to fix what we believe is the problem with education by throwing simplistic solutions at it. Like the fable of the elephant and experts, we have an expert holding the tail and swearing by their children that it is the whole elephant. Other equally cleaver experts are hanging on the trunk and would bet their last shilling that it is the whole elephant. Those holding the tusk could never be more confident about how wholesome their elephant is.
What this fable of the experts and the elephant illustrates is the limits to specialized expertise and what can go wrong if we don’t collaborate across sectors, integrate data or information and elevate the framing of intervention hypotheses to a higher systems level. What I mean here is that the reason our children are not learning goes beyond teachers or desks and books or technology. We must look at the child and his environment; the nutrition and nurturing in the first 1000 days of the child’s life, the socio-economic factors at home, the dominant livelihood of the family and the community.
Integrating multiple variables to model, predict or detect patterns has become nearly trivial in this era of open data, big data and data analytics. We don’t have an excuse for tolerating the elephant and the expert conundrum. It is possible to combine data and information on nutrition, socio-economic status of the child, education level of the mother, teachers, school infrastructure and the curriculum to understand what factors or combination of factors explain why our children are not learning. Using big data we can generate deeper insights into children’s learning and improve classroom teaching as a comprehensive picture of their capabilities and needs are developed earlier.
Open data, big data and data analytics permits sense making, understanding why our children are not learning. With big data we can predict which child is likely to have learning difficulties or is at risk of dropping out of school. Big data could make it possible to understand why retention or completion rates are low and what remedial action would be needed. Big data could ensure rationalization of investment and coordination across multiple public and private agencies. With big data we can deliver education for all, which is also tailored to the learners context and needs.
As we contemplate education reforms we must leverage open data and big data to inform our policy choices and actions.