Though schools have adapted impressively to hybrid learning models, it’s becoming clear that remedial measures are going to be necessary if we’re to help students make up for lost time. To that point, news aggregator All Africa reported last summer that about two-thirds of countries across the continent are taking steps to help students catch up. Some initiatives they’re enacting include adjusting curricula to resolve learning losses and improving facilities to enhance a return to in-person schooling.
Steps like these depend largely on one crucial tool: Big Data. So below, we’re going to look at a few ways in which schools across Africa are leveraging data analytics –– and data-driven learning as a whole –– to set up optimal education in the New Normal.
When administrators are formulating school policies, data analytics can simplify the process of discerning which areas require immediate attention. For example, a school may simultaneously be experiencing declining rates of enrolment and gender diversity in the classroom. With research from the Journal of International Development having found that administrative data plays a significant role in informing gender-equitable outcomes, schools can analyse their enrolment history – and will likely discover that simply prioritising enrolment will not guarantee more equal gender representation among students. Consequently, any enrollment-related policies the school adjusts can be better informed and can be engineered specifically to bring more girls into the classroom.
Data analytics can similarly help schools facing financial challenges. Indeed, this focus can be especially helpful here in Sierra Leone — where, according to the International Journal of Educational Development, the majority of schools do not receive government funding. By analysing a school’s history of resource allocation, administrators can determine which departments have been maximising their budgets and which ones require more funds given the current circumstances. Financial analysis can also help predict the success of cost-cutting measures like adopting automated administrative tools or merging sections with low class sizes –– which can ultimately help schools run more effectively on smaller budgets
With data analytics, teachers can also curate lesson plans and assessments, and track each pupil’s progress. This allows them to gain a better understanding of which students need help in specific areas, and enables them to adjust their teaching methods strategically if general engagement is low. This process is exemplified by the tools used at Bridge Uganda, which is part of a continent-wide education network. Through this program, teachers use specially-crafted, data-driven lesson plans and are given tools to track pupils’ progress. As a result, the 2020 McKinsey report titled “Reimagining a More Equitable and Resilient K–12 Education System” found that Bridge pupils learned an additional 2.5 years’ worth of material within a year-long period.
In many regions, outdated curriculums are still being used despite their inability to satisfy the contemporary student’s unique circumstances. Data analytics’ predictive properties, however, allow educators to assess current and future educational requirements, so that they can update teaching priorities according to real-world needs. At the same time, data science itself is becoming an in-demand skill in the modern job market. It’s thus no wonder that higher education institutions like Njala University in Sierra Leone are celebrated for being among the first to host seminars on leveraging Big Data aimed at administrators, educators, and students alike. At the same time, some of Africa’s largest and leading schools like the University of Nairobi have begun to establish big data courses, including deep learning and AI optimisation. Through this, many are hopeful that the new generation of graduates will be better equipped for data-based careers and trends.
Addressing the digital age’s concerns in education will be a long and arduous road. But with data analytics, schools can build data-driven learning cultures that can pave the best path forward.