From oil and gas to the health sector, and many others, artificial intelligence is eliciting momentous transformations in overall productivity and the way operations are carried out. Within the past decade, the implementation of artificial intelligence in solving routine and complex challenges has known no bounds. Whilst artificial intelligence involves the development of algorithms that make machines smarter, the technology is also being used, now, to help students get smarter. The educational sector in Africa has joined the league of sectors being transformed by the magic of artificial intelligence. In Africa, artificial intelligence is being weaved into the educational sector to improve the quality of education.
In 2018, Kenyan entrepreneur, Claire Mongeau, launched M-Shule, an AI-powered SMS-based edtech startup, in Nairobi, Kenya. The startup is leveraging the use of artificial intelligence algorithms to analyze the individual performance of students, their academic strengths and weaknesses, and then deliver personalized learning content that meet the individual needs of students and aid improvements in the competence and academic strength of each student. M-Shule also provides analytics and insights on the progress and performance of students to the schools, teachers and parents of the students. This enables close monitoring and evaluation of the performance of students and the introduction of learning assistance when necessary. The adaptive learning platform is easily accessible by African students because it works offline and requires the use of SMS alone. By sending MSHULE to 40606, any student can get connected to the M-Shule platform.
Mtabe is another edtech startup, based in Tanzania, that harnesses the power of artificial intelligence to improve learning in African schools. The Tanzanian startup offers similar services to M-Shule. Mtabe offers an AI-powered product that provides customised instant lessons and answers from a virtual tutor to students. This is done via SMS. The platform employs the use of AI to facilitate the provision of personalized educational resources to students who have no access to the internet or textbooks.
Just like Mtabe and M-Shule, Schoola broadens the horizon of personalized learning in Africa, but for Nigerian-based students. The startup, which recently emerged as one of the top ten startups that was offered full sponsorships to attend the 40th edition of GITEX Technology at the World Trade Centre (DWTC) Dubai, UAE, offers a gamified AI-based learning product that operates on the learning content developed by the individual k12 schools.
Fast-rising Nigerian-based edtech startup, Gradely, also makes use of artificial intelligence to customize learning content, like video tutorials, etc, and practice exercises for students. The e-learning platform incorporates AI to recommend learning materials for students from the data obtained from regular assessments. The platform analyzes the performance of students in their weekly assignments and provides information on their learning progress and the challenges that have been identified. This enables parents and teachers to intervene early enough to ensure that the academic performance of a student does not continue to decline steadily. The startup also supplements its platform with elements of gaming to engage students and grow their competence.
Beyond personalized learning content, AI is being applied in many other ways to improve education in Africa. In 2017, while contesting in Facebook’s Bots for Messenger challenge, Nati Gossaye birthed the idea of Langbot, an AI-powered platform that facilitates the teaching and learning of languages. Today, Langbot specializes in the teaching of languages through the use of chatbots. The chatbots are extremely intelligent and mimic human tutors.
Via the use of Langbot’s product, tools are provided for schools and teachers to create chatbots that offer personalized language learning content to teach students and help them in preparing for language tests.
In 2019, Data Science Nigeria proposed the use of deep-learning-powered cameras to recognize and assess the engagement levels of students and their behavioural patterns in a classroom. With the aid of these cameras, the behaviour of each student in a classroom can be closely monitored and analyzed. This will facilitate the detection of learning-risk indicators like fatigue, emotional distress, frustrations and learning dysfunctions.