Codesigning A Big Data Analytic Tool for Girl Child Learner Drop Out from Eastern Cape Province -South Africa

Codesigning A Big Data Analytic Tool for Girl Child Learner Drop Out from Eastern Cape Province -South Africa

Harare, Zimbabwe and Virtual

Developing sustainable solutions is critical for adoption of digital solutions. As the high number of learners dropping out of school continues to increase, it is critical to find innovative ways of predicting and preventing high drop out. Current literature has documented a number of factors that influence learner drop out. Innovative ideas, techniques and activities have been undertaken to motivate learners to stay at school. It is unfortunate that most of the initiatives have not helped to avoid drop out of learners. The study is based on a mixed approached that was used targeting female learns from Oliver Tambo District in the Eastern Cape Province of South Africa which consists of face-to-face engagements and community codesigning approach. A variety of factors were presented as drop out reasons. These factors represent large data sets that are available to affect learners. A big data analytic tool was co-designed involving key stakeholders in education since they also have an influence on learners. Emerging technologies such as machine learning and big data analytics were applied to produce the presented tool.