Thirteenth International Conference on e-Learning & Innovative Pedagogies

Abstract

In most low to middle income countries (LMIC), access and use of educational materials and information dissemination are currently through paper systems and partly by digital technologies without learning and predictive analytics functionalities. The UZCHS is using TSIME, a customized version of Claroline as a Learning Management System where hosts of educational e-resources are found. These e-resources can only be accessed using the physical ICT infrastructure such as local WiFi and Ethernet cable access points while the learner is on campus. The college, through collaborative effort with Stanford University, has further developed some SMILE boxes which are tools that can provide online internet connectivity without using any physical infrastructure. These tools have been useful in providing localized online internet connectivity in the remote areas where the students do their community based education (CBE). However, the study sought to provide additional functionality of learning analytics that determines learning outcomes. The portablecloud was designed to cost effectively provide online internet connectivity without using any physical infrastructure and were embedded with artificial intelligence (AI) and machine learning (ML) chip that grade e-assessments and identify patterns of students’ performance on topic and task specific e-assessments to promote success, improve retention, and streamline class enrollment and better management of e-resources. Natural language processing and geographical positioning system of e-books, e-journals and general e-content sites were the ML to define the students’ unique adaptive learning trajectories and aggregated remedial learning tasks for optimum performance. This was to enhance learning outcomes and robust public health information dissemination.