A comprehensive conceptual framework is developed and described for evolving recommender‐driven online learning systems (ROLS). This framework describes how such systems can support students, course authors, course instructors, systems administrators, and policy makers in developing and using these ROLS. The design science information systems research approach was used to develop the framework. The ROLS framework incorporates both the cognitive and situative perspectives of the constructivist paradigm of learning. Research propositions are developed to highlight new research opportunities for these systems. The framework demonstrates how various components of an evolving ROLS can be integrated to provide potential benefits for all users.

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Recommender‐driven online learning systems (ROLS) are at the forefront of new computer‐based learning. They incorporate machine learning to allow learning‐by‐doing, generating personalized recommendations in the process. This article describes the evaluations of a new type of online learning systems, ROLS. This evaluation was carried out in three phases using a design science research approach. In Phase I, building the ROLS prototype validated the conceptual framework used. In Phase II, building an instantiation of ROLS to teach Structured Query Language (SQL), SQL‐with‐Ease, validated the ROLS prototype. In Phase III, a laboratory experiment evaluated learning outcomes from using SQL‐with‐Ease compared with two other traditional forms of learning. A set of qualitative interviews carried out with learners soon after using the system confirmed that the system was effective. They indicated that more work on fine‐tuning recommendations generated by the system could further improve learner satisfaction. The key implication for practitioners is that ROLS have the potential to improve learning outcomes significantly. Implications for researchers are that evaluations of ROLS, which include formative and summative evaluations, are essential to improve their performance and that developing innovative approaches to evaluation can advance these learning technologies.

Big data is having a positive impact in almost every sphere of life, such as in military intelligence, space science, aviation, banking, and health. Big data is a growing force in healthcare. Even though healthcare systems in the developed world are recording some breakthroughs due to the application of big data, it is important to research the impact of big data in developing regions of the world, such as Africa. Healthcare systems in Africa are, in relative terms, behind the rest of the world. Platforms and technologies used to amass big data such as the Internet and mobile phones are already in use in Africa, thereby making big data applications to be emerging. Hence, the key research question we address is whether big data applications can improve healthcare in Africa especially during epidemics and through the public health system. In this study, a literature review is carried out, firstly to present cases of big data applications in healthcare in Africa, and secondly, to explore potential ethical challenges of such applications. This review will provide an update on the application of big data in the health sector in Africa that can be useful for future researchers and health care practitioners in Africa.

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