Networks and Innovation Capacity: Assessing the role of social relations and structure in technology adoption and adaptation for teaching in Nigeria, Kenya and the Republic of Benin

This study contributes to a better understanding of how the network perspective to innovation presents a relevant framework for explaining the adoption of innovation in developing countries. The examination of the phenomenon was done by focusing on the education sector and the case of science teachers in Nigeria, Kenya and the Republic of Benin. The four-phased longitudinal study assessed the influence of social elations and structure on the decision to adopt or reject the Go-lab Ecosystem (a digital STEM Laboratory) and Inquiry-based Learning by the science teachers. The theoretical framework for the study emanates from the intersection of three concepts which are grounded in the innovation systems theory; Technology Innovation System (TIS), Sectoral Innovation System (SIS), and Regional Innovation System (RIS).

This study used a mixed-method approach to explore network constructs that are important for analysing how social structure and relations influence the adoption of innovation. The method allowed for the assessment of relational and structural network data, time of adoption and usage patterns in explaining how the pattern of interactions and structural characteristics of the social system in the 9 participating schools influence the decision of the 38 STEM teachers to accept or reject the innovation. The approach revealed how a set of prior conditions including perceived newness and innovativeness of the innovation, and previous practice influenced the adoption process.

One of the significant contributions of this study is the manifestation of the network perspective through the innovation ecosystem concept. The framework presents a path to assessing how interactions among actors in a network are coordinated and the contribution of informal actors to the value exchange and creation within the network. In addition, this focus on network dynamics allows for assessing how practices and institutions are formed or shaped, thereby providing a more relevant framework for assessing innovation capacity.