Development of a Model for Data-Driven Decision Making: Critical Skills for School Leaders

Abstract

Data may equip school leaders with the information they need to make crucial changes that will enhance the education system in the future although the usage of data may not be able to resolve every issue. However, proper data utilization can advise the right conclusion. Therefore, this study aims to design and develop an experiential narrative-based model for school leaders in data-driven decision-making (DDDM). The model has been designed and developed using the Design and Development Research (DDR) approach, which involves three phases: the need analysis phase, the design and development phase, and the usability evaluation phase. However, the researcher only focuses on this paper in the second phase. The design and development process began with a literature study, followed by approval and consensus from a 9-expert panel. The model was designed using the Nominal Group Technique (NGT) technique and developed using the Interpretive Structural Modelling (ISM) method. The design and development phase revealed that 13 DDDM competency components had been generated through the expert panel's opinions and agreement. Overall, based on the experiential narrative of the experts in this study, the model is appropriate for usage and implementation. As a result, the empirically established and verified model has the potential to enhance school leaders' knowledge, skills, and attitudes toward data-driven decision-making.