Blended learning in Computer Science teacher training

Abstract

This research aims to contribute to the discourse on blended learning approaches in Computer Science teacher training programs in Ukraine. The objectives are twofold: 1) to determine the appropriate Ukrainian scientific term for “blended learning” given Ukraine’s ongoing European integration, and 2) to provide a comprehensive definition of “blended learning” by synthesizing various academic conceptualizations. The object of study is the concept of “blended learning” itself and how it can be applied to train future Computer Science teachers with the necessary digital competencies. The purpose is to support the professional development of educators so that they can effectively prepare students for success in the digital age. The methods employed include linguistic analysis of how “blended learning” is translated across European languages and an extensive literature review to synthesize definitions from prior research into a unified conceptual understanding. The key results are: 1) the proposed Ukrainian term “kombinovane navchannia” reflects an adaptive combination of learning modes; 2) a comprehensive definition views blended learning as an adaptive, pedagogically balanced integration of face-to-face, online, formal, informal, individual and collaborative learning facilitated by intelligent ICTs like machine learning, big data analytics, virtual reality, and AI tutoring systems. The findings highlight how blended learning provides access to rich educational data that can be processed by intelligent technologies to enable personalized, immersive experiences and predictive learning analytics. Promising future dimensions across philosophical, psychophysiological, sociological, organizational, technological and synergistic factors are discussed.