Abstract

Educational technology (EdTech) systems now play a central role in teaching, learning, assessment, and institutional management across higher education and professional training contexts. Universities and training providers increasingly rely on learning management systems, digital assessment platforms, and analytics-enabled tools to support pedagogical innovation and operational efficiency. However, despite sustained financial and institutional investment, many EdTech initiatives fail to achieve their intended educational impact. These shortcomings are frequently linked not to technological limitations, but to suboptimal software development processes, weak alignment between developers and educational stakeholders, and the underutilization of empirical feedback from system use and learning data. This paper proposes a data-driven approach to optimizing software development processes for educational technology systems, drawing on principles from software process improvement (SPI), agile and iterative development, and analytics-informed decision- making. The proposed approach emphasizes the systematic integration of development analytics, system usage data, and learning analytics across the software lifecycle from requirements elicitation and design to deployment, evaluation, and continuous improvement. By embedding evidence-based feedback loops into development practices, the framework aims to improve development efficiency, enhance software quality, and ensure stronger pedagogical alignment with teaching and learning objectives. The paper advances a conceptual framework that connects software engineering practices with educational data ecosystems, addressing a critical disconnect between learning analytics research and software process optimization. By positioning learning data as an active input into software process decisions, the study contributes to both software engineering and educational technology literature. The proposed framework offers practical implications for EdTech developers, instructional designers, and higher education institutions seeking to deliver scalable, responsive, and pedagogically effective digital learning systems.

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