Challenges in Implementing Data-Driven Learning Policies
Keywords:
Data-driven learning, educational policy, data literacy, organizational challenges, technological infrastructure, localizationAbstract
This study aims to systematically examine the key challenges of implementing data-driven learning policies in educational systems and to identify the technical, human, and policy-related factors affecting their success or failure. This qualitative review employed an inductive content analysis approach. Data were collected through a systematic review of scientific literature and purposive selection of 12 high-quality articles from Scopus, ScienceDirect, Springer, and Emerald databases. Data analysis was conducted using NVivo version 14 software. Through open coding and categorization, recurring patterns were identified, leading to theoretical saturation. Three main themes emerged: technical and infrastructural challenges, human and organizational challenges, and policy and strategic challenges. Results revealed that the most significant barriers to implementing data-driven learning policies fall into three main domains. Technical challenges included lack of digital infrastructure, poor data security, and absence of standardized data frameworks. Human and organizational challenges involved low data literacy, resistance to change, lack of data-driven leadership, and weak organizational culture. Policy-level challenges encompassed lack of national strategy, limited financial and institutional support, weak data governance laws, and failure to localize global models. The findings highlight that inadequate alignment between technical, human, and policy dimensions hinders sustainable implementation. Data-driven learning represents not merely a technological innovation but a paradigm shift in educational policymaking. Its successful implementation requires secure infrastructure, data-informed leadership, capacity building in data literacy, and coherent, localized policy frameworks. The study’s outcomes provide practical insights for policymakers seeking to establish effective strategies for advancing data-driven learning.
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