Big Data Analytics in Education: A Systematic Review of Its Impact on Teaching Strategies and Learning Experiences
Keywords:
Big Data Analytics, Systematic Review, Teaching Strategies, Learning ExperiencesAbstract
The rapid growth of digital technologies in education has generated vast amounts of data, offering new opportunities to enhance teaching and learning processes. This study aims to systematically review the impact of big data analytics on teaching strategies and learning experiences in educational contexts. Using a systematic literature review approach, relevant articles published in reputable international journals over the past decade were identified, screened, and analyzed based on predefined inclusion and exclusion criteria. The findings reveal that big data analytics plays a significant role in transforming teaching strategies by enabling data-driven decision-making, personalized instruction, and adaptive learning environments. Educators are increasingly utilizing learning analytics to monitor student performance, identify learning patterns, and provide timely interventions. Furthermore, the integration of big data analytics enhances learning experiences by promoting student engagement, improving learning outcomes, and supporting flexible and interactive learning environments. However, the study also highlights several challenges, including data privacy concerns, lack of technical expertise among educators, and limited infrastructure in certain educational settings. These challenges indicate the need for comprehensive policies and capacity-building initiatives to ensure effective implementation. In conclusion, big data analytics has substantial potential to reshape educational practices, although its successful adoption requires careful consideration of ethical, technical, and institutional factors. This study contributes to the existing literature by providing a comprehensive overview of current trends, opportunities, and challenges in the use of big data analytics in education.
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