Instructional Leadership and Data-Driven Inclusive Learning: A Bibliometric–Systematic Literature Review
DOI:
https://doi.org/10.21009/jtp.v28i2.64130Keywords:
instructional leadership, inclusive education, academic decision-making, data-driven learning, nature-based elementary schoolsAbstract
and inclusive learning in nature-based elementary schools remains limited, particularly in terms of empirical evidence and contextual application. This study aims to synthesize existing literature and identify research trends and gaps related to principals’ instructional leadership in supporting data-driven inclusive learning. This study employed a bibliometric–systematic literature review design. Data were retrieved from the Crossref database using the SEforRA search engine, yielding 9,967 initial records. Through systematic screening stages (identification, screening, eligibility, and inclusion) based on predefined criteria, 397 articles were identified as relevant, and 36 articles were included in the final analysis. The study applied bibliometric mapping (publication trends, citation, and co-word analysis) and thematic synthesis. As a literature-based study, statistical measures such as mean differences, p-values, and effect sizes were not applicable. The results indicate that instructional leadership is consistently associated with collaborative practices, systematic data use, and technology integration in inclusive learning environments. Evidence suggests that data-informed practices support improved academic decision-making, learning personalization, and student outcomes. However, persistent challenges—including limited resources, insufficient professional development, and resistance to change—remain significant barriers. Bibliometric findings also show increasing research trends, although studies focusing on nature-based elementary schools remain scarce . In conclusion, instructional leadership is an important factor in advancing data-driven inclusive learning; however, further empirical and context-specific research is needed to examine its effectiveness and long-term impact.
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