Claim Missing Document
Check
Articles

Found 32 Documents
Search

How Transformational Leadership and Organizational Learning Impact Organizational Citizenship Behavior: A Meta-Analysis Usep Kasman; Merry Lapasau; Oom Rohmah; Bambang Sumadyo
Jurnal Penelitian Pendidikan IPA Vol 11 No 9 (2025): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i9.12838

Abstract

Organizational Citizenship Behavior (OCB) plays a crucial role in enhancing school effectiveness, yet research on how transformational leadership and organizational learning influence teachers’ OCB has produced mixed results. To address this gap, this study conducted a quantitative meta-analysis to integrate empirical evidence and measure the strength of these relationships. A total of 35 studies published between 2020 and 2025 were systematically collected from Scopus, SINTA, and Google Scholar and analyzed using JASP 0.14.1 with a random-effects model and correlation effect size (r). The analysis revealed that transformational leadership demonstrated a stronger positive association with teachers’ OCB (r = 0.515, p < 0.01) compared to organizational learning (r = 0.387, p < 0.01). Tests of heterogeneity indicated a moderate level of variation across studies, and no signs of publication bias were detected. These results highlight the critical need to foster transformational leadership and nurture a culture of learning in schools as strategic efforts to promote OCB among teachers.
A meta-analysis of computational thinking and artificial intelligence in education: impacts on students' problem-solving skills Asmaul Husnah; Widodo Widodo; Merry Lapasau; Hasbullah Hasbullah; Oom Rohmah
Jurnal Konseling dan Pendidikan Vol. 13 No. 4 (2025): JKP
Publisher : Indonesian Institute for Counseling, Education and Therapy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/1187400

Abstract

Despite the rapid expansion of research on computational thinking (CT) and artificial intelligence (AI) in education, evidence on their comparative effects on students' problem-solving skills remains fragmented and inconsistent, underscoring the need for a systematic quantitative synthesis. This study conducted a systematic meta-analysis to examine and compare the effects of CT-based and AI-based instructional interventions on students' problem-solving performance. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, twenty-four empirical studies published between 2017 and 2025 were analyzed using a three-level random-effects meta-analytic model to account for within-study dependencies and heterogeneity. The results showed that CT-based instruction produced a statistically significant and consistent positive effect on problem-solving skills (pooled effect size = 0.30, p < 0.001), indicating high stability across educational contexts. AI-based instructional interventions yielded a larger pooled effect size (0.46, p < 0.001), although greater variability was observed across instructional designs and contexts. These findings suggest that CT strengthens analytical reasoning and systematic problem-solving processes, whereas AI enhances adaptive and reflective thinking through personalized learning support. The study contributes theoretically by clarifying the complementary roles of CT and AI in problem-solving development and practically by providing evidence-based guidance for designing effective technology-enhanced learning environments.