<![CDATA[Background: Generative AI search tools has transformed how researcher access, interpret, and synthesize academic literature. For early-career scholars, these technologies offer potential support in addressing limitations related to research experience, particularly in literature comprehension and conceptual framework development. However, empirical studies explaining how and through what internal mechanisms generative AI supports educational research remain limited, especially those that account for psychological and cognitive mediating factors.Aims: This study aims to examine the role of generative AI search tools in enhancing educational research productivity among early-career scholars by analyzing the mediating roles of academic self-confidence, literature comprehension, and research self-regulation.Methods: A mediation-based multi-method approach with an explanatory sequential design was employed. Quantitative data were collected through a Likert-scale survey and analyzed using mediation modeling, followed by qualitative data collected through semi-structured interviews and analyzed thematically to elaborate and contextualize the quantitative findings.Result: The findings indicate that the use of generative AI search tools is positively associated with educational research productivity. This relationship is primarily mediated by literature comprehension, academic self-confidence, and research self-regulation, with literature comprehension emerging as the strongest mediating pathway. Qualitative findings further reveal that generative AI functions as an intellectual companion that supports understanding of complex scholarly literature, strengthens research independence, and facilitates more effective management of the research process.Conclusion: The study demonstrates that the contribution of generative AI to educational research extends beyond technical assistance, operating through researchers’ internal cognitive and psychological processes. By adopting a mediation-based perspective, this study provides a more nuanced explanation of how generative AI search tools support early-career scholars’ research productivity and contributes to a deeper theoretical understanding of AI-supported educational research practices.]]>
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