<![CDATA[The development of personalized learning technologies, such as adaptive learning systems, intelligent tutoring systems, and artificial intelligence-based learning analytics platforms, has transformed the patterns of students’ interaction with learning materials, including in mathematics education. However, the effectiveness of these technologies in improving students’ learning achievement is unlikely to operate independently, but rather depends on students’ digital competence and learning motivation in utilizing such technologies. This article aims to examine, through a literature-based approach, the role of digital competence and learning motivation in the relationship between the use of personalized learning technologies and students’ learning achievement. The study employed a narrative-thematic literature review of selected articles retrieved from Scopus, ScienceDirect, ERIC, and PubMed Central databases and published between 2019 and 2025. The findings indicate that personalized learning technologies contribute positively to students’ learning achievement when supported by adequate digital competence, particularly in the dimensions of digital evaluation and self-management, as well as learning motivation rooted in the fulfillment of basic psychological needs for autonomy, competence, and relatedness, as explained by self-determination theory. Digital competence and learning motivation are positioned as variables that both moderate and mediate the effectiveness of personalized learning technologies in relation to students’ learning achievement. This article concludes that the integration of personalized learning technologies into mathematics education should be accompanied by efforts to strengthen students’ digital literacy and the design of learning environments that support intrinsic motivation. Further empirical research is recommended to examine the proposed conceptual framework within the context of mathematics education in Indonesia.]]>
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