<![CDATA[The increasing demand for data-driven decision-making requires engineering graduates to possess strong statistical data analytics competencies. However, statistics learning in vocational higher education often provides limited opportunities for students to develop analytical competencies through authentic, AI-supported learning experiences. This study investigated the development of students' statistical data analytics competencies through AI-assisted interactive dashboard development using Tableau. A convergent mixed-methods design was employed involving undergraduate students enrolled in a Statistics course in the Informatics Engineering Department of Politeknik Negeri Semarang, Indonesia. Quantitative data were collected through competency-based assessment of students' interactive dashboard projects, while qualitative data were obtained through artifact analysis of three sequential authentic learning artifacts: AI-assisted authentic dataset development, interactive dashboard development, and AI-assisted analytical presentation. The findings indicate that students achieved proficient to advanced competency levels across technical, analytical, and professional competency dimensions. Qualitative findings further revealed that the three learning artifacts formed a progressive competency pathway, enabling students to move from knowing the data, to representing the data, and ultimately to reasoning and communicating with the data. These findings demonstrate that AI-assisted project-based learning provides an effective instructional approach for strengthening statistical data analytics competencies in engineering vocational higher education]]>
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