<![CDATA[This study investigates undergraduate students’ understanding of grouped data analysis using SPSS within an interdisciplinary framework integrating statistics education, computer science, and educational psychology. Employing a descriptive qualitative design, the study involved 18 computer science students who had completed coursework in grouped data computation. Data were collected through semi-structured interviews, classroom observations, and document analysis, and analyzed using iterative coding and thematic categorization. The findings reveal a gradient of understanding: 55.56% of students demonstrated high-level conceptual–procedural integration, 33.33% exhibited moderate understanding characterized by procedural competence with partial conceptual articulation, and 11.11% showed limited conceptual and interpretative ability. The results indicate that operational proficiency in statistical software does not automatically ensure statistical literacy. Students with higher understanding were able to justify class interval construction, interpret frequency distributions, and contextualize SPSS outputs within research applications. Conversely, lower-level understanding was associated with procedural dependency and limited interpretative reasoning. These findings reinforce contemporary perspectives emphasizing that technology-enhanced learning must integrate conceptual explanation, computational execution, and reflective interpretation. The study contributes to the discourse on interdisciplinary statistical education by highlighting the importance of aligning computational fluency with conceptual reasoning in higher education contexts. Strengthening pedagogical scaffolding in software-supported statistics instruction may enhance students’ readiness for quantitative research and improve the quality of undergraduate academic work.]]>
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