Аннотация
Professional orientation has become an essential objective of higher education because university courses are increasingly expected to prepare students for professional practice as well as academic achievement. This study examined students’ perceptions of the professional orientation of a university Probability Theory and Mathematical Statistics course using a seven-dimensional framework. Data were collected from 242 undergraduate students enrolled in the Artificial Intelligence and Data Analysis bachelor’s program at a university in Kazakhstan using a 37-item questionnaire that measured both the current and the needed levels of professional orientation. The instrument demonstrated good-to-excellent reliability and confirmatory factor analysis provided support for the proposed multidimensional measurement structure. Linear mixed-effects models, importance–performance priority analysis, and repeated-measures marginal models were used for data analysis. Students evaluated the needed level significantly higher than the current level across all seven dimensions, showing a consistent professional-orientation gap. Descriptively, Software and Digital Tools showed the largest observed gap, while Assignments and Learning Activities was classified as a curriculum-improvement priority using the sample-specific priority matrix. Students without previous statistics coursework, first-year students, and those with lower mathematical confidence reported significantly larger gaps than their counterparts. Students with previous statistical-software experience also reported greater unmet needs across all dimensions. The findings illustrate a potentially useful multidimensional framework for evaluating professionally oriented statistics courses and offer practical direction for curriculum redesign through stronger addition of authentic learning activities, software-supported data analysis, and professionally relevant applications.