Design and Practice of Integrating Industry Cases into the Teaching of Big Data Courses in Higher Vocational Education

Abstract

To address the weak connection between technical knowledge and application contexts in big data courses at higher vocational colleges, as well as students' limited ability to analyze continuous data and complex operations as a whole, a vessel navigation data monitoring case was adapted for teaching and incorporated into the course Big Data Analysis and Development. Tasks involving position determination, trajectory storage, stateful processing, and the presentation of status information guided students through requirements interpretation, solution comparison, program implementation, debugging and refinement, and improvement of project outcomes. In classroom implementation, the adapted industry case provided a constrained application context for technical learning and prompted students to make technical choices based on timeliness, data continuity, and programming conventions. Through teaching activities covering single-point position determination and continuous trajectory analysis, comparison between offline and stream processing approaches, program implementation, and result presentation, this paper summarizes methods for adapting industry cases for teaching, organizing progressive tasks, assessing process evidence, and defining instructional boundaries. The study provides a reference for reforming practice-oriented big data courses in higher vocational education.