Algorithm Design and Experimental Research on Achievement Analysis of Output Oriented Course Objectives, Using Digital “Signal Processing A” as a Case Study

Abstract

In the context of the deepening implementation of the principles of Output-oriented Education (OBE) in engineering education, the analysis of course goal achievement plays a crucial role in enhancing teaching quality. Aiming at the shortcomings of traditional analytical methods in modeling assessment indicators and diagnosing teaching improvements, this study constructs an analysis system for course goal achievement that integrates the Analytic Hierarchy Process (AHP), weighted comprehensive evaluation models, and data visualization techniques. This research scientifically quantifies the weights of assessment indicators by using AHP. It establishes a nonlinear weighted comprehensive evaluation model to depict the relationships among dimensions such as "theoretical knowledge" and "practical skills", breaking through the independence assumption of traditional linear models. Additionally, it designs a structured processing workflow for multi-source performance data. By integrating multidimensional data from regular performance, final assessments, and extension training according to their weights, it forms a quantitative calculation framework for the achievement of sub-goals and overall goals. Moreover, a data visualization module is developed to intuitively present the achievement status of each goal and individual student differences through bar charts, scatter plots, etc. Taking the teaching data of 116 students in the course "Digital Signal Processing A" at North China University of Science and Technology as a sample, the effectiveness of this system in quantitatively evaluating Course Goal 1 (achievement degree of 0.73), Goal 2 (achievement degree of 0.73), and Goal 3 (achievement degree of 0.72) has been verified. The relevant results provide data support for optimizing teaching content (such as enhancing the integration of theory and practice) and personalized guidance (such as focusing on students with weaker performance). Practice shows that the system provides a replicable technical solution for the assessment of course goal achievement in colleges and universities through the closed-loop design of "indicator weighting--achievement calculation--visual feedback". Its data-driven precision diagnosis mechanism can effectively contribute to the implementation of OBE and the continuous improvement goal under the concept of "student-centered".