Construction and Design of an Academic Ability Evaluation System for Vocational College Students Fused K-means Algorithm

• Published in: 2024 7th International Conference on Computer Information Science and Application Technology (CISAT) pp. 701 - 705
• Main Author: Bu, Xing
• Format: Conference Proceeding
• Language: English
• Published: IEEE 12.07.2024
• Subjects: Academic ability evaluation; Big Data; Computational modeling; Education; Exploratory factor analysis; Indexes; Indicator system; Information science; K-means clustering; Reliability; Simulation; Technological innovation; Training
• DOI: 10.1109/CISAT62382.2024.10695310

The existing academic ability evaluation standards for vocational college students overly focus on commonalities while neglecting individual differences among students, and place too much emphasis on teaching outcomes while ignoring the teaching process. To effectively evaluate the individual differences and academic abilities exhibited by vocational college students during online learning, this paper constructs an academic ability evaluation index system, uses exploratory factor analysis to condense the indicator items, and further divides and labels learners through the k-means algorithm, creating learner portraits. Taking the learning situation of practical training platform courses for students majoring in big data and accounting at a certain college as the experimental subject, the simulation results show that the constructed academic ability evaluation system includes 5 dimensions and 16 specific measurement indicators, demonstrating good reliability and validity. After clustering, students of different categories show significant differences in evaluations across the 5 dimensions, and groups with lower multidimensional evaluations can be effectively identified. Subsequently, precise teaching intervention strategies can be designed for the target groups to improve teaching quality.