Article: AI-driven framework for enhancing vocational college teacher development: a natural language processing approach to professional growth and skill enhancement Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.24 pp.29 - 48 Abstract: The professional development of vocational college teachers is crucial for enhancing teaching quality and student outcomes. This paper presents an AI-driven framework using natural language processing (NLP) to support vocational educators' professional growth. The framework evaluates teaching effectiveness, identifies skill gaps, and provides customised feedback for continuous improvement. NLP techniques were applied to analyse the teaching content, feedback, and communication patterns of 100 teachers and 2,000 students over a 12-month period. The framework's success was evaluated using important measures: 1) teaching performance improved by 30% in evaluation accuracy; 2) student engagement increased by 20% in satisfaction with a 2% error margin; 3) skills in specific subjects grew by 35%; 4) feedback delivery became 45% faster. Results indicate substantial improvements in teaching performance, student satisfaction, and academic outcomes, along with optimal feedback delivery. This study demonstrates the potential for AI-driven NLP frameworks to revolutionise vocational education. Inderscience Publishers - linking academia, business and industry through research

Title: AI-driven framework for enhancing vocational college teacher development: a natural language processing approach to professional growth and skill enhancement

Authors: Xiao Yang; Lin Wang

Addresses: Vocational Education, Jinan Information Engineering School, 250022, Shandong, China ' Meterage Shandong Institute of Metrology, Shandong, 250000, China

Abstract: The professional development of vocational college teachers is crucial for enhancing teaching quality and student outcomes. This paper presents an AI-driven framework using natural language processing (NLP) to support vocational educators' professional growth. The framework evaluates teaching effectiveness, identifies skill gaps, and provides customised feedback for continuous improvement. NLP techniques were applied to analyse the teaching content, feedback, and communication patterns of 100 teachers and 2,000 students over a 12-month period. The framework's success was evaluated using important measures: 1) teaching performance improved by 30% in evaluation accuracy; 2) student engagement increased by 20% in satisfaction with a 2% error margin; 3) skills in specific subjects grew by 35%; 4) feedback delivery became 45% faster. Results indicate substantial improvements in teaching performance, student satisfaction, and academic outcomes, along with optimal feedback delivery. This study demonstrates the potential for AI-driven NLP frameworks to revolutionise vocational education.

Keywords: artificial intelligence; vocational education; teacher development; natural language processing; skill enhancement.

DOI: 10.1504/IJICT.2025.147134

International Journal of Information and Communication Technology, 2025 Vol.26 No.24, pp.29 - 48

Received: 07 Apr 2025
Accepted: 21 May 2025
Published online: 10 Jul 2025 *

Title: AI-driven framework for enhancing vocational college teacher development: a natural language processing approach to professional growth and skill enhancement

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