Current Status and Dilemmas of Artificial Intelligence Usage by Vocational College Teachers in Henan: Evidence From Henan Vocational and Technical College

Abstract

Background and Aim: Artificial intelligence fully empowers the digital transformation of vocational education. The AI literacy and teaching technology adoption level of vocational college teachers directly determine the quality of skills training. Existing domestic empirical studies mostly focus on eastern institutions, lacking micro-quantitative research on the micro-level of public vocational colleges in the central region. This study fills the gap in regional research, identifies the stratification characteristics of vocational college teachers' AI literacy, and quantitatively analyzes the multiple influencing factors that constrain teachers' adoption of AI teaching behaviors. This paper takes Henan Vocational and Technical College as the observation sample, combined with the practical cases of many colleges in Henan Province, and analyzes the real situation of vocational college teachers in AI application. This study aims to explore the cognitive level and current knowledge and skills status of vocational college teachers regarding artificial intelligence technology and analyze the key factors that affect their improvement of AI capabilities.

Materials and Methods: This study adopted a mixed-methods research design combining questionnaire surveys and focus group interviews. First, to ensure the rigor of research data, participating teachers were selected across diverse majors, teaching years and genders. Henan Vocational and Technical College had a total teaching staff of 800 individuals. Using the Yamane sampling formula with a margin of error controlled within 5%, the calculated required sample size was 267 participants, and a total of 276 valid questionnaires were collected in practice. A self-designed Questionnaire on the Current Status and Dilemmas of Artificial Intelligence Application among Higher Vocational Teachers was adopted in this research. Both its content validity and reliability coefficients exceeded 0.85 after inspection. For the focus group, five participants were recruited, comprising three frontline teachers from the target college covering industrial and business majors, one expert in educational technology, and one specialist in AI educational application. Descriptive statistics including means and standard deviations as well as perceptual grading analysis were applied to analyze questionnaire data. Findings from the focus group discussions were further used to supplement and interpret the quantitative results of the questionnaire.