Professional Development Paths and Teacher Competence Enhancement of Vocational School Teachers under the Integration of Intelligent Technology

• Published in: Applied mathematics and nonlinear sciences Vol. 10; no. 1
• Main Author: Zhou, Lingyu
• Format: Journal Article
• Language: English
• Published: Beirut Sciendo 01.01.2025; De Gruyter Poland
• Subjects: 97B20; Educational technology; Emotion recognition model; Facial expression recognition; Factor analysis; Intelligent technology; Professional development; Teacher competencies; Teacher professional development; Teachers; Teaching
• ISSN: 2444-8656; 2444-8656
• DOI: 10.2478/amns-2025-0212

As an advanced technological tool that triggers great changes in the times, intelligent technology is promoting great changes in vocational education. With the purpose of exploring the path of intelligent technology to boost teachers’ professional development and the countermeasures to improve teachers’ competence, the article specifies the path of teachers’ professional development from five levels, namely, teaching environment, teaching reform, teachers’ competence, education balance and teaching evaluation. The specific application of intelligent technology in teachers’ professional development is explored through the construction and application case study of students’ classroom emotion recognition model. The model consists of two components, facial expression recognition and behavioral gesture recognition, and is integrated at the decision-making level of teaching and learning, which can help teachers to obtain teaching feedback and adjust their teaching strategies, and the neutral emotions (23%) and happy emotions (22%) of the sample students accounted for the most in the classroom, and the whole presented a smoother learning state. Exploratory factor analysis obtained five dimensions of teacher ability characteristic elements: research and professional development ability (19.98%), personal traits (20.56%), professional teaching ability (20.93%), professional quality (18.39%) and professional practice ability (20.14%), which provides a reference to the countermeasures for teacher ability improvement under the integration of intelligent technology.