Teacher Readiness Level In Implementing The Deep Learning Mathematics Approach To Senior High School Students In Batu City - Kusnia Nur Hadiyah; Surahmat Surahmat; Sikky El Walida (Universitas Wiralodra, 2025)
This study aims to measure the readiness of high school mathematics teachers in Batu City to implement Deep Learning in the context of the Industry 4.0 Era. The research employed a quantitative descriptive survey approach. A sample of 60 teachers was selected using purposive sampling from active teachers in public and private high schools in Batu City. Data were collected through a closed questionnaire referring to four core teacher competencies: pedagogical, personality, professional, and social. Data analysis was conducted using descriptive statistics in the form of averages, percentages, and readiness level categories. The results of the study showed that the majority of teachers (63.33%) were in the Ready category in the pedagogical aspect, 32.5% were Less Ready, and 4.17% were Very Ready. In the personality aspect, 37.22% of teachers were Ready, 37.22% Less Ready, and 25.56% Very Ready. In the professional aspect, 51.11% of teachers were Less Ready, 28.33% Very Ready, and 20.56% Ready. In the social aspect, 51.67% of teachers were Less Ready, 25.83% Very Ready, and 22.50% Ready. These findings indicate that successful implementation of Deep Learning requires strengthening teacher competencies through ongoing training, learning communities, and school policy support that is adaptive to developments in the digital era.