Mapping professional competency for teachers' productive arts and culture of vocational school - Edhy Susatya; Fitri Nur Mahmudah; Rubiati Budhiasih (Jurnal Pendidikan Vokasi, 2022)
The purpose of the study was to analyze the educational background, the suitability of teacher competence or linearity, and map the professional competence of productive teachers in the vocational school of arts and culture. This research is descriptive qualitative research. The research stages are; collecting information related to teacher educational background, education and training data, and interviews. The research subjects were school principals, administrative heads, and teachers. The evaluation uses the discrepancy model. The research population is principals and productive teachers of the vocational schools of arts and culture. Data collection techniques using observation, interviews, and documentation. Data validation uses source triangulation and collection. Data analysis used descriptive techniques and simple mathematical analysis. The results showed that: (1) The educational background of productive teachers; dance, musical arts, theater arts, and puppetry arts 96,67% in accordance with the legal basis set by the Ministry of Education and Culture of the Republic of Indonesia; (2) The suitability of the competence or linearity of productive teachers according to learning materials in vocational high school; and (3) A map of professional competence for productive teachers; dance, musical arts, theater arts, and puppetry are 30% of teachers in the mastering category and 70% in the very mastered category. Based on passport skills, it is recommended that 8 (26,67%) teachers attend secondary level training, 9 (30%) teachers attend advanced training, and 13 (43,33%) teachers attend advanced level training. The results of the study are recommended for consideration by the relevant agencies in making policies, recruiting, improving the quality of teachers, determining teaching tasks, teaching burdens, and developing teacher coaching models.