Collaboration-Based Academic Supervision Model with Peer Evaluation Approach to Improve Pedagogical Competence and Quality of School Performance: The Role of Principal's Motivation as Moderation Variables - Singerin, Sarlota (Universitas Pendidikan Ganesha, 2021)
Teaching skills are one of the skills that must be possessed by a teacher. Whether or not the pedagogical competence possessed by teachers can be seen from the quality of school performance. Supervision still tends to lead to inspection. So far, the implementation of academic supervision is considered effective. In order for the Academic Supervision to provide objective and detailed results, collaborative self-evaluation is carried out, namely peer evaluation to find teacher strengths that need to be maintained and deficiencies that must be corrected. This study aims to determine the effect of collaboration-based Academic Supervision model with Peer Evaluation Approach to Improve Pedagogical Competence and Quality of School Performance: The Role of Principal's Motivation as Moderation Variable. This research is a quantitative study with numerical data analyzed using the Structural Equation Model (SEM) assisted by the Smart PLS application. The results showed that Academic Supervision has an effect on Pedagogical Competence with a P-Value of 0.000 (p <0.05). Academic Supervision affects the Quality of Performance with a P value of 0.000 (p <0.05). motivation is able to moderate positively pedagogical competence with a P value of 0.032 (p <0.05). Motivation is not able to moderate supervision of the quality of performance with a P value of 0.138 (p> 0.05). Supervision is able to explain the Pedagogical Competence (Y1) variable of 69.4%. Supervision is able to explain the Performance Quality variable (Y2) of 40.1%. The principal should be able to periodically monitor the learning carried out by the teacher in the classroom, so that the principal knows the problems faced by the teacher in learning. Researchers who want to research further on this topic can use other variables and a wider sample.