E-supporting Performance Styles based on Learning Analytics for Development of Teaching Practices in Teaching Science

Abstract

This study aims to identify the effectiveness of delivering electronic supporting performance styles that are based on learning analytics for the development of teaching practices in teaching science, moreover, the Electronic and face to face supporting performance styles will deliver according to the data analytics that extracted from observations, (participating rate- page views) data from platform, therefore, to determine the effectiveness, the researchers design observation rubric based on teaching practices standard that extract from (ASTE/NSTA, AITSL) to observe teaching practices of student science teachers. Regarding the participants they were science students who enrolled in educational diplomas, researchers use the mixed method in collected data and quantitative data, furthermore, they will study a supportive program of considering data analyses to develop their teaching practices in teaching science, the results exposed that providing a supporting program that considers learning analytics, helps increase teaching practices in teaching science for student's science teachers.