Student Performance on an ELearning Platform: Mixed Method Approach Elearning is considered a leading application of digital technologies in educational systems. The aim of the paper is to explore the utilization and impact of digital technologies on an elearning platform. For this purpose, research was conducted at the Moodle learning management system. Data from the elearning platform were empirically evaluated in order to find key indicators of student performance in different courses. Student success with the elearning system was evaluated using a mixedmethod: Social Network Analysis, KMeans Clustering, and Multiple Linear Regression.  The research was conducted at the University of Novi Sad, Faculty of Technical Sciences, Serbia. The results indicate a significant relationship between the performance of students and the use of digital educational resources from the elearning platform.

DataDriven Validation of Pedagogical Model  A Case of Blended LCM Model Learning Analytics has been successful in supporting learners and instructors with large and finegrained datasets. However, its impact on practice and pedagogical theory has been limited. One of the solutions to this problem is to apply learning analytics to support evidencebased education. In this paper, we analyse the implementation of Learningcentric MOOCs (LCM), a pedagogical model, which was adopted in a blended classroom setting for an undergraduate Physics course. Extracting learning logs from the elearning platform, we applied Gaussian Mixture model to classify students and built a logistic regression model of the student performance. Our analysis demonstrated that 1) Videos (called LeD in LCM model) and Discussion Forum (called LxI) were positively related to exam scores and 2) studentu0027s access pattern of learning materials also affected exam scores. Our study is an example where learning analytics explores the dynamics of the LCM model for a blendedlearning context and provide evidence from studentsu0027 learning data. We discuss how such analysis is integrated into our technologyenhanced and evidencebased education and learning (TEEL) platform and its implications.