Learning analytics focuses on using existing accumulated learning data through analysis related techniques to provide appropriate information to learners and facilitating learners to adjust their learning strategies (personalization and adaptation) in improving learning effectiveness. Through learning analytics, activities of teaching, learning, and management processes will be significantly changed. Although learning analytics has been considered one of the six critical trends (ebook, mobile learning, augmented reality, game-based learning, natural user interface, and learning analytics) of high education in the near future, there are only few studies focusing on exploring learning analytics related issues. To address this void, this thesis aims for analyzing and designing a personalized mobile learning analytics system that is a mobile application prototyping system developed by incorporating concepts of learning analytics and mobile learning. User requirements of the prototyping system are collected by database analysis (LMS platform), focus groups (users of mobile learning), and expert interviews (experts and practitioners in e-learning domain). Those collected requirements have been translated into system functionalities and then they have been appropriately implemented through adequate system development tools. Finally, the implemented prototyping system has been tested and validated by experts and practitioners in e-learning domain. Therefore, this study has significant contributions on conducting an in-depth system analysis and design relating to mobile learning with learning analytics and validating the feasibility of learning analytics by the prototyping approach. We suggest that academics and practitioners can conduct more in-depth research on investigating learning analytics related issues based on the findings of this study.