This course is designed to introduce graduate students to the application of big data in educational context, including the epistemological underpinnings of data science, in-depth knowledge of data science theories in education, and the methodological nuts-and-bolts in conducting educational evaluation.
This course is to introduce prospective data scientists to data-driven approach in educational administration. Emphasis is placed on the use and re-purposing of data to enhance governance and efficiency of school education as well as to formulate or update relevant policies and administrative measures emerged in response to changing social development or enactment of laws or rules.
This course is designed to improve instruction using data. In the digital age, a wealth of data is available for teaching and learning purposes. This course aims to broaden students with the initiatives undertaken to make use of data-driven approaches that can improve the learning process. Students are expected to make use of tools to mine a wide range of learning patterns and behaviors so as to enhance the quality of instruction. They will study, experience and review the theory and practice of existing applications of big data in order to make informed judgment about their educational duties.
This course is designed to be part of the emerging field of quantitative/computational social sciences. The goal is to equip students with data science approach to answer social science questions. This course will introduce principles and skills of quantitative social science research. Students will receive an update of the major tools and ideas used in the field and be guided toward their first data-driven research project throughout this course.