Search Results


This course provides graduate students with hands-on experiences that model data-driven decision making for educational success in today's classroom. Students will learn how to create valid and reliable assessments; interpret standardized test data; build data models that identify student, classroom, program, and school needs; and in general, to systematically enhance educational decision making from a base of carefully collected information. Graduate students will also explore data collection and analysis strategies associated with technologies such as cloud computing, tablet computers, and smart phones. In addition, they will experience data-driven decision-making models that can be integrated into student lessons to not only teach more effectively with data-driven decisions, but also to help teach students about data-driven decision-making. The course will use real data sets and cases, in interesting, hands on and technology-rich activities, to help educators learn how to find the "educational story" represented by a set of carefully collected data points. (Cross-listed with STEM 8050).

Prerequisite(s): Graduate standing.