Principal Investigator: Florence Sullivan
CoPrincipal Investigator(s): W Richards Adrion
Organization: University of Massachusetts Amherst
Research activities that will be undertaken in this project are:(1) the development of theoretically-based, microgenetic learning analytic protocols aimed at understanding middle school student learning in a robotics setting as well as the development of theoretically-based, sentiment analysis protocols aimed at understanding the salience of stereotype threat for underrepresented students studying in a robotics context; (2) pilot testing these protocols on an existing data set; (3) refining and improving the protocols based on the results of the pilot test; and (4) conducting original research on the development of computational thinking in underrepresented middle school students studying in a robotics context, including examining the salience of stereotype threat on student activity.
Microgenetic analysis refers to the study of learning changes where:
1. Observations span the period of rapidly changing competency
2. Within the this period the density of observations is high relative to the rate of change
3. Observations are analyzed intensively
This proposal combines microgenetic analysis with computer science based learning analytics. The computer science based learning analytics take computer captured data and analyzes and mines that data for understanding of student learning. It is frequently used in intelligent tutoring systems and Massive Open Online Courses. In such cases, every keystroke is captured and the learning analytics is about making sense of those captured keystrokes.
The goal of this FIRE proposal is to increase the diversity of individuals who enter the field of computing by engaging in research on the development of computational thinking in underrepresented middle school students as they interact in a robotics environment. This research will include an examination of the salience of stereotype threat in an all girl robotics study setting. The PIs will achieve this project goal through the creation of a new research method that combines microgenetic analysis techniques derived from the field of developmental psychology with learning analytic techniques, derived from the field of computer science. The PIs term this new method Microgenetic Learning Analytics.