In addition to quantitative accuracy, it is critical for learning analytics to consider design principles and methods of persuasion that convince educational leaders and students to do things differently. This requires a complementary approach that includes quantitative techniques, qualitative analysis, narrative, and design thinking.
John is the Analytics and Research Director at Blackboard. In this position, he leads the data science efforts conducting research into the use of Blackboard’s teaching and learning solutions. He also manages the integration of these results into analytics features within existing applications and creation of dedicated analytics solutions. His research focuses on interactions of students and faculty with educational technology applications, the fit/gap between product design and use, and the educational outcomes resulting from those interactions. John holds a Doctorate in Educational Leadership from UC Davis and a Master’s Degree in Sociocultural Anthropology from UC Davis.
Prior to joining Blackboard in 2014, John managed large-scale distributed educational technology projects for the California State University, California Community Colleges, and NEES, Inc., a 15-university NSF-sponsored research consortium. John is an applied researcher with published studies in Learning Analytics and MOOC effectiveness research. He currently co-Chairs the IMS Privacy Task Force and is an active member of the Society for Learning Analytics Research.
Findings from two research studies at scale reveal the implications of learning analytics for designing courses in learning management systems to enhance student success.
Everyone from government agencies to mainstream press are looking for improvements in areas that typically fall under the umbrella of “student success.
ECAR Analytics Working Group
WRC06 Program Committee