Stephanie Teasley, Research Professor at the School of Information, and Director of the Learning Education and Design Lab (https://www.si.umich.edu/people/stephanie-teasley) gives the lecture "Learning Analytics: Data Science for Education" at the Women in Data Science Conference hosted by MIDAS (http://midas.umich.edu/).
Dr. Teasley’s research has focused on issues of collaboration and learning, looking specifically at how sociotechnical systems can be used to support effective collaborative processes and successful learning outcomes. As Director of the LED lab, she leads learning analytics-based research to investigate how instructional technologies and digital media are used to innovate teaching, learning, and collaboration. The LED Lab is committed to providing a significant contribution to scholarship about learning at Michigan and in the broader field as well, by building an empirical evidentiary base for the design and support of technology rich learning environments.
For more lectures on demand, visit the Alumni Engagement website:
http://www.engin.umich.edu/college/info/alumni/professional-dev/lectures
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Women in Data Science | Stephanie Teasley
Stephanie Teasley, Research Professor at the School of Information, and Director of the Learning Education and Design Lab (https://www.si.umich.edu/people/stephanie-teasley) gives the lecture "Learning Analytics: Data Science for Education" at the Women in Data Science Conference hosted by MIDAS (http://midas.umich.edu/).
Dr. Teasley’s research has focused on issues of collaboration and learning, looking specifically at how sociotechnical systems can be used to support effective collaborative processes and successful learning outcomes. As Director of the LED lab, she leads learning analytics-based research to investigate how instructional technologies and digital media are used to innovate teaching, learning, and collaboration. The LED Lab is committed to providing a significant contribution to scholarship about learning at Michigan and in the broader field as well, by building an empirical evidentiary base for the design and support of technology rich learning environments.
For more lectures on demand, visit the Alumni Engagement website:
http://www.engin.umich.edu/college/info/alumni/professional-dev/lectures
