Victor Lee, Associate Professor of Instructional Technology and Learning Sciences at Utah State University

Data are taking on more prominent and pervasive roles in our lives, yet current forms of classroom instruction related to data still leave much room for improvement. In this talk, I will share from multiple years of design-based research with fifth and sixth-grade classrooms that have partnered with my research team where we worked to increase student comfort and familiarity with elementary statistics content required by current state standards related to data and measurement. Namely, we have engineered ways for students to devise ways to describe data, talk about measures of center, understand distributional shape, and make inferences from and about their own data personal sets. The primary strategy for enabling this has been to provide youth with wearable activity trackers and to design tools, activities, and experiences that youth can leverage to support statistical description and inference in classroom activities. Using a learning progressions assessment instrument from Lehrer, Wilson, Ayers, & Kim (2014), this talk will share some documented learning gains for students in the area of statistical reasoning. Additionally, a new framework for describing data sensemaking that emerged from this work, where “quantified self” data serve as memory prostheses that facilitate reflection on and reconstruction of experience, will be introduced and discussed. Along the way, I will also share some of the concurrent research I have done in service of this design endeavor that has sought to identify how data are already encountered in situ and are made meaningful in out-of-school settings. Challenges and future opportunities related to research and design for data fluency will be discussed.

Dr. Victor R. Lee is currently Associate Professor of Instructional Technology and Learning Sciences at Utah State University. His research involves studying and designing supports for “quantified self” in education; Maker education activities in out-of-school settings such as afterschool groups and libraries; and most recently, “unplugged” and screen-free computer science learning experiences and resources in schools. Dr. Lee is past recipient of an NSF CAREER award, a National Academy of Education/Spencer Foundation postdoctoral fellowship, and the AERA Jan Hawkins Award. His research has been funded through various sources including the National Science Foundation, the Institute of Museum and Library Services, and private foundations. Dr. Lee serves on several editorial boards, including Journal of the Learning Sciences, Cognition & Instruction, and the SAGE Encyclopedia for Out-of-School Learning. To date, he has published two books, Learning Technologies and the Body and Reconceptualizing Libraries. Additionally, he serves as an elected board member for the International Society of the Learning Sciences and in various leadership roles for the society’s conferences. Dr. Lee completed his doctorate at Northwestern University in Learning Sciences and BA and BS degrees in Mathematics and Cognitive Science with a specialization in Human-Computer Interaction at the University of California, San Diego.