Joshua M. Rosenberg (PhD, Michigan State University) is an Assistant Professor of STEM Education at the University of Tennessee, Knoxville. His research focuses on how learners think of and with data, particularly in science education settings. Dr. Rosenberg tries to understand how practices such as creating, representing, and modeling data create new opportunities for learning how to use data to pose and answer questions about scientific phenomena. In addition to how learners think of and with data,
Dr. Rosenberg is also interested in student engagement across a range of STEM learning environments and the use of technology in education, particularly for teacher professional development. As a part of this work, Dr. Rosenberg makes use of quantitative methods, such as multi-level models for analyzing data collected through the experience sampling method, and newer approaches, such as social network analysis to analyze teachers’ conversations on social media. Dr. Rosenberg’s research has been published in journals such as the Journal of Research on Science Teaching, the Journal of Youth and Adolescence and the Journal of Technology and Teacher Education.
This page contains information about my research as well as information about ongoing research projects.
Publications and Other Products
Visit this page here for information about and links to pre-prints and other resources associated with publications (peer-reviewed journal articles, book chapters, and conference proceedings) and other products (R packages and simulations for learners).
Ongoing Research Projects
State Educational Twitter Hashtags (SETHs): https://jmichaelrosenberg.shinyapps.io/SETHs z
Ongoing Research Projects
Here is information about ongoing and recently completed research projects.
Profiles of Science Engagement
With Jennifer Schmidt (MSU), Neil Naftzger (American Institutes for Research), Lee Shumow (Northern Illinois University) and colleagues.
- Investigate student engagement through the use of data collected through an Experience Sampling Method (ESM).
- Use data collected from both middle and high school classes as well as outside-of-school STEM programs.
- Using person-oriented and within-person analytic approaches.
STEM Interest and Engagement
With Jennifer Schmidt (MSU), Lee Shumow (Northern Illinois University), and colleagues.
- Explore the impact of learners’ participation in outside-of-school STEM programs.
- Understand momentary, personal, and program predictors of students’ interest and engagement.
- Use of ESM, survey, and video data and use mixed effects (or multi-level) models.
The REX Virtual Experiment Platform
With Rochelle Schwartz-Bloom (Duke), Lisa Linnenbrink-Garcia (MSU), and colleagues.
- Understand high school students’ development of situational interest as part of their use of an online virtual experiment platform.
- Use self-report and log-trace data to document student motivation and learning.
Teaching and Learning in Online Science Classes at Michigan Virtual School
With John Ranellucci (Hunter College).
- Design activities to support student work with authentic data sources in high school science classes.
- Document the development of students’ ability to engage in work with data through the use of embedded assessments.
- Use self-report and log-trace data to explore relationships among students’ motivation, engagement, and achievement.
Supporting Scientific Practices in Elementary and Middle School Classrooms
With Christina Schwarz (MSU), Christina Krist (University of Illinois), Brian Reiser (Northwestern University), and colleagues.
- Develop curricula, providing teacher professional development, and documenting student (and teacher) learning across multiple years.
- Document student learning using computational and traditional qualitative and quantitative approaches.
- Understand longitudinal changes in teachers’ instructional practice focused around support students’ development of scientific models of phenomena.
The MSU-Wipro STEM & Leadership Teaching Fellowship
With Leigh Graves Wolf (MSU), Punya Mishra (Arizona State), Matthew Koehler (MSU) and colleagues.
- Develop and explore the development of online learning communities through the use of a Twitter hashtag, a Facebook group, and other educational and communication technologies.
- Use social network analysis models and methods to understand how teachers’ influence one another and impact changes in their teaching practice.