My research focuses on support and documenting student engagement in activities focused around work with data. I also explore how new data sources and methods (such as log-trace data and network analysis) can be used as part of educational research.
The aims of this work are to design curricula and tools centered around learners’ use of data to make sense of phenomena and to document student engagement and learning. I carry out my research and development in the context of classrooms (at the K-12 and post-secondary levels) and other settings.
This page contains information on publications (peer-reviewed journal articles, book chapters, and conference proceedings), other products (R packages and simulations for learners) as well as information about ongoing research projects.
Ongoing Research Projects
Here is information about ongoing research projects.
Supporting Scientific Practices in Elementary and Middle School Classrooms
- 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.
Profiles of Science Engagement
- 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.
The MSU-Wipro STEM & Leadership Teaching Fellowship
- 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.
STEM Interest and Engagement
- 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
- 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.
Flipping the Undergraduate Anatomy Classroom
- Work with a professor and teaching assistants to flip an undergraduate anatomy class.
- Make changes over time to the design of the class to support students’ motivation both within and outside of the classroom.
- Use log-trace data for viewing videorecorded lectures to understand patterns in students’ outside of class engagement over time.
Teaching and Learning in Online Science Classes at Michigan Virtual School
- 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.
Teachers’ use of Twitter as a professional learning community
- Collect more than 2,000,000 tweets over two years associated with State Educational Twitter Hashtags (SETHs)
- Use descriptive and social network analysis models and methods to understand participation in these communities
- Share findings back to participants associated with SETHs to build recognition of new places for teacher professional learning