Publications & Research

Publications: Our first paper on Data Nuggets is in the January 2015 issue of the American Biology Teacher. We hope this paper introduces Data Nuggets to a broader audience of teachers. Click here for a PDF!

Schultheis, E. H. and M. K. Kjelvik (2015). Data Nuggets: Bringing real data into the classroom to unearth students’ quantitative and inquiry skills. The American Biology Teacher 77(1):19-29.

We were published in the June 2019 issue of CBE Life Sciences Education available open access online. Click here for a PDF!

Kjelvik, M. K. and E. H. Schultheis (2019). Getting messy with authentic data: Exploring the potential of using data from scientific research to support student data literacyCBE Life Sciences Education 18(2): es2.

Our next paper focuses on use of messy data in the classroom, and is out in the September 2020 issue of The American Biology Teacher! Click here for a PDF!

Schultheis, E. H. and M. K. Kjelvik (2020). Using messy, authentic data to promote data literacy and reveal the nature of science. The American Biology Teacher 82(7): 439-446.

Based on a survey of Data Nuggets users and other teachers across the country, we have a new paper looking at the types of data and technology used in K-12 classrooms today. Blog summary here. Click here for a PDF!

Rosenberg, J., E.H. Schultheis, M.K. Kjelvik, A. Reedy, O. Sultana. (2022) Big data, big changes? The technologies and sources of data used in science classrooms. British Journal of Educational Technology

The results of our NSF DRK-12 efficacy study on Data Nuggets is now published! We found that students using Data Nuggets improved in their ability to construct scientific explanations, had greater interest in STEM careers, improved confidence in their ability to work with data, and spent more time engaged in science practices. Click here for a PDF!

Schultheis, E.H., M.K. Kjelvik, J. Snowden, L. Mead, and M.A.M. Stuhlsatz (2022) Effects of Data Nuggets on student interest in STEM careers, self-efficacy in data tasks, and ability to construct scientific explanationsInternational Journal of Science and Mathematics Education

NSF IUSE Research Study: We are collaborating with Project Biodiversify and Auburn University on a new grant, with the goal of increasing the representation in our scientist role models found in Data Nuggets.

You can find the press release for the grant here!

NSF DRK-12 Research Study: We just completed our first research study, in partnership with BSCS and BEACON at MSU. Using a fully randomized design, we evaluated the effectiveness of integrating Data Nuggets into science curriculum. We found that students in classrooms using Data Nuggets:

  1. Spent more time engaged in the practices of science.

  2. Were better at constructing scientific explanations, including their ability to support claims using data as evidence.

  3. Had greater confidence (self-efficacy) in their science and data literacy abilities.

  4. Showed greater motivation to engage in science and pursue STEM careers.

For a press release on the project, check out the page on MSU’s website here. For our paper with results from the study, click here!

BEACON: Data Nuggets was awarded several grants through the BEACON Center at Michigan State University. The goal of this collaboration was to develop and provide science communication professional development workshops across all 5 BEACON institutions, create evolution-themed curriculum to use in K-12 and undergraduate classrooms, and disseminate BEACON research to teachers and students.

  • Enhancing BEACON’s educational legacy with a set of curricular materials derived from our center’s research (2020)
  • Bringing Data to Life in Science Classrooms (2016)
  • Data on Data Nuggets: Assessing the efficacy of an innovative science education resource to build a foundation for future support (2015)
  • Taking Data Nuggets to the national level (2014)
  • Data Nuggets: Unearthing Inquiry skills (2013)

LTER Data Nuggets: Data Nuggets was funded by the KBS LTER to develop new activities that focus on available long-term datasets, and expand students’ exposure to data of different levels of complexity. To explore these resources, check out this page!