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Data Nuggets are free classroom activities, co-designed by scientists and teachers. When using Data Nuggets students are provided with the details of authentic science research projects, and then get to work through an activity that gives them practice looking for patterns and developing explanations about natural phenomena using the scientific data from the study.
The goals of the Data Nuggets program are to (1) help scientists increase the broader impacts of their research by sharing their science story and data with the public; (2) engage students in the practices of science through an innovative approach that includes science storytelling, cutting-edge research, and authentic datasets; and (3) provide teacher professional development training surrounding data literacy, practices of science, and introducing scientist role models.
Because of their simplicity and flexibility, Data Nuggets can be used throughout the school year as students build confidence in their quantitative skills. Reading and graphing levels allow for differentiated learning for students with any science background.
Data Nugget activities are ranked from 1-4 according to the reading, vocabulary, and content level of the background information provided to students. Readability for each activity is determined using the Flesch–Kincaid Reading Grade Level, which calculates how difficult a reading passage in English is to understand. Content level is determined by aligning each activity with science standards and discussions with our advisor panel of K-12 teachers. Activities of the highest level (4) are probably inappropriate for younger students, but level 1 activities are still appropriate to use with higher-level students if the quantitative skills they teach are relevant.
Each Data Nugget comes with three student versions, based on the type of graphing skills required. Type A activities provide the graph for the students (allowing a focus on graph interpretation, making claims based on evidence, and explaining reasoning), Type B activities provide axis labels but requires students to graph the data, and Type C provides an unlabeled grid on which to draw a graph.
Data Nuggets have been shown to engage students in the practices of science, increase student interest in STEM careers, and help students relate to scientist role models. The first efficacy study on Data Nuggets took place in high school biology classrooms across the country. They found that students who used Data Nuggets had improved confidence (self-efficacy) when working with data, were more interested in STEM careers, and were better able to construct scientific explanations using data as evidence (Schultheis et al. 2022). Students using Data Nuggets also spent more time engaged in the work of scientists in the classroom. The next round of research built on these findings to explore the role of scientist role models within our activities. They found that when scientists shared humanizing, personal information alongside details of their research, students were better able to relate to scientists (Schultheis et al. 2024). Sharing humanizing information also increased student engagement in the activities (Costello et al. 2025). For more on Data Nuggets research, visit https://datanuggets.org/research/
References
editStrode, P.K., L.S. Mead, M. Stuhlsatz, M.K. Kjelvik, E.H. Schultheis, A. R. Warwick, A. Mohan, J.A. Morris, and R. Mayes. 2025. Quantitative Reasoning in the Context of Science Phenomena. The American Biology Teacher 87:308-312.
Costello, R.A., S.N. Ewell, P.E. Adams, M.L. Aranda, A. Curry, M.M. De Jesus, R.D.P. Dunk, M.E. Garcia-Ojeda, SJ. Gutzler, L.R.A. Habersham, M.K. Kjelvik, M. Mateen, K.J. Metzger, K.X. Mulligan, M.T. Owens, R.M. Pigg, K. Quillin, M.M. Rice, S. Sovi, E.H. Schultheis, J. Schultz, E.J. Theobald, E.Tracey, B. Tripp, S. Yang, A. Zemenick, C.J. Ballen, and D. Ovid. (2025). Highlighting counterstereotypical scientists in undergraduate life science courses. CBE Life Sciences Education 24:es1.
Costello, R. A., E. P. Driessen, M. K. Kjelvik, E. H. Schultheis, R. M. Youngblood, A. T. Zemenick, M. G. Weber, and C. J. Ballen. (2025). More than a token photo: humanizing scientists enhances student engagement. Proceedings. Biological sciences / The Royal Society 292:20240879.
Schultheis, E. H., A. T. Zemenick, R. M. Youngblood, R. A. Costello, E. P. Driessen, M. K. Kjelvik, M. G. Weber, and C. J. Ballen. (2024). “Scientists are people too”: Biology students relate more to scientists when they are humanized in course materials. CBE Life Sciences Education 23:ar64.
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 explanations. International Journal of Science and Mathematics Education 21:1339-1362.
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 53:1179-1201.
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.
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 literacy. CBE Life Sciences Education 18(2): es2.
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.