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Title: Using slow reveal graphs to build data literacy skills and increase student engagement
Data literacy is an integral part of overall literacy in the twenty-first century. After participating in a National Science Foundation–funded BIORETS (Research Experiences for Teachers Sites in Biological Sciences) program that emphasized the importance of data literacy, I was motivated to focus more intentionally on data literacy in my middle school classroom. Providing students with strategies for making sense of data is an important component of data literacy. In an effort to develop this data literacy skill, I introduced Slow Reveal Graphs, a teaching strategy that promotes sensemaking about data. By removing contextual information from data visualizations presented in textbooks and the media and asking students to interpret the information as it is provided, students engage in problem solving, gain confidence, and grow their computational thinking skills. As a result, students engage more deeply with the content of graphs and other visual representations of data. more »« less
Maxwell, Danielle N.; Spencer, Jeffrey L.; Teich, Ethan A.; Cooke, Madeline; Fromwiller, Braeden; Peterson, Nathan; Nicholas-Figueroa, Linda; Shultz, Ginger V.; Pratt, Kerri A.
(, Journal of Chemical Education)
Holme, Thomas
(Ed.)
Reading and understanding scientific literature is an essential skill for any scientist to learn. While students’ scientific literacy can be improved by reading research articles, an article’s technical language and structure can hinder students’ understanding of the scientific material. Furthermore, many students struggle with interpreting graphs and other models of data commonly found in scientific literature. To introduce students to scientific literature and promote improved understanding of data and graphs, we developed a guided-inquiry activity adapted from a research article on snow chemistry and implemented it in a general chemistry laboratory course. Here, we describe how we adapted figures from the primary literature source and developed questions to scaffold the guided-inquiry activity. Results from semi-structured qualitative interviews suggest that students learn about snow chemistry processes and engage in scientific practices, including data analysis and interpretation, through this activity. This activity is applicable in other introductory science courses as educators can adapt most scientific articles into a guided-inquiry activity.
Gold, Anne U.; Atkins, Rachel; McNeal, Karen S.
(, Scholarship and Practice of Undergraduate Research)
Research Experiences for Undergraduate (REU) programs often introduce students to scientific research and STEM career possibilities. However, the program impact on students and their research skill development is not well understood. In a case study with 10 REU students, the authors used eye-tracking and self-report data to determine student strategies for reading scientific papers and interpreting graphs at the beginning and end of the program. The strategies of REU students and science experts were then compared. The REU students changed their strategies and performed more like experts at posttest. These findings indicate that, during the REU, students acquired expert-like strategies necessary to engage with scientific articles and extract key information from graphs. The study demonstrates that eye-tracking can document skill growth in REU students.
Despite efforts to diversify the science, technology, engineering, and mathematics (STEM) workforce, engineering remains a White, male-dominated profession. Often, women and underrepresented students do not identify with STEM careers and many opt out of STEM pathways prior to entering high school or college. In order to broaden participation in engineering, new methods of engaging and retaining those who are traditionally underrepresented in engineering are needed. This work is based on a promising approach for encouraging and supporting diverse participation in engineering: disciplinary literacy instruction (DLI). Generally, teachers use DLI to provide K-12 students with a framework for interpreting, evaluating, and generating discipline-specific texts. This instruction provides students with an understanding of how experts in the discipline read, engage, and generate texts used to solve problems or communicate information. While models of disciplinary literacy have been developed and disseminated in several humanities and science fields, there is a lack of empirical and theoretical research that examines the use of DLI within the engineering domain. It is thought that DLI can be used to foster diverse student interest in engineering from a young age by removing literacy-based barriers that often discourage underrepresented students from entering and pursuing careers in STEM fields. This work-in-progress paper describes a new study underway to develop and disseminate a model of disciplinary literacy in engineering. During this project, researchers will observe, interview, and collect written artifacts from engineers working across four sub-disciplines of engineering: aerospace/mechanical, biological, civil/environmental, and electrical/computer. Data that will be collected include interview transcripts, observation field notes, engineer logs of literacy practices, and photographs of texts that the engineers read and write. Data will be analyzed using constant comparative analytic (CCA) methods. CCA will be used to generate theoretical codes from the data that will form the basis for a model of disciplinary literacy in engineering. As a primary outcome of this research, the engineering DLI model will promote the use of DLI practices within K-12 engineering instruction in order to assist and encourage diverse, underrepresented students to engage in engineering courses of study and pursue STEM careers. Thus far, the research team has begun collecting and analyzing data from two electrical engineers. This work in progress paper will report on preliminary findings, as well as implications for K-12 classroom instruction. For instance, this study has shed insights on how engineers use texts as part of the process of conducting failure analysis, and the research team has begun to conceptualize how these types of texts might be used with K-12 students to help them conduct failure analyses during design testing. Ultimately, this project will result in a list of grade-appropriate texts, evaluative frameworks, and activities (e.g., failure analysis in testing) that K-12 engineering teachers can use to prepare their diverse students to think, act, read, and write like engineers.
To promote understanding of and interest in working with data among diverse student populations, we developed and studied a high school mathematics curriculum module that examines income inequality in the United States. Designed as a multi-week set of applied data investigations, the module supports student analyses of income inequality using U.S. Census Bureau microdata and the online data analysis tool the Common Online Data Analysis Platform (CODAP). Pre- and post-module data show that use of this module was associated with statistically significant growth in students’ understanding of fundamental data concepts and individual interests in statistics and data analysis, with small to moderate effect sizes. Student survey responses and interview data from students and teachers suggest that the topic of income inequality, features within CODAP, the use of person-level data, and opportunities to engage in multivariable thinking helped to support critical data literacy and its foundations among participating students. We describe our definitions of data literacy and critical data literacy and discuss curriculum strategies to develop them.
Strode, Paul K; Mead, Louise S; Stuhlsatz, Molly; Kjelvik, Melissa K; Schultheis, Elizabeth H; Warwick, Alexa R; Mohan, Audrey; Morris, Julie A; Mayes, Robert
(, The American Biology Teacher)
Over the last decade, reform in science education has placed an emphasis on the science practices as a way to engage students in the process of science and improve scientific literacy. A critical component of developing scientific literacy is learning to apply quantitative reasoning to authentic scientific phenomena and problems. Students need practice moving fluidly (or fluently) between math and science to develop a habit of mind that encourages the application of quantitative reasoning to real-world scenarios. Here we present a student-facing model that challenges students to think across these two fields. The model brings together math and science with a goal to increase scientific literacy by engaging students in quantitative reasoning within the context of scientific questions and phenomena. In the classroom, the model serves to help students visualize the logical and necessary moves they make as they use quantitative reasoning to connect science practices with mathematical thinking.
Hipps, Nina, and Bruhn, Jacqueline. Using slow reveal graphs to build data literacy skills and increase student engagement. Retrieved from https://par.nsf.gov/biblio/10660007. Science Scope 49.1
Hipps, Nina, & Bruhn, Jacqueline. Using slow reveal graphs to build data literacy skills and increase student engagement. Science Scope, 49 (1). Retrieved from https://par.nsf.gov/biblio/10660007.
Hipps, Nina, and Bruhn, Jacqueline.
"Using slow reveal graphs to build data literacy skills and increase student engagement". Science Scope 49 (1). Country unknown/Code not available: National Science Teachers Association / Taylor and Francis. https://par.nsf.gov/biblio/10660007.
@article{osti_10660007,
place = {Country unknown/Code not available},
title = {Using slow reveal graphs to build data literacy skills and increase student engagement},
url = {https://par.nsf.gov/biblio/10660007},
abstractNote = {Data literacy is an integral part of overall literacy in the twenty-first century. After participating in a National Science Foundation–funded BIORETS (Research Experiences for Teachers Sites in Biological Sciences) program that emphasized the importance of data literacy, I was motivated to focus more intentionally on data literacy in my middle school classroom. Providing students with strategies for making sense of data is an important component of data literacy. In an effort to develop this data literacy skill, I introduced Slow Reveal Graphs, a teaching strategy that promotes sensemaking about data. By removing contextual information from data visualizations presented in textbooks and the media and asking students to interpret the information as it is provided, students engage in problem solving, gain confidence, and grow their computational thinking skills. As a result, students engage more deeply with the content of graphs and other visual representations of data.},
journal = {Science Scope},
volume = {49},
number = {1},
publisher = {National Science Teachers Association / Taylor and Francis},
author = {Hipps, Nina and Bruhn, Jacqueline},
}
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