skip to main content


Title: Getting Messy with Authentic Data: Exploring the Potential of Using Data from Scientific Research to Support Student Data Literacy
Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise when students are given opportunities to work with authentic data from scientific research. First, we explore the overlap between the fields of quantitative reasoning, data science, and data literacy, specifically focusing on how data literacy results from practicing quantitative reasoning and data science in the context of authentic data. Next, we identify and describe features that influence the complexity of authentic data sets (selection, curation, scope, size, and messiness) and implications for data-literacy instruction. Finally, we discuss areas for future research with the aim of identifying the impact that authentic data may have on student learning. These include defining desired learning outcomes surrounding data use in the classroom and identification of teaching best practices when using data in the classroom to develop students’ data-literacy abilities.  more » « less
Award ID(s):
1832042 1637653 1027253
PAR ID:
10112628
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
CBE—Life Sciences Education
Volume:
18
Issue:
2
ISSN:
1931-7913
Page Range / eLocation ID:
es2
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Incorporating authentic research skills and practices into K‐12 science, technology, engineering, and mathematics (STEM) instruction is a challenging yet crucial approach for introducing students to authentic science inquiry. While recommendations for emphasizing data literacy and quantitative reasoning in science classroom contexts are well‐established, implementation remains challenging. Over the span of 4 years (2019–2023), a multi‐institution team of teachers, education researchers, and forest scientists established a partnership with the overarching goal of integrating authentic forest research and data into middle and high school classrooms. The education researchers played a critical role in facilitating effective scientist and teacher interactions while addressing classroom implementation challenges. Importantly, the effectiveness and mutual benefits of the research partnership were greatly influenced by specific practices implemented by the education research team, and the assumption of different collaborative roles by all stakeholders involved. In this study, we examine these roles, relationships, and interactions of all stakeholders in the partnership, with “stakeholder” referring to participating teachers, education researchers, and collaborating forest scientists.

     
    more » « less
  2. null (Ed.)
    Authentic, “messy data” contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science itself. While the value of bringing contemporary research and messy data into the classroom is recognized, implementation can seem overwhelming. We discuss the importance of frequent interactions with messy data throughout K–16 science education as a mechanism for students to engage in the practices of science, such as visualizing, analyzing, and interpreting data. Next, we describe strategies to help facilitate the use of messy data in the classroom while building complexity over time. Finally, we outline one potential sequence of activities, with specific examples, to highlight how various activity types can be used to scaffold students' interactions with messy data. 
    more » « less
  3. Data science education can help broaden participation in computer science (CS) because it provides rich, authentic contexts for students to apply their computing knowledge. Data literacy, particularly among underrepresented students, is critical to everyone in this increasingly digital world. However, the integration of data science into K-12 schools is nascent, and the pedagogical training of CS teachers in data science remains limited. Our research-practice partnership modified an existing data science unit to include two pedagogical techniques known to support minoritized students: rich classroom discourse and personally-relevant problem-solving. This paper describes the iterative design process we used to revise and pilot this new data science unit. 
    more » « less
  4. In an effort to improve the quality of citizen engagement in workplace, politics, and other domains in which quantitative reasoning plays an important role, Quantitative Literacy (QL) has become the focus of considerable research and development efforts in mathematics education. QL is characterized by sophisticated reasoning with elementary mathematics. In this project, we extend the notions of QL to include the physics domain and call it Physics Quantitative Literacy (PQL). We report on early stage development from a collaboration that focuses on reasoning inventory design and data analysis methodology for measuring the development of PQL across the introductory physics sequence. We have piloted a prototype assessment designed to measure students' PQL in introductory physics: Physics Inventory of Quantitative Literacy (PIQL). This prototype PIQL focuses on two components of PQL: proportional reasoning, and reasoning with signed quantities. We present preliminary results from approximately 1,000 undergraduate and 20 graduate students. 
    more » « less
  5. This study explores disciplinary literacy instruction integrated within an elementary engineering unit in an urban classroom. A multidisciplinary team of university literacy and engineering educators and classroom teachers served as the research team for this case study. A social semiotic language theory (systemic functional linguistics) and a framework of mechanistic reasoning informed the instruction and analysis of classroom discourse and student writing. The study illustrates how a flexible set of disciplinary language choices functioned to support students’ evolving reasoning as part of the engineering design process. These findings provide insights into synergy between language and reasoning as a habit of design. These findings also inform calls to align science, technology, engineering, and mathematics (STEM) literacy and core disciplinary practices within both Common Core State Standards for (English language arts) ELA and Next Generation Science Standards.

     
    more » « less