A cross-disciplinary approach to teaching data literacy and proportionality

The Thinking with Data project (TWD) expands on current notions of data literacy by (1) focusing on proportional reasoning as key to data literacy and (2) leveraging the non-mathematics disciplines to engage students in deep thinking about the context of data and the application of proportionality. A set of four 2-week, sequential modules for cross-disciplinary implementation in seventh-grade classrooms was designed and evaluated. Using a quasi-experimental approach, we found that student data literacy was increased through the focused integration of social studies, mathematics, science, and English language arts. In this article, we describe our theoretical approach to designing and implementing the modules, report on student learning gains in mathematics, and describe teacher reactions to the materials. In sum, our study provides evidence that the TWD approach has the potential to build data literacy while also allowing students to learn core discipline-based content standards.

[1]  Dani Ben-Zvi,et al.  Junior high school students' construction of global views of data and data representations , 2001 .

[2]  Kenneth A. Strike,et al.  A revisionist theory of conceptual change , 1992 .

[3]  William H. Schmidt,et al.  Facing the Consequences: Using TIMSS for a Closer Look at U.S. Mathematics and Science Education , 1999 .

[4]  James J. Kaput,et al.  From static to dynamic mathematics: historical and representational perspectives , 2008 .

[5]  Merlyn J. Behr,et al.  Number concepts and operations in the middle grades , 1988 .

[6]  A. Su,et al.  The National Council of Teachers of Mathematics , 1932, The Mathematical Gazette.

[7]  Robert Adjiage,et al.  An Experiment in Teaching Ratio and Proportion , 2007 .

[8]  Jeremy Roschelle,et al.  Designing Formative Assessment Software with Teachers: an Analysis of the Co-Design Process , 2007, Res. Pract. Technol. Enhanc. Learn..

[9]  James E. Akenson.  NATIONAL COUNCIL FOR THE SOCIAL STUDIES CONVENTION , 2012 .

[10]  James J. Kaput,et al.  Teaching and Learning a New Algebra , 1999 .

[11]  Robin Fogarty,et al.  How to Integrate the Curricula , 1991 .

[12]  Steven Pulos,et al.  Proportional reasoning: A review of the literature , 1985 .

[13]  D. Clements.  Curriculum Research: Toward a Framework for "Research-based Curricula" , 2007 .

[14]  K. Kafadar,et al.  Statistics: Concepts and Controversies , 1980 .

[15]  Richard Lesh,et al.  Origins and Evolution of Model-Based Reasoning in Mathematics and Science , 2003 .

[16]  D. Cohen,et al.  Learning Policy: When State Education Reform Works , 2001 .

[17]  Richard Lehrer,et al.  Grounding Metaphors and Inscriptional Resonance: Children's Emerging Understanding of Mathematical Similarity , 2002 .

[18]  K.P.E. Gravemeijer,et al.  Context Problems in Realistic Mathematics Education: A Calculus Course as an Example , 1999 .

[19]  Peggy A. House,et al.  Connecting Mathematics Across the Curriculum , 1995 .

[20]  Noel Enyedy,et al.  Learning probability through the use of a collaborative, inquiry-based simulation environment , 2000 .

[21]  Richard Lehrer,et al.  Investigating Real Data in the Classroom: Expanding Children's Understanding of Math and Science. Ways of Knowing in Science and Mathematics Series. , 2002 .

[22]  M. Mariotti.  Introduction to Proof: The Mediation of a Dynamic Software Environment , 2000 .

[23]  Jeremy Roschelle,et al.  Integration of Technology, Curriculum, and Professional Development for Advancing Middle School Mathematics , 2010 .

[24]  Edward A. Silver,et al.  Implementing Standards-Based Mathematics Instruction: A Casebook for Professional Development , 2009 .

[25]  Daniel L. Schwartz,et al.  Rethinking transfer: A simple proposal with multiple implica-tions , 1999 .

[26]  James J. Kaput,et al.  Authentic Inquiry With Data: Critical Barriers to Classroom Implementation , 1992 .

[27]  Keith Jones.  Providing a Foundation for Deductive Reasoning: Students' Interpretations when Using Dynamic Geometry Software and Their Evolving Mathematical Explanations , 2000 .

[28]  Lyn D. English,et al.  Problem solving for the 21st century , 2010 .

[29]  Milena K. Nigam,et al.  The Equivalence of Learning Paths in Early Science Instruction: Effects of Direct Instruction and Discovery Learning , 2022 .

[30]  Paul Cobb,et al.  Supporting Students' Ability to Reason about Data , 2001 .

[31]  Susanne P. Lajoie,et al.  Empowering children in the use of statistics , 1995 .

[32]  Kpe Koeno Gravemeijer.  How Emergent Models May Foster the Constitution of Formal Mathematics , 1999 .

[33]  Jere Confrey,et al.  The Development of multiplicative reasoning in the learning of mathematics , 1995 .

[34]  A. Strauss,et al.  Grounded theory , 2017 .

[35]  Chris Arney.  Mathematics and Democracy: The Case for Quantitative Literacy , 2002 .

[36]  Takeshi Miyakawa,et al.  Didactical designs for students’ proportional reasoning: an “open approach” lesson and a “fundamental situation” , 2009 .

[37]  D. S. Moore,et al.  Mathematics, statistics, and teaching , 1997 .

[38]  Lynn Arthur Steen,et al.  Book reviews: Mathematics and democracy: the case for quantitative literacy , 2002 .

[39]  Richard Lesh,et al.  A science need: Designing tasks to engage students in modeling complex data , 2008 .

[40]  Lyn D. English,et al.  Theories of Mathematics Education: Seeking New Frontiers , 2012 .

[41]  Patrick W Thompson,et al.  Images of Rate , 1992 .

[42]  H. Freudenthal.  Didactical Phenomenology of Mathematical Structures , 1983 .