Large-Scale Studies in Mathematics Education

1. Front Matter

   Pages i-xxix

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2. Why Mathematics Education Needs Large-Scale Research

   • James A. Middleton, Jinfa Cai, Stephen Hwang

   Pages 1-13

3. Curriculum

   1. Front Matter

      Pages 15-15

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   2. A Lesson for the Common Core Standards Era from the NCTM Standards Era: The Importance of Considering School-Level Buy-in When Implementing and Evaluating Standards-Based Instructional Materials

      • Steven Kramer, Jinfa Cai, F. Joseph Merlino

      Pages 17-44

   3. Longitudinally Investigating the Impact of Curricula and Classroom Emphases on the Algebra Learning of Students of Different Ethnicities

      • Stephen Hwang, Jinfa Cai, Jeffrey Shih, John C. Moyer, Ning Wang, Bikai Nie

      Pages 45-60

   4. Exploring the Impact of Knowledge of Multiple Strategies on Students’ Learning About Proportions

      • Rozy Vig, Jon R. Star, Danielle N. Dupuis, Amy E. Lein, Asha K. Jitendra

      Pages 61-73

   5. Challenges in Conducting Large-Scale Studies of Curricular Effectiveness: Data Collection and Analyses in the COSMIC Project

      • James E. Tarr, Victor Soria

      Pages 75-91

4. Teaching

   1. Front Matter

      Pages 93-93

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   2. Turning to Online Courses to Expand Access: A Rigorous Study of the Impact of Online Algebra I for Eighth Graders

      • Jessica B. Heppen, Margaret Clements, Kirk Walters

      Pages 95-132

   3. A Randomized Trial of Lesson Study with Mathematical Resource Kits: Analysis of Impact on Teachers’ Beliefs and Learning Community

      • Catherine C. Lewis, Rebecca Reed Perry

      Pages 133-158

   4. Conceptualizing Teachers’ Capacity for Learning Trajectory-Oriented Formative Assessment in Mathematics

      • Caroline B. Ebby, Philip M. Sirinides

      Pages 159-176

5. Learning

   1. Front Matter

      Pages 177-177

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   2. Using NAEP to Analyze Eighth-Grade Students’ Ability to Reason Algebraically

      • Peter Kloosterman, Crystal Walcott, Nathaniel J. S. Brown, Doris Mohr, Arnulfo Pérez, Shenghi Dai et al.

      Pages 179-207

   3. Homework and Mathematics Learning: What Can We Learn from the TIMSS Series Studies in the Last Two Decades?

      • Yan Zhu

      Pages 209-234

   4. Effect of an Intervention on Conceptual Change of Decimals in Chinese Elementary Students: A Problem-Based Learning Approach

      • Ru-De Liu, Yi Ding, Min Zong, Dake Zhang

      Pages 235-263

   5. A Longitudinal Study of the Development of Rational Number Concepts and Strategies in the Middle Grades

      • James A. Middleton, Brandon Helding, Colleen Megowan-Romanowicz, Yanyun Yang, Bahadir Yanik, Ahyoung Kim et al.

      Pages 265-289

6. Methodology

   1. Front Matter

      Pages 291-291

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   2. Measuring Change in Mathematics Learning with Longitudinal Studies: Conceptualization and Methodological Issues

      • Jinfa Cai, Yujing Ni, Stephen Hwang

      Pages 293-309

   3. A Review of Three Large-Scale Datasets Critiquing Item Design, Data Collection, and the Usefulness of Claims

      • Darryl Orletsky, James A. Middleton, Finbarr Sloane

      Pages 311-334

   4. Methodological Issues in Mathematics Education Research When Exploring Issues Around Participation and Engagement

      • Tamjid Mujtaba, Michael J. Reiss, Melissa Rodd, Shirley Simon

      Pages 335-362

In recent years, funding agencies like the Institute of Educational Sciences and the National Science Foundation have increasingly emphasized large-scale studies with experimental and quasi-experimental designs looking for 'objective truths'. Educational researchers have recently begun to use large-scale studies to understand what really works, from developing interventions, to validation studies of the intervention, and then to efficacy studies and the final "scale-up" for large implementation of an intervention. Moreover, modeling student learning developmentally, taking into account cohort factors, issues of socioeconomics, local political context and the presence or absence of interventions requires the use of large data sets, wherein these variables can be sampled adequately and inferences made. Inroads in quantitative methods have been made in the psychometric and sociometric literatures, but these methods are not yet common knowledge in the mathematics education community. In fact, currently there is no volume devoted to discussion of issues related to large-scale studies and to report findings from them. This volume is unique as it directly discusses methodological issue in large-scale studies and reports empirical data from large-scale studies.

• Large-scale studies in mathermatics education
• Learning Trajectories for mathematics education
• effective teaching of mathematics
• mathematics curriculum implementation
• quantitative research methods
• standards-based curriculum for amthematics education

• Global Institute of Sustainability, Arizona State University, Tempe, USA

  James A. Middleton

• Dept. Mathematical Sciences, University of Delaware, Newark, USA

  Jinfa Cai

• Department of Mathematical Sciences, University of Delaware, Newark, USA

  Stephen Hwang

James A. Middleton is Professor of Mechanical and Aerospace Engineering at Arizona State University. Prior to these appointments, Dr. Middleton served as Associate Dean for Research for the Mary Lou Fulton College of Education at Arizona State University and as Director of the Division of Curriculum and Instruction. He received his Ph.D. in Educational Psychology from the University of Wisconsin-Madison in 1992, where he also served in the National Center for Research on Mathematical Sciences Education as a postdoctoral scholar for 3 years. Jim’s research interests focus in the following areas where he has published extensively: Children’s mathematical thinking; Teacher and Student motivation in mathematics; and Teacher Change in mathematics. He has served as Senior co-Chair of the Special Interest Group for Mathematics Education of the American Educational Research Association, and as chair of the National Council of Teachers of Mathematics Research Committee.

Jinfa Cai is a Professor of Mathematics and Education and the director of Secondary math education at the University of Delaware.  He is interested in how students learn mathematics and solve problems, and how teachers can provide and create learning environments so that students can make sense of mathematics.  He received a number of awards, including a National Academy of Education Spencer Fellowship, an American Council on Education Fellowship, an International Research Award, and a Teaching Excellence Award. He has been serving on the Editorial Boards for several international journals, such as the Journal for Research in Mathematics Education.  He was a visiting professor in various institutions, including Harvard University.  He has serves as a Program Director at the U.S. National Science Foundation (2010-2011) and a co-chair of American Educational Research Association’s Special Interest Group on Research in Mathematics Education (AERA’s SIG-RME)(2010-2012).  He will be chairing a plenary panel at the ICMI-12 in Germany in 2016.

Stephen Hwang is currently a post-doctoral researcher working with Jinfa Cai in the Department of Mathematical Sciences at the University of Delaware. His research interests include the teaching and learning of mathematical justification and proof, the nature of practice in the discipline of mathematics, the development of mathematical habits of mind, and mathematics teacher preparation.

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