It Pays to Compare: Effectively Using Comparison to Support Student Learning of Algebra Bethany Rittle-Johnson Jon Star.

Slides:



Advertisements
Similar presentations
The “Insertion” Error in Solving Linear Equations Kosze Lee and Jon R. Star, Michigan State University Introduction This proposed research investigates.
Advertisements

Common Core State Standards K-5 Mathematics Kitty Rutherford and Amy Scrinzi.
Highlights from PIRLS and TIMSS 2011 Jack Buckley National Center for Education Statistics Washington, DC December 11, 2012.
Teacher Quality Workshops for 2010/2011
Contrasting Cases in Mathematics Lessons Support Procedural Flexibility and Conceptual Knowledge Jon R. Star Harvard University Bethany Rittle-Johnson.
Explaining Contrasting Solution Methods Supports Problem-Solving Flexibility and Transfer Bethany Rittle-Johnson Vanderbilt University Jon Star Michigan.
Middle School Mathematics Teachers’ Circle Institute for Mathematics & Education Nov. 3, 2009 Cynthia Anhalt Using Algebra Blocks.
Enhancing the Mathematical Problem Solving Performance of Seventh Grade Students Using Schema-Based Instruction: Year 1, Design Experiment Asha K. Jitendra,
Does Comparison Support Transfer of Knowledge? Investigating Student Learning of Algebra Jon R. Star Michigan State University (Harvard University, as.
Investigating Student Thinking about Estimation: What Makes a Good Estimate? Jon R. Star Kosze Lee, Kuo-Liang Chang Tharanga Wijetunge Michigan State University.
Compared to What? How Different Types of Comparison Affect Transfer in Mathematics Bethany Rittle-Johnson Jon Star.
Students’ use of standard algorithms for solving linear equations Jon R. Star Michigan State University.
Results (continued) In the sequential student pair’s (A&B) interactions, the students read out the coefficients of the terms (2, 6 and 4) without using.
Interview Effects on the Development of Algebraic Strategies Howard Glasser and Jon R. Star, Michigan State University Purpose/Objective This research.
Improving Students’ Flexibility in Algebra: The Benefits of Comparison Jon R. Star Michigan State University (Harvard University, as of July 2007)
Discussant Remarks Jon R. Star Michigan State University.
Improving Students’ Flexibility in Algebra: The Benefits of Comparison Jon R. Star Michigan State University (Harvard University, as of July 2007)
Contrasting Examples in Mathematics Lessons Support Flexible and Transferable Knowledge Bethany Rittle-Johnson Vanderbilt University Jon Star Michigan.
When it pays to compare: Benefits of comparison in mathematics classrooms Bethany Rittle-Johnson Jon R. Star.
Collaborating for Student Success Teacher Collaboration: Strategies & Outcomes ARCHES Seminar UC Irvine ~ 3/15/10 Ivan Cheng
Collaborating for Student Success Using Collaborative Inquiry with Student Teachers to Support Teacher Professional Development Sponsored by Teachers for.
Thinking, reasoning and working mathematically
Scaffolding Middle School Science Learning with Contrasting Cases
ACOS 2010 Standards of Mathematical Practice
It Pays to Compare! The Benefits of Contrasting Cases on Students’ Learning of Mathematics Jon R. Star 1, Bethany Rittle-Johnson 2, Kosze Lee 3, Jennifer.
NCCSAD Advisory Board1 Research Objective Two Alignment Methodologies Diane M. Browder, PhD Claudia Flowers, PhD University of North Carolina at Charlotte.
Three Shifts of the Alaska Mathematics Standards.
Katie McEldoon, Kelley Durkin & Bethany Rittle-Johnson 1.
Prototypical Level 4 Performances Students use a compensation strategy, recognizing the fact that 87 is two less than 89, which means that the addend coupled.
In Vivo Experimentation Lecture 1 for the IV track of the 2012 PSLC Summer School Philip Pavlik Jr. University of Memphis.
EDU 385 Education Assessment in the Classroom
Prompts to Self-Explain Why examples are (in-)correct Focus on Procedures 58% of explanations were procedure- based Self-explanation is thought to facilitate.
CERA 87 th Annual Conference- Effective Teaching & Learning: Evaluating Instructional Practices Rancho Mirage, CA – December 4, 2008 Noelle C. Griffin,
T 7.0 Chapter 7: Questioning for Inquiry Chapter 7: Questioning for Inquiry Central concepts:  Questioning stimulates and guides inquiry  Teachers use.
Welcome to Curriculum Night Fifth Grade Teachers: Mr. Niemeyer Mrs. Tarvin Mr. Peacock Mrs. Motley.
Using Schema-based Instruction to Improve Seventh Grade Students’ Learning of Ratio and Proportion Jon R. Star (Harvard University) Asha K. Jitendra (University.
An exploration of students’ problem solving behaviors Presenter: Chun-Yi Lee Advisor: Ming-Puu Chen Muir, T., Beswick, K., & Williamson, J. (2008). I am.
Dr. John D. Barge, State School Superintendent “Making Education Work for All Georgians” Assessment for Learning Series Module 2: Understanding.
Mathematics Teachers Grade 8 October 10, 2013 Joy Donlin and Tony Lobascher.
Developing and Using Meaningful Math Tasks The Key to Math Common Core Take a moment to record on a sticky: What is a meaningful Math Task?
Educator Effectiveness Academy Day 2, Session 1. Find Someone Who…. The purpose of this activity is to review concepts presented during day 1.
TEMPLATE DESIGN © From the laboratory to the classroom: Designing a research- based curriculum around the use of comparison.
Exploring the Development of Flexibility in Struggling Algebra Students Kristie J. Newton (Temple University) Jon R. Star (Harvard University) Katie Lynch.
+ Revisiting Collaboration and RtI October 11, 2011 Math Alliance Teaching All Learners Judy Winn Beth Schefelker Mary Ann Fitzgerald.
1 Assessing Student Understanding David Niemi UCLA Graduate School of Education & Information Studies National Center for Research on Evaluation, Standards,
Promoting the development of procedural flexibility Dr. Jon R. Star Harvard Graduate School of Education
Effective Practices and Shifts in Teaching and Learning Mathematics Dr. Amy Roth McDuffie Washington State University Tri-Cities.
Strategy Flexibility Matters for Student Mathematics Achievement: A Meta-Analysis Kelley Durkin Bethany Rittle-Johnson Vanderbilt University, United States.
Knowledge of Procedures (familiar)1. 3(h + 2) + 4(h + 2) = (x + 1) = 10 Knowledge of Procedures (transfer)3. 3(2x + 3x – 4) + 5(2x + 3x – 4) = 48.
Welcome to Parent Math Night Haslet Elementary School.
Development of the Algebra II Units. The Teaching Principle Effective teaching requires understanding what ALL students know and need to learn and challenging.
Leveraging Examples in e-Learning (Chapter 11)
The Role of Comparison in the Development of Flexible Knowledge of Computational Estimation Jon R. Star (Harvard University) Bethany Rittle-Johnson (Vanderbilt.
The Power of Comparison in Learning & Instruction Learning Outcomes Supported by Different Types of Comparisons Dr. Jon R. Star, Harvard University Dr.
Using a Model Teaching Activity to Help Teachers Learn to Use Comparison in Algebra Kristie J. Newton, Temple University Jon R. Star, Nataliia Perova Harvard.
Learning Target Cycles Chris Coombes
Comparison of Student Learning in Challenge-based and Traditional Instruction in Biomedical Engineering Others: Taylor Martin, Stephanie D. Rivale, and.
Using Worked Examples Dr. Mok, Y.F..
Effectiveness of the ‘Change in Variable’ Strategy for Solving Linear Equations Mustafa F. Demir and Jon R. Star, Michigan State University Introduction.
July 8, 2008In vivo experimentation: 1 Step by Step In Vivo Experimentation Lecture 3 for the IV track of the 2011 PSLC Summer School Philip Pavlik Jr.
Pathways to Flexibility: Leveraging Comparison and Prior Knowledge Bethany Rittle-Johnson Jon Star Kelley Durkin 1.
The Role of Prior Knowledge in the Development of Strategy Flexibility: The Case of Computational Estimation Jon R. Star Harvard University Bethany Rittle-Johnson.
Developing Procedural Flexibility: When Should Multiple Solution Procedures Be Introduced? Bethany Rittle-Johnson Jon Star Kelley Durkin.
Using Comparison to Support Mathematics Knowledge: From the Lab to the Classroom Bethany Rittle-Johnson Jon Star Kelley Durkin.
Core Mathematics Partnership Building Mathematical Knowledge and
CHAPTER 3 Teaching Through Problem Solving
Elementary and Middle School Mathematics Chapter Reflections: 1,2,3,5,6 By: Amy Howland.
Instructional Coaching in the Elementary Mathematics Classroom
From the laboratory to the classroom: Creating and implementing a research-based curriculum around the use of comparison Courtney Pollack, Harvard University Dr.
Bethany Rittle-Johnson Jon Star
Presentation transcript:

It Pays to Compare: Effectively Using Comparison to Support Student Learning of Algebra Bethany Rittle-Johnson Jon Star

IES Conference Our approach to improving students’ mathematics learning Identify instructional practices used in exemplary and typical classrooms Use cognitive science literature to focus on practices most likely to help student learning Experimentally evaluate impact of the instructional practice on student learning and develop instructional guidelines

IES Conference Potential of comparison Mathematics Education: Central tenet of reform efforts; used by teachers Cognitive Science: A fundamental learning mechanism

IES Conference Central tenet of math reforms Students benefit from sharing and comparing solution methods “nearly axiomatic”, “with broad general endorsement” (Silver et al., 2005) Noted feature of ‘expert’ math instruction Present in classrooms in high performing countries such as Japan and Hong Kong (Ball, 1993; Fraivillig, Murphy, & Fuson, 1999; Huffred-Ackles, Fuson, & Sherin Gamoran, 2004; Lampert, 1990; Silver et al., 2005; NCTM, 1989, 2000; Richland et al 2007; Stigler & Hiebert, 1999)

IES Conference Used in some Algebra textbooks Sobel, M.A., Maletsky, E. M., Lerner, N., & Cohen, L.S. (1985) Algebra One, Harper and Row Inc.

IES Conference But does comparison improve student learning? No evidence that comparison improves student learning in mathematics Cognitive science research suggests that it should…

Comparison in cognitive science “The simple, ubiquitous act of comparing two things is often highly informative to human learners…. Comparison is a general learning process that can promote deep relational learning and the development of theory-level explanations” (Gentner, 2005, pp. 247, 251)

IES Conference Fundamental learning mechanism Lots of evidence from cognitive science ◦ Identifying similarities and differences in multiple examples is an important pathway to flexible, transferable knowledge Mostly laboratory studies Rarely done with school-age children or in mathematics (Catrambone & Holyoak, 1989; Gentner, Loewenstein, & Thompson, 2003; Gick & Holyoak, 1983; Kurtz, Miao, & Gentner, 2001; Loewenstein & Gentner, 2001; Namy & Gentner, 2002; Oakes & Ribar, 2005; Schwartz & Bransford, 1998)

IES Conference Does comparison support math learning? Goal of our IES grant ◦ Investigate whether comparison can support conceptual and procedural knowledge of equation solving (and estimation) ◦ Explore what types of comparison are most effective ◦ Experimental studies in intact classrooms

IES Conference Why equation solving? Often students’ first exposure to abstraction and symbolism of mathematics Area of weakness for US students (Blume & Heckman, 1997; Schmidt et al., 1999) According to NCTM and National Math Panel Report, linear equation solving should be a focal point of math instruction in middle school Although real-world contexts and informal solution methods are powerful for simple problems, equations and equation solving are more effective for complex problems (Koedinger, Alibali & Nathan, 2008)

IES Conference Multiple methods for solving equations Method #1: 3(x + 1) = 15 3x + 3 = 15 3x = 12 x = 4 Method #2: 3(x + 1) = 15 x + 1 = 5 x = 4 ◦ Some are better than others ◦ Students tend to memorize only one method ◦ Example: Solving 3(x + 1) = 15

IES Conference Study 1 Research question: Does comparing solution methods improve equation solving knowledge? Research design: Randomly assigned to: ◦ Comparison condition  Compare and contrast alternative solution methods ◦ Sequential condition  Study same solution methods sequentially Rittle-Johnson, B. & Star, J.R. (2007). Does comparing solution methods facilitate conceptual and procedural knowledge? An experimental study on learning to solve equations. Journal of Educational Psychology.

IES Conference Translation to the classroom Students study and explain worked examples with a partner Based on core findings in cognitive science -- the advantages of: ◦ Worked examples (e.g. Sweller, 1988) ◦ Generating explanations (e.g. Chi et al, 1989; Rittle-Johnson, 2006) ◦ Peer collaboration (e.g. Fuchs & Fuchs, 2000)

IES Conference Comparison condition

IES Conference Sequential condition next page

IES Conference Predicted outcomes Students in comparison condition will make greater gains in: ◦ Procedural knowledge, including success on novel problems ◦ Procedural flexibility (e.g. use more efficient methods; evaluate when to use a procedure) ◦ Conceptual knowledge (e.g. equivalence)

IES Conference Study 1 Method Participants: 70 7th-grade students and their math teacher Design: ◦ Pretest - Intervention - Posttest ◦ Replaced 2 lessons in textbook ◦ Intervention occurred in partner work during 2 1/2 math classes Intervention: ◦ Randomly assigned to Compare or Sequential condition ◦ Studied worked examples with partner ◦ Solved practice problems on own

IES Conference Procedural knowledge assessment Equation Solving ◦ Intervention: 1/3 (x + 1) = 15 ◦ Posttest Familiar: -1/4 (x – 3) = 10 ◦ Posttest Novel: 0.25 (t + 3) = 0.5

IES Conference Procedural flexibility Use of more efficient solution methods on procedural knowledge assessment Knowledge of multiple methods ◦ Solve each equation in two different ways ◦ Evaluate methods: Looking at the problem shown above, do you think that this way of starting to do this problem is a good idea? An ok step to make? Circle your answer below and explain your reasoning. (a) Very good way (b) Ok to do, but not a very good way (c) Not OK to do

IES Conference Conceptual knowledge assessment

IES Conference Gains in procedural knowledge F(1, 31) =4.49, p <.05

IES Conference Flexible use of procedures Solution MethodComparisonSequential Conventional.61 ~.66 Demonstrated efficient.17 *.10 Solution Method at Posttest (Proportion of problems) ~ p =.06; * p <.05 Comparison students more likely to use more efficient method and somewhat less likely to use the conventional method

IES Conference Gains in flexible knowledge of procedures F(1,31) = 7.73, p <.01

IES Conference Gains in conceptual knowledge No Difference

IES Conference Summary of Study 1 Comparing alternative solution methods is more effective than sequential sharing of multiple methods ◦ Improves procedural transfer and flexibility ◦ In mathematics, in classrooms

IES Conference Comparison can help: Now what? Replicated findings for fifth graders learning computational estimation Goal: Develop guidelines for using comparison to support mathematics learning Starting Point: Standard classroom practices

IES Conference What are teachers doing? US teachers use comparison in 8th grade math lessons (average 4 per lesson) Types of comparisons (used with equal frequency): 1.Compare two similar problems with same basic solution 2.Compare two moderately similar problems or solutions 3.Compare a problem to a mathematical rule or principle 4.Compare a problem to a non-mathematical situation (Richland, Holyoak & Stigler, 2004 analysis of TIMSS videos)

IES Conference What are teachers doing? May not be using comparison well ◦ Teachers, rather than students, initiate comparisons and make links between examples ◦ When they present multiple solutions, rarely provide support for or discuss comparisons ◦ Don’t know which types of comparison support learning  e.g. Comparisons to contexts from different domains rarely support learning in laboratory studies. (Richland, Holyoak & Stigler, 2004; Richaland, Zur & Holyoak, 2007; Chazan & Ball, 1999)

IES Conference What about Algebra I textbooks? Compare two similar problems with same basic solution method (Equivalent Equations) Bellman,A.E., Bragg,S.C., Charles, R.I., Hall,B., Handlin, W.G., & Kennedy, D. (2007) Algebra 1, Pearson Education Inc, Pearson Prentice Hall

IES Conference Hollowell, K.A., Ellis, W., & Schultz, J.E. (1997). HRW Algebra. Holt, Rinehart, & Winston. Algebra I textbooks Compare problems with different structures (Different Problem Types )

IES Conference Algebra I textbooks Sobel, M.A., Maletsky, E. M., Lerner, N., & Cohen, L.S. (1985) Algebra One, Harper and Row Inc. Compare different solution methods to same problem (Solution Methods)

IES Conference Comparison in Algebra 1 textbooks Type of ComparisonPercent of worked examples Equivalent equations (similar problems; same method) 33% Different problem types (diff probs, solved same way) 1% Solution methods (one problem solved in two ways) 19% None - single worked examples47% Informal analysis of 10 Algebra I textbooks - chapter on multi-step linear equations

IES Conference What should be compared? Variety of comparisons are being used in math classrooms What are benefits and drawbacks to different types of comparisons? ◦ Study 1 confirms that comparing solution methods aids learning, as suggested by expert teaching practices ◦ Cognitive science literature suggests that comparing two problems solved with the same solution method should benefit learning

IES Conference Study 2 Research question: What are the relative merits of comparing solution methods vs. comparing problems? Research design: Randomly assigned to: ◦ Compare solution methods ◦ Compare problems that:  Are very similar (Equivalent)  Have different problem features (Different problem types)

IES Conference Types of comparison Solution Methods (one problem solved in 2 ways) Problem Types (2 different problems, solved in same way) Equivalent (two similar problems, solved in same way)

IES Conference Study 2 Method Participants: 161 7th & 8th grade students from 3 schools (more diverse sample) Design: ◦ Pretest - Intervention - Posttest - 2 week Retention ◦ Replaced 3 lessons in textbook ◦ Randomly assigned to  Compare Solution Methods  Compare Problem Types  Compare Equivalent ◦ Intervention occurred in partner work ◦ Assessment adapted from Study 1

IES Conference Conceptual knowledge results F (2, 153) = 5.76, p =.004,  2 =.07 *

IES Conference Procedural knowledge results No differences, even on novel problem types

IES Conference Flexible use of procedures F (2, 153) = 4.96, p =.008,  2 =.06 *

IES Conference Flexible knowledge of procedures F (2, 153) = 5.01, p =.008,  2 =.07 *

IES Conference Summary Across studies, Comparing Solution Methods often supported the largest gains in conceptual knowledge, procedural knowledge and procedural flexibility ◦ Supported attention to multiple methods and their relative efficiency, which both predicted learning

IES Conference Guidelines for using comparison Provide a written record of examples ◦ Leverage current use of worked examples in textbooks Contrast important dimensions in the examples, such as problem features or solution methods ◦ Contrasting correct and incorrect solution methods can help too (Kelley Durkin, IES pre-doc research) Have students compare a familiar method to an unfamiliar method Invite comparisons by using common labels and prompting for specific comparisons, including efficiency of the methods Be sure students, not just teachers, are comparing and explaining Incorporate some direct instruction

What’s next? Teacher Professional Development for using comparison in Algebra I courses Type of comparison matched to prior knowledge and sequencing different types of comparison

IES Conference Acknowledgements For slides, papers or more information, contact: Funded by a grant from the Institute for Education Sciences, US Department of Education Thanks to research assistants at Vanderbilt: ◦ Holly Harris, Shanelle Chambers, Jennifer Samson, Anna Krueger, Heena Ali, Kelley Durkin, Kelly Cashen, Calie Traver, Sallie Baxter, Amy Goodman, Adam Porter, John Murphy, Rose Vick, Alexander Kmicikewycz, Jacquelyn Beckley and Jacquelyn Jones And at Michigan State: ◦ Kosze Lee, Kuo-Liang Chang, Howard Glasser, Andrea Francis, Tharanga Wijetunge, Beste Gucler, and Mustafa Demir And at Harvard: ◦ Martina Olzog, Jennifer Rabb, Christine Yang, Nira Gautam, Natasha Perova, and Theodora Chang