Showing posts with label RME. Show all posts
Showing posts with label RME. Show all posts

RME 6: Opening Keynote - Moving from Disowning to Owning Realistic Mathematics Education


Frank Eade, Ministry of Education, Cayman Islands
David Webb, School of Education, University of Colorado Boulder

Frank Eade
The point of this keynote was to describe Realistic Mathematics Education from the experience of two of its strongest proponents, Frank Eade of the Cayman Islands and David Webb of the United States. With Grand Cayman as a new location for this conference, and many educators coming to an RME conference for the first time, the keynote was designed to describe experiences that any math teacher could relate to.

Frank described his early experiences as a math teacher in the UK. There were influences of New Math from the US, and a sense that things could be changing, but the expectation was to teach traditionally. David's early experiences as a teacher, teaching high school in 1980s Los Angeles, was that instruction was largely teacher-oriented. People talked about group work, but not without much of a sense of purpose. People focused on procedure and problem solving only came at the end after the procedures had been learned.

David Webb
Frank began to learn about dilemmas with students' mathematical experiences. For example, if you ask students to put 0.375, 0.7, and 0.32 in order, many students will say 0.375 is the smallest because it has thousandths, and thousandths are the smallest. Frank read this in research and didn't want to believe it, so he tried it with his own students. They replicated the research, revealing to him that he'd been totally unaware of their misconceptions. He talked to them about why they believed what they did, and got answers like "It's a bit like negative numbers --- the smaller it is, the larger it is." David knew he could organize his entire curriculum around a procedural textbook and hand out worksheets. Students didn't seem to mind and figuring out how to do group work seemed like an uphill battle. Change meant fighting the didactical contract students had formed with their math teachers over many years.

Frank's first experiences with RME came when he visited the University of Amsterdam and some schools there. He observed 7/8 students comparing 2/3 to 3/4. He figured students would answer as his would -- that the fractions were the same because in each fraction you could add one to the numerator to get the denominator. Instead, he saw students drawing pictures and using those pictures to argue their reasoning. The only student he observed who reasoned incorrectly was someone who recently moved there. He started to become a convert. David entered graduate school after 7-8 years of teaching and ended up at Wisconsin with Tom Romberg. His assignment as a grad student was to align every activity in Math in Context to the NCTM Curriculum Standards. There were 30 MiC units, so it was a lot of work, but it gave him a detailed look at RME's approach to curriculum design. Sometimes he was in disbelief about the kind of reasoning that was expected of students before procedural understanding had developed. But as he observed students in classrooms, he became a believer as students approached problems informally but expressed all the reasoning they would need to understand the problem formally.

Frank and David describing models and progressive formalization
Frank's experience with RME curriculum design was part of a MiC pilot. A teacher who was supposed to try a unit for 3 weeks ended up stretching the unit for 10 weeks because kids were so engaged in all the mathematical reasoning -- and because they all had a lot to learn about how to implement and pace a different kind of curriculum. This led to multiple grant-funded projects both to develop new curriculum and to study its implementation. David's experience with design in RME came at the end of the MiC project as focus shifted to implementation and assessment. He had the opportunities to travel the country and offer PD and learn from teachers who needed support to understand the principles of RME and, maybe more importantly, to redefine the roles of teacher and learner in their classrooms.

3A + 2P = $9.20
1A + 2P = $5.20

Frank gave the above problem to a group of students with experience with RME, but they were scared of the symbolic notation. Then one student in the room said, "Wait, it's hats and umbrellas!" (a problem in Math in Context) and the rest of the class caught on and they were able to reason with the mathematics. They had seen the hats and umbrellas problem 2 years before, but the reasoning had stuck with them. David's work with assessment bridged the divides between RME and formative assessment. It was yet another way to rethink what it meant for students to understand mathematics. David began to promote the use of the assessment pyramid, even for teachers to think about how they arrange the bulk of their assessments they use in their classrooms. "Students are capable of solving fascinating problems -- we just have to ask them."

Frank was talking to his wife about math and asked her to explain how she got an answer to a particular fraction problem. She said, "I cheated. I imagined it, but I know I'm supposed to find the common denominator." Here in the Caymans, Frank has worked with students who have struggled but are now seeing the math in their worlds in new ways. RME isn't totally different from other approaches to mathematics, but some distinctions are useful. It's important for teachers to see their role in orchestrating students' mathematical experiences, and not just facilitate. The use of models is fundamental to RME's design, and teachers need to understand that approach to be successful.

When Frank introduced RME to the Caymans, he first visited every classroom to get a sense for the current state of math education on the islands. Staff turnover tends to be high in the Caymans. He found that many children didn't have a sense of shopping and the values of things, so those were opportunities to work those contexts into the curriculum. Students needed more support, so they introduced Mathematics Recovery. Interventions outside the classroom were far more fruitful in helping students because teachers struggled with interventions within the classroom. They employed lesson study to help teachers understand how lessons could be taught, and to address their own experiences with traditional instruction. At the end of primary in 2011, only 25% of students were expected and only 5% were above. At the end of primary in 2018, 62% were expected and 25% were above. That said, Frank says there is great danger in looking at scores like this too much, as we don't want teachers to become too focused on exam success as a measure of achievement.

On Major Problems and Grand Challenges, Part 1

Last month the NCTM Research Committee asked its members to help it identify the grand challenges for mathematics education. Grand challenges, said NCTM, (a) are hard yet doable, (b) affect millions of people, (c) need a comprehensive research program, (d) are goal-based with progress we can measure, and (e) capture the public's attention and support. I'm a month too late to contribute to NCTM's survey, and before blogging my thoughts into the wider conversation I thought I should look back at someone else's previous attempt. Maybe I'd gain some perspective on what grand challenges are and how persistent they might be.

Hans Freudenthal (Wikimedia Commons, CC-BY-SA)
In 1980, Hans Freudenthal gave a plenary address at ICME that later turned into an article in Educational Studies in Mathematics titled, Major Problems of Mathematics Education. I've briefly summarized the article on the MathEd Wiki and here I'll note the progress I think we've made on Freudenthal's 11 problems.
  1. Freudenthal believed we "need[ed] more pardigmatic cases, paradigms of diagnosis and prescription, for the benefit of practitioners and as bricks for theory builders" (p. 135). In the case of arithmetic, which was Freudenthal's example, I think Cognitively Guided Instruction (CGI) is very much the kind of thing Hans was looking for.
  2. Freudenthal wanted us to more carefully consider how people learn and observe their learning processes. I think several decades of teachers' awareness of constructivist theories of learning has changed how most people think of learning, and newer work in the area of teacher noticing puts fine points on what teachers notice and why.
  3. How do we design curriculum and instruction around progressive formalization? There is always more to learn, but the Freudenthal Institute in the Netherlands has now worked on this for decades and the frameworks for curriculum design are well-established.
  4. How do we retain and leverage mathematical insight? Freudenthal wrapped this into the conceptual vs. procedural debate, one that's still very much alive. However, I think we have better examples of productive approaches to this problem, and some research results (the BEAR project work at Berkeley comes to mind) showed that more focus on the conceptual didn't come at the expense of procedural facility. Still, this problem gets wrapped up in people's beliefs about mathematics and the teaching and learning of mathematics, and those beliefs sometimes aren't swayed by current evidence.
  5. How do we reflect on our learning? This is another problem we now know much more about, particularly due to Schoenfeld and his work on metacognition.
  6. How do we develop a mathematical attitude? This is still a challenge, and not just because some students say they don't like math. I think this problem might be closest to what Jo Boaler is currently trying to change with her focus on mindsets in learning mathematics.
  7. How do we coordinate students working together when the are at different levels of learning? Many teachers and scholars have worked quite hard on this problem and I feel like most teachers now see the benefit of heterogeneous ability groups. For more, I'd suggest Ilana Horn's book, Strength in Numbers.
  8. How do we create contexts for mathematizing? I think there's been a wealth of work in this area, from work based in Realistic Mathematics Education, work on word problems like that from Verschaffel, Greer, and de Corte, and, most recently, Dan Meyer's work. I could go on, as there are many more examples, and perhaps future work will give us a clearer picture about which contexts work best and why.
  9. Can we teach geometry by having the learner reflect on spatial intuitions? Maybe it's my lack of expertise in geometry education research, but I really don't know where we stand on this problem. Freudenthal seemed to be reaching in his article on this problem, and maybe a more tangible articulation of the problem would have helped me better judge any solutions we might have.
  10. How can technology increase mathematical understanding? Freudenthal admitted not being tech-savvy even in 1981 (he used "the ballpoint" as an example of technology that changed instruction, and not in an obviously historical way), but I think we now have numerous examples of tech that helps increase understanding. We also have a lot of examples of tech that doesn't, and I'm sure Freudenthal would have seen problems in our ability to judge the good from bad.
  11. How do we use a holistic approach to educational development for change? In his native Netherlands, Freudenthal would likely be pleased today to see his colleagues' commitment to design-based, participatory approaches to research. We have some of that here in the U.S., too, but we also struggle for a "scientific" approach to finding "what works" based on experimental studies. We also have too much faith in how standards affect change; if Freudenthal thought curriculum development for change was a wrong perspective, surely he'd think the same about standards. Those things are just part of a much bigger picture.
Looking at this list, I think we have a lot to be proud of. Even though Freudenthal's article wasn't some sort of directive or command to fellow and future math education researchers and teachers, many people over many years worked so we'd have some answers to these questions. Still, there's a gap between ''what the field of math ed knows'' and ''what a teacher does with this knowledge, if they know it," which hints at what might be a grand challenge of its own. I'd like to get to that, but in a later post. Next, I'll look at some of the grand challenges that I've seen others post on the web in response to NCTM's call for input.

RYSK: Cobb, Zhao, & Visnovska's Learning From and Adapting the Theory of Realistic Mathematics Education (2008)

This is the 21st in a series describing "Research You Should Know" (RYSK).

It's Open Access Week (#OAweek) so I thought it would be fitting to use this "research you should know" post to highlight one of my favorite open access articles in mathematics education, Learning From and Adapting the Theory of Realistic Mathematics Education by Paul Cobb, Qing Zhao, and Jana Visnovska. Because the article is open access, I get to be less interested in summarizing it and more interested in giving you a reason to read it.

Realistic Mathematics Education (RME) is a theory for the design and development of mathematics curriculum. It is still deeply rooted in the Netherlands, where Hans Freudenthal greatly influenced mathematics instruction there with his belief that mathematics was a human activity, and that activity was characterized by mathematizing the real or readily imagined world. ("Realistic" comes from the Dutch phrase "zich realiseren," which in English means "to imagine.") This mathematization can be thought of in two ways, horizontal and vertical: "horizontal mathematization involves going from the world of life into the world of symbols, while vertical mathematization means moving within the world of symbols" (Freudenthal, 1991). Hans Freudenthal died in 1990 but his work continues, primarily at the Freudenthal Institute for Science and Mathematics Education at the University of Utrecht in the Netherlands.

There have been four primary avenues where RME has established itself in the United States. The first is with the middle school curriculum series Mathematics in Context, which grew from a partnership between mathematics education researchers at the University of Wisconsin (primarily Thomas Romberg) and researchers at the Freudenthal Institute. The second is the K-8-focused work of Mathematics in the City, which primarily brought together Cathy Fosnot from the City College of New York and Maarten Dolk of the Freudenthal Institute. The pair also wrote most of the Young Mathematicians at Work book series. The third place where RME is established in the U.S. is here at CU-Boulder, home of Freudenthal Institute US and its director, David Webb. David worked on the Mathematics in Context project at Wisconsin, and brought FI-US with him to CU-Boulder. The fourth place I recognize RME having a significant influence in the United States is in the work of Paul Cobb, particularly in his long research partnership with Koeno Gravemeijer, a researcher from the Freudenthal Institute. Cobb and Gravemeijer spent more than a decade working and publishing together, and that work did a lot to strengthen ties between RME as a design theory and theories in the learning sciences.

Like any idea or theory, RME has limitations. Over its 40+ years of existence it's proven to not be a static thing (van den Heuvel-Panhuizen, 2002), and this article by Cobb, Zhao, & Visnovska describes some of the important ways their work has both informed and been influenced by RME. They describe three adaptations: the first involves accounting for classroom activity and discourse in RME, the second acknowledges the mediating role of the teacher in making curriculum modifications and adaptations, and the third looks at how RME can focus on teacher learning, not just student learning. For details, I'll let you read the article for yourself at http://educationdidactique.revues.org/276. If you have any questions about the article or RME, leave a comment, find me on social media, or email me. We RME folks want to spread the word!

References

Freudenthal, H. (1991). Revisiting Mathematics Education: China Lectures. Dordrecht: Kluwer.

van den Heuvel-Panhuizen, M. (2002). Realistic Mathematics Education as work in progress. In F. L. Lin (Ed.), Common Sense in Mathematics Education: Proceedings of 2001 The Netherlands and Taiwan Conference on Mathematics Education (pp. 1–39). Taipei, Taiwan.

RME4: Webb's Opening Remarks

Opening Session - Friday, September 27, 2013

David Webb - Executive Director of Freudenthal Institute US and Associate Professor of Mathematics Education, University of Colorado Boulder

David Webb
David Webb welcomed us to the 4th International Realistic Mathematics Education Conference (#RME4) by addressing a shift in organizational structures. What used to be simply the Freudenthal Institute in the Netherlands is now the Freudenthal Institute for Science and Mathematics Education, and its American counterpart, Freudenthal Institute US, is now part of a larger CU-Boulder effort known as the Center for STEM Learning. These shifts reflect a desire to not just have cooperation between mathematics and science disciplines, but a perceived need to create innovative new STEM curricula along with the supporting frameworks, teacher education, and professional development to support it. Webb announced that earlier in the week that FISME and the Center for STEM Learning had formally agreed to collaborate, although we'll have to wait and see how this collaboration takes shape.

At its core, RME is a set of principles for curriculum design. It is sensible, then, to seek common ground in mathematics and the sciences for ideas upon which we can design curriculum. Some of that common ground is found in how we reason in math and science, and Webb offered these four activities:

  • Recognition of patterns
  • Making conjectures from observation
  • Reasoning from evidence
  • Generating new evidence

From these, we can think about how we consider the acts of modeling, problem solving, generalizing, and proving in both math and science. There are similarities and differences, and these things are meant as a starting point, not a definitive list. Perhaps the most fundamental RME principle is that of progressive formalization (see here for an example), so we must also think about how informal contexts can be used in both math and science, as well as the preformal models and representations that support more formal kinds of student thinking. Webb encouraged us to consider these RME traditions as we stretched ourselves beyond our usual disciplines, and with that the conference was underway.

NCTM Denver 2013: Abels, Matassa, & Johnson's Making Sense of Algebra with Realistic Mathematics Education

Annual Meeting - Thursday, April 18, 2:45 pm

Mieke Abels - Freudenthal Institute for Science and Mathematics Education, University of Utrecht
+Michael Matassa Jr. - Freudenthal Institute US, University of Colorado Boulder
+Raymond Johnson - Freudenthal Institute US, University of Colorado Boulder

When it came time to propose session for the 2013 NCTM Annual Meeting in nearby Denver, we at the Freudenthal Institute US at CU-Boulder knew we should have some kind of "Intro to RME" workshop. Because I was already proposing to be a lead speaker on another session, I needed to find someone else to take the lead. Michael Matassa said he would do it, but then +David Webb had a better idea: Why not ask Mieke Abels from the Freudenthal Institute to do it? Mieke would be a perfect choice - she's been involved in FIUS from the beginning and she continues to be involved in curriculum development for Mathematics in Context and curriculum in the Netherlands. Happily, Mieke agreed and Michael and I were happy to back her up as co-presenters.

The picture at the top is Nederland, CO, which is amusing to our Dutch colleagues

Our goal in this presentation was to bring out the curriculum design features and give attendees a sense for informal and preformal approaches to algebra for the middle grades. Too often it seems "early algebra" gets interpreted as "algebra early," as if a school could just box up their high school algebra textbooks and ship them down to the middle school. Making big jumps to formal mathematics is risky, and that's one reason Realistic Mathematics Education (RME) adheres to a principle called progressive formalization. To illustrate, we started with a task you could give to 6th graders, or perhaps even younger students.

Tug-of-war, taken from Mathematics in Context

Those of us who have mastered formal algebra tend to want to write equations for this and solve. But for young students, RME design principles suggest we support students by relying on a "realistic" context. While "real-world" contexts are certainly realistic, RME's use of "realistic" means it can be imagined by the learner. The power of the context is not necessarily its authenticity, but its capacity to be mathematized.

On the tug-of-war task students will inevitably find different ways to substitute different animals for each other until it becomes clear which side would win the tug-of-war. Some students will likely try to redraw the animals, while others might use letters ("E" for elephant, etc.) as a substitute. Even though a formal equation might use "E" to represent the pulling strength of an elephant, it's fully expected at this stage for students to try writing things like "E = O + 2H" to represent the animals in the middle of the above slide, and interpret "2H" simply as the abbreviation "2 horses."

The Iceberg Metaphor

The concept of progressive formalization is often represented with the iceberg metaphor (Boswinkel & Moerlands, 2003; Webb, Boswinkel, & Dekker, 2008), which places formal mathematics above the water line. The tip of the iceberg is only supported because of the iceberg's "floating capacity, which is where informal and preformal mathematics is placed. Examples like the tug-of-war problem are informal because they rely almost entirely on the realistic context with little or no mathematical abstraction.

Here's another example of an informal task:

Three Frogs, taken from Mathematics in the City

Again, the frog jumping doesn't have to be something replicable in the real world. It need only exist in the imagination of the student, and to solve it students need to find ways to represent the jumps and steps in their work. At this point students will have worked often with number lines (including open number lines) and easier problems involving frog jumping, making number lines a natural model for this problem, like this:

Using an open number line to represent Sunny's jumps

The nature of this problem and the need to draw double number lines that end in a particular place helps students consider what it means to be variable in this problem, versus what quantities remain constant. Other types of problems with other contexts use other kinds of models. For example, the familiar model of a balance is used in RME-based curricula (the 1 and 5 represent weights):

The balance model, found in the Digital Mathematics Environment

Student work for these kinds of tasks can be an indicator of where in the formalization process students might be. If students are redrawing pineapples and lemons, they are still working at an informal level. For convenience they might replace pineapples and lemons with letters, suggesting a small amount of formalization, and eventually they'll be using those letters to write equations and not need to think in terms of the fruit and the balance. Just like tug-of-war, the balance model suggests an understanding of equals that is relational, which helps students who tend to interpret equals as operational.

The use of models is at the heart of the preformal level of the iceberg. Nearer the bottom we would place models of informal contexts. For example, a student who draws sectors of a circle to represent a fraction of a pizza is using the circle as a model of the pizza. Nearer the top of the preformal level we would place models for mathematical abstraction. The student who uses sectors of a circle to represent a fraction of seats occupied in a bus is using the sectors of the circle as a generalized representation of a part and whole, and not a specific representation of a bus. In RME students become familiar with many models, such as number lines, open number lines, double number lines, ratio tables, five frames, rekenreks, area models, and balance models.

Models are key at the preformal level of the iceberg

Another preformal model useful for systems of equations is notebook notation. Here a problem shows two combinations of long and short candles. Working informally, students would find some combination of candles that makes the problem solvable, such as doubling the second combination to make two long candles and two short candles for $6.80. Since the top arrangement has one more short candle and is a dollar more, then short candles must cost $1.00. A preformal way of working with these combinations is notebook notation:

Notebook Notation, taken from Mathematics in Context

From the notebook it becomes easier to see how students will learn to write and manipulate formal systems of equations. The column headings become the variables, and equal signs are placed in front of the total. Formal matrix notation is reachable from notebook notation as well.

Although progressive formalization is often presented as a direct informal-to-preformal-to-formal process, it is not expected that students will learn this way. Students who can work formally or preformally with easier problems are likely to reach to a lower level when problems become more difficult. Because they have achieved the formalization with easier problems, they become more likely to formalize more difficult problems when they can reason with less formal strategies when necessary.

Another way to view progressive formalization is with a learning trajectory, which connects specific contexts and representations along a path towards formal mathematics. Creation of both iceberg models and learning trajectories can be a productive activity for professional development and curriculum planning and alignment.

A learning trajectory for equations and systems of equations, with connecting links

RME isn't meant to be deeply complex, but contexts, models, and the connections between them need to be carefully chosen. Curriculum developers at the Freudenthal Institute take a design research approach to this work, testing and revising in iterative cycles to improve the curriculum over time. FI (formerly IOWO) was founded by Hans Freudenthal in 1971, giving the Netherlands over 40 years to gradually improve their mathematics curriculum and teaching. This type of adherence to a core philosophy for so long is generally unknown in education in the U.S., but schools in the Netherlands have used it to score near the top of international rankings on the mathematics portion of the PISA assessment.

If you'd like more information about RME, the following might be of interest:
References

Boswinkel, N., & Moerlands, F. (2003). Het topje van de ijsberg [The top of the iceberg]. De Nationale Rekendagen, een praktische terugblik [National conference on arithmetic, a practical view] (pp. 103–114). Utrecht, The Netherlands: Freudenthal Institute. Retrieved from http://www.fisme.science.uu.nl/publicaties/literatuur/5467.pdf

Van Reeuwijk, M. (2001). From informal to formal, progressive formalization an example on “solving systems of equations”. In H. Chick, K. Stacey, J. Vincent, & J. Vincent (Eds.), The future of teaching and learning of algebra: The 12th ICMI study conference (pp. 613–620). Melbourne, Australia. Retrieved from http://repository.unimelb.edu.au/10187/2812

Webb, D. C., Boswinkel, N., & Dekker, T. (2008). Beneath the tip of the iceberg: Using representations to support student understanding. Mathematics Teaching in the Middle School, 14(2), 110–113. Retrieved from http://www.nctm.org/publications/article.aspx?id=20793.

Planning for NCTM 2013

It's going to be a busy, busy week. The advantage of having a major conference in your backyard is that you feel like you can go to everything, but the disadvantage is the feeling you should be going to everything despite local distractions and responsibilities that don't go away. I try to get my money's worth at conferences; I think when I went to the Annual Meeting in 2008 in Salt Lake City I attended 17 sessions across the four days. We'll see if I set a new personal record this year. I'll be attending both the Research Presession and the Annual Meeting and have attempted to describe my schedule below.

RME at NCTM

Before getting into what I hope to attend, there are a number of opportunities to learn about Realistic Mathematics Education at this year's conference. I don't have a definitive list, but these are the RME-related sessions I'm aware of:

Tuesday


1:00 - Marja van den Heuvel-Panhuizen, Marc van Zanten, et al (Room 103, Colorado Convention Center)
Mathematics Curriculum Design and Development in the East and West

4:45 - +Fred Peck (Lobby A, Colorado Convention Center)
How Do Students Reinvent Their Mathematics? A Study Involving Slope

Thursday


2:45 - Mieke Abels, +Michael Matassa Jr., & +Raymond Johnson (Mile High 3 A, Convention Center)
Making Sense of Algebra with Realistic Mathematics Education

2:45 - +David Webb (Centennial Ballroom G/H, Hyatt Regency)
Promoting Student Reasoning and Understanding by Using Representational Pathways

(Putting Mieke and David head-to-head in the schedule was not something we RME folks wanted, but that's the way it is.)

Friday


12:30 - +Ryan Grover (702, Convention Center)
lim_{calculus → RME} f(calculus) = :-D

Saturday


10:00 - Britannica Digital Learning (Exhibitor Workshop, 304, Convention Center)
Meeting the Practice Standards with Models from Math in Context



My Schedule

(Yes, I overschedule. It's good practice for when sessions are full, get cancelled, or when you just can't decide.)

Monday

5:30 - Jacqueline G Van Schooneveld (Lobby A, Colorado Convention Center)
Lesson Plan Evaluation Instrument: Assessing Math Lesson Plans

5:30 - Janet Mercado, Rossella Santagata, & Sonja Mohr (Lobby A, Colorado Convention Center)
Mathematics Knowledge and Beliefs and Their Relationships in Preservice Teachers

7:00 - Kenneth Zeichner (Rooms 205/207, Colorado Convention Center)
The Struggle for the Soul of Teaching and Teacher Education

Tuesday

8:30 - Anne Foegen, Barbara J. Dougherty, Vickie L. Spain, Jeannette R. Olson, and Subha Singamaneni (Room 107/109, Colorado Convention Center)
Building Progress Monitoring Measures for Algebra: Exploring Items and Scores

10:30 - I'll be planning for one of my presentations on Thursday, but if I weren't I'd probably be headed to Interactive Paper Session 9 (for papers here, here, and here) or Jere Confrey's session.

1:00 - Alison Castro Superfine, James Lynn, Timothy M. Stoelinga, Mara V. Martinez, Cynthia L. Schneider, and Diane J. Briars (Room 205/207, Colorado Convention Center)
Supporting Underprepared Algebra Students: Results from a Design-Based Research Program

1:00 - +Douglas Clements, Julie Sarama, Curtis Tatsuoka, Kikumi Tatsuoka, and Elvira Khasanova (Room 107/109, Colorado Convention Center)
Using Learning Trajectories to Create Cognitively Diagnostic Adaptive Assessments

3:00 - Dawn Berk, James Hiebert, +Amanda Jansen, Anne Morris, Laura Cline, Heather Gallivan, Erin Meikle, and Emily Miller (Room 102, Colorado Convention Center)
Effects of Mathematics Teacher Preparation on Teacher Knowledge and Practice

3:00 - +Pat Herbst, Daniel Chazan, +Karl Kosko+wendy rose aaron, Justin Dimmel, Orly Buchbinder, and Ander W. Erickson (Room 104, Colorado Convention Center)

4:45 - +Fred Peck (Lobby A, Colorado Convention Center)
How Do Students Reinvent Their Mathematics? A Study Involving Slope

4:45 - +Edd Taylor and Tracey E. Dobie (Lobby A, Colorado Convention Center)
Religious Engagement and Context in Mathematical Problem Solving

4:45 - Corey Webel (Lobby A, Colorado Convention Center)
Secondary Mathematics Teachers Negotiating Obligations and Goals: Two Case Studies

4:45 - +Janine Remillard, Jacqueline G. Van Schooneveld, and Enakshi Bose (Lobby A, Colorado Convention Center)
Teacher Adaptations of Homework: A Window into Curriculum Enactment

4:45 - Sara Lohrman Hartman (Lobby A, Colorado Convention Center)
Rural School Math Coaching: Lessons from a Yearlong Case Study

Wednesday

8:30 - Geoffrey Saxe, Maryl Gearhart, Ronli Diakow, Nicole Leveille Buchanan, Jennifer Collett, Bona Kang, Kenton De Kirby, and Marie Le (Rooms 205/207, Colorado Convention Center)
Engagement in Mathematical Discussion: Linking Practices and Outcomes

10:30 - +Jo Boaler (Rooms 205/207, Colorado Convention Center)
Using Research to Make a Difference

1:00 - +Janine Remillard, Ok-Kyeong Kim, Luke Reinke, Napthalin A. Atanga, Joshua Taton, Dustin O. Smith, Hendrik Van Steenbrugge, and Shari Lewis (Room 105, Colorado Convention Center)
Using Curriculum Materials to Design and Enact instruction

3:00 - Interactive Paper Session 22 (papers here, here, and here, Room 110/112, Colorado Convention Center)

5:30 - Mayim Bialik (Bellco Theater, Convention Center)
The Power of Just One Teacher

Thursday

(If you can't find good sessions on Thursday, I'm pretty sure you're at the wrong conference. I wish I could be in multiple places at once!)

8:00 - +Douglas Clements and Julie Sarama (Capitol Ballroom 4, Hyatt Regency)
Math Lessons from Research

8:00 - Daniel Chazan, Mark Driscoll, and Megan Franke (Mile High 1 C/D, Convention Center)
Teaching and Learning of Algebraic Thinking: Research Insights

9:30 - Daniel Chazan (207, Convention Center)
Algebraic Thinking When Solving Equations and Doing Word Problems

10:30 - I'll be using this for last-minute planning for my afternoon sessions. If you think you might be interested in graduate studies in mathematics education, I'd recommend the 11:30 talk from +Amy Ellis+Anita Wager, and Eric Knuth in 704/706 of the Convention Center.

12:30 - +Alan Schoenfeld (Four Seasons 2/3, Convention Center)
Meeting the Challenges of the Common Core Standards
(I'm sure I'll miss this one, but I hope it's on MathRecap.)

1:00 - +Raymond Johnson and +Susan Thomas (Mineral Hall D/E, Hyatt Regency)
Statistical Reasoning in the Middle School

2:45 - +Mieke Abels+Michael Matassa Jr., and +Raymond Johnson (Mile High 3A, Convention Center)
Making Sense of Algebra with Realistic Mathematics Education

Friday

8:00 - Doug Sovde (Four Seasons 1, Convention Center)
PARCC: An Interactive Progress Update

9:30 - Steven Leinwand (Four Seasons 1, Convention Center)
Essential Mindsets for Tilling the Soil for the Common Core

11:00 - Emily Thrasher and Ayanna Franklyn (605, Convention Center)
Supporting Beginning Teachers through Online Social Communities

11:30 - Mark Ellis, Chris Stapel, and Cynthia A. Miller (704/706, Convention Center)
International Perspectives on Preparing Mathematics Teachers

12:30 - Kichoon Yang (Mile High 1 C/D, Convention Center)
NCTM Business Meeting

12:30 - +Ryan Grover (702, Convention Center)
lim_{calculus → RME} f(calculus) = :-D

2:00 - Matthew R. Larson (Mile High 1 C/D, Convention Center)
Implementing the Common Core State Standards: Five Paradigm Shifts

2:00 - Christian Hirsch (203, Convention Center)
Mathematical Modeling: The Core of the Common Core State Standards

2:45 - Heather Howell, Barbara Weren, and Shona Ruiz Diaz (110/112, Convention Center)
Mathematical Knowledge for Teaching Measures as Opportunities for Professional Learning

2:45 - NCTM Professional Development Services Committee (603, Convention Center)
Building Mathematics Learning Communities with NCTM Reflection Guides

3:30 - Francis Skip Fennell, John Wray, and Beth Kobett (Four Seasons 2/3, Convention Center)
Math Specialists Get Ready Now: Common Core Assessments Are Coming

Saturday

8:00 - Zalman Usiskin (Four Seasons 2/3, Convention Center)
Mathematical Understanding in the Common Core Standards

9:30 - Frank K. Lester (Mile High 1 C/D, Convention Center)
Whatever Happened to Problem Solving in the Math Curriculum?

9:45 - Cheryl Fricchione and Diane Austin (607, Convention Center)
An Invitation to Experience Online Lesson Study Firsthand

11:00 - +Dan Meyer (Four Seasons 1, Convention Center)
Tools and Technology for Modern Math Teaching

11:30 - Patrick Scott and Ann Lawrence (607, Convention Center)
Lessons from the U.S. National Presentation at ICME-12 in Korea

12:30 - Vi Hart and George Hart (Four Seasons 2/3, Convention Center)
Viral Math Videos: A Hart-to-Hart Conversation

Reminder: You can catch some of what you might miss at MathRecap, and if you're attending the conference I encourage you to contribute!

A Genealogy of Realistic Mathematics Education

Time sinks are curious things. Some are tedious, some are frustrating, and some turn out to be fun. A few months ago, when I probably should have been studying for my comprehensive exams, a simple conversation in the office with +Ryan Grover started a genealogical journey (academically speaking) to trace back our origins and those of Realistic Mathematics Education (RME). I'm pretty good with my mathematics education history, and I knew RME in the United States took hold with the Mathematics in Context curriculum project, bringing Thomas Romberg and others at the University of Wisconsin together with Jan de Lange and others at the Freudenthal Institute at the University of Utrecht in the Netherlands. I suggested to Ryan that we search the Mathematics Genealogy Project to see if there were other ties between U.S. math ed and the history of RME, and the time sucking began in earnest.

With Ryan searching at his desk and me at the chalkboard, after several (or 4? 5?) hours we had traced back our academic roots many generations. Here's a glimpse of that work after some un-criss-crossing of arrows by Ryan, but probably still with a few mistakes:


Ryan and I left the office after dark. When I got home, my thoughts were still consumed about organizing and preserving this history, so I stayed up most of the night creating this in Google Drawings (part of Drive/Docs), where it would be easier to edit and be more shareable:
Years indicate when doctorate(s) earned. Download large version.
I've highlighted a few individuals who I think stand out. At the top left is Nicolaus Copernicus. We could have traced back a few more generations, but beginning with the person who is famous for not putting the Earth at the center of the universe seemed like a good place to start. The next one down, in yellow, is Jakob Thomasius. Although more of a philosopher, he was advised by Friedrich Leibniz and advised his more famous son, Gottfried Leibniz, and represents an early connection between the left and right sides of the diagram. The next person down, again in yellow, is Abraham Kästner. Ryan and I had never heard of him, but he's an extraordinarily connected fellow in this chart. Five of Kästner's 10 documented students are represented here, and an unseen one, to Johann Bartels, leads directly to Nikolai Lobachevsky. Furthermore, Kästner's bio on Wikipedia reads like some stereotypically tragic mathematician's drama, having been engaged to a woman for 12 years, only to marry her and see her die within the year. So then he had a daughter with his maid and spent his later years writing poetry.

If you look around, you'll find Kant, Euler, Gauss, and others, but prominently representing an early attention to mathematics education is Felix Klein, again in yellow. Klein became interested in the teaching of mathematics around 1900, and the International Commission on Mathematical Instruction (ICMI) has named their lifetime achievement award after Klein. From Klein we establish three major lines: the U.S. line through William Edward Story, a separate U.S. line to Maxime Bôcher, and a German line through Hilbert and Bieberbach. Curiously, the tree artwork on the main page of the Mathematics Genealogy Project shows the link from Klein to Story, although neither Klein's or Story's page establish a recognized advisor-advisee relationship. After checking a few other sources, it seems that making the Klein-Story connection is typical.

Now we have three major figures in the third row from the bottom. All were trained as mathematicians but transformed themselves into prominent figures and researchers in mathematics education. On the left is Ed Begle, colored in red to reflect his association with Stanford. Begle was the director of the School Mathematics Study Group, creators of what most call the "New Math" of the 1960s and 1970s. I don't want to overgeneralize, but Begle and his descendents tend to focus on the curriculum, instruction, and policy aspects of mathematics education.

Next is Henry Van Engen, colored in purple to signify his association with Iowa State Teachers College, now known as the University of Northern Iowa (my alma mater). Van Engen's publications going back to the 1940s reveal that he was focused on learning and meaning in mathematics. Instead of relying wholly on his mathematics background, he incorporated ideas from figures like Brownell and Piaget. Van Engen left ISTC in the late 1950s to help establish the math ed program at the University of Wisconsin - Madison, and his lineage of Leslie Steffe and Paul Cobb represent one of the strongest learning science traditions in math education.

On the right is Hans Freudenthal, shown in orange to signify his place in the Netherlands. A giant figure internationally, ICMI's other major international mathematics education award is named for Freudenthal in recognition of a major cumulative program of research. Whereas I associate Begle with curriculum, and Van Engen with learning science, to me Freudenthal represents a math education visionary and philosopher, someone able to reflect broadly on the field and history of mathematics and structure a new approach to mathematics education. Interestingly, Freudenthal's involvement in mathematics education was in part inspired by Begle and the New Math -- not liking what he saw in the New Math and fearing Europe would adopt a similar approach, Freudenthal steered the Netherlands in the direction we now call RME.

There are a few hidden connections at the bottom of the diagram that reflect my experience studying RME. Being at the Freudenthal Institute US and working with David Webb is the most prominent, but I greatly anticipate opportunities to learn from our FI colleagues from the Netherlands. Paul Cobb's collaboration with Koeno Gravemeijer in the early 2000s was mutually beneficial and has influenced me greatly, as Cobb's theories of learning mathematics work well in the context of RME.

Copernicus, more than 20 generations away, tends to be less influential.



Notes: Along the way I explored a number of other connections less related to RME and my perspective of it. William Brownell, for example, can be traced back through a number of psychologists to Kastner. Alan Shoenfeld, another mathematician-turned-math educator, can also be traced back to Kastner and has two different lines back to Gauss. Kastner seemed to turn up everywhere, while Issac Newton turned up nowhere.

RYSK: Ball, Thames, & Phelps's Content Knowledge for Teaching: What Makes It Special? (2008)

This is the 17th in a series describing "Research You Should Know" (RYSK) and part of my OpenComps. I also Storified this article as I read.

My last two posts summarized the underpinnings of Shulman's pedagogical content knowledge and Deborah Ball's early work building upon and extending Shulman's theories. Now we jump from Ball's 1988 article to one she co-authored in 2008 with University of Michigan colleagues Mark Thames and Geoffrey Phelps, titled Content Knowledge for Teaching: What Makes It Special?

This article starts by looking at the 20+ years we've had to further develop Shulman's theories of pedagogical content knowledge (PCK). Despite the theory's widespread use, Ball and colleagues claim it "has lacked definition and empirical foundation, limiting its usefulness" (p. 389). (See also Bud Talbot's 2010 blog post and related efforts.) In fact, the authors found that a third of the more than 1200 articles citing Shulman's PCK

do so without direct attention to a specific content area, instead making general claims about teacher knowledge, teacher education, or policy. Scholars have used the concept of pedagogical content knowledge as though its theoretical founcations, conceptual distinctions, and empirical testing were already well defined and universally understood. (p. 394)

To build the empirical foundation that PCK needs, Ball and her research team did a careful qualitative analysis of data that documented an entire year of teaching (including video, student work, lesson plans, notes, and reflections) for several third grade teachers. Combined with their own expertise and experience, and other tools for examining mathematical and pedagogical perspectives, the authors set out to bolster PCK from the ground up:

Hence, we decided to focus on the work of teaching. What do teachers need to do in teaching mathematics -- by virtue of being responsible for the teaching and learning of content -- and how does this work demand mathematical reasoning, insight, understanding, and skill? Instead of starting with the curriculum, or with standards for student learning, we study the work that teaching entails. In other words, although we examine particular teachers and students at given moments in time, our focus is on what this actual instruction suggests for a detailed job description. (p. 395)

For Ball et al., this includes everything from lesson planning, grading, communicating with parents, and dealing with administration. With all this information, the authors are able to sharpen Shulman's PCK into more clearly defined (and in some cases, new) "Domains of Mathematical Knowledge for Teaching." Under subject matter knowledge, the authors identify three domains:
  • Common content knowledge (CCK)
  • Specialized content knowledge (SCK)
  • Horizon content knowledge

And under pedagogical content knowledge, the authors identify three more domains:
  • Knowledge of content and students (KCS)
  • Knowledge of content and teaching (KCT)
  • Knowledge of content and curriculum

Ball describes each domain and uses some examples to illustrate, mostly from arithmetic. For my explanation, I'll instead use something from high school algebra and describe how each domain applied to my growth of knowledge over my teaching career.

Common Content Knowledge (CCK)

Ball et al. describe CCK as the subject-specific knowledge needed to solve mathematics problems. The reason it's called "common" is because this knowledge is not specific to teaching -- non-teachers are likely to have it and use it. Obviously, this knowledge is critical for a teacher, because it's awfully difficult and inefficient to try to teach what you don't know yourself. As an example of CCK, my knowledge includes the understanding that \((x + y)^2 = x^2 + 2xy + y^2\). I've known this since high school, and I would have known it whether or not I became a math teacher.

Specialized Content Knowledge (SCK)

SCK is described by Ball et al. as "mathematical knowledge and skill unique to teaching" (p. 400). Not only do teachers need this knowledge to teach effectively, but it's probably not needed for any other purpose. For my example, I need to have a specialized understanding of how \((x+y)^2\) can be expanded using FOIL or modeled geometricaly with a square. It may not be all that important for students to understand both the algebraic and geometric ways of representing this problem, but I need to know both so I can better understand student strategies and sources of error. Namely, the error that \((x + y)^2 = x^2 + y^2\).

Horizon Content Knowledge

This domain was provisionally included by the authors and described as, "an awareness of how mathematical topics are related over the span of mathematics included in the curriculum" (p. 403). For my example of \((x + y)^2 = x^2 + 2xy + y^2\), I need to understand how previous topics like order of operations, exponents, and the distributive property relate to this problem. Looking forward, I need to understand how this problem relates to factoring polynomials and working with rational expressions.

Knowledge of Content and Students (KCS)

This is "knowledge that combines knowing about students and knowing about mathematics" (p. 401) and helps teachers predict student thinking. KCS is what allows me to expect students to incorrectly think \((x + y)^2 = x^2 + y^2\), and to tie that to misconceptions about the distributive property and exponents. I'm not sure I had this knowledge for this example when I started teaching, but it didn't take me long to figure out that it was a very common student mistake.

Knowledge of Content and Teaching (KCT)

Ball et al. say KCT "combines knowing about teaching and knowing about mathematics" (p. 401). While KCS gave me insight about why students mistakingly think \((x + y)^2 = x^2 + y^2\), KCT is the knowledge that allows me to decide what to do about it. For me, this meant choosing a geometric representation for instruction over using FOIL, which lacks the geometric representation and does little to address the problem if students never recognize that \((x + y)^2 = (x + y)(x + y)\).

Knowledge of Content and Curriculum

For some reason, Ball et al. include this domain in a figure in their paper but never describe it explicitly. They do, however, scatter enough comments about knowledge of content and curriculum to imply that teachers need a knowledge of the available materials they can use to support student learning. For my example, I know that CPM uses a geometric model for multiplying binomials, Algebra Tiles/Models can be used to support that model, virtual tiles are available at the National Library of Virtual Manipulatives (NLVM), and the Freudenthal Institute has an applet that allows students to interact with different combinations of constants and variables when multiplying polynomials.

Some of the above can be hard to distinguish, but thankfully Ball and colleagues clarify by saying:

In other words, recognizing a wrong answer is common content knowledge (CCK), whereas sizing up the nature of an error, especially an unfamiliar error, typically requires nimbleness in thinking about numbers, attention to patterns, and flexible thinking about meaning in ways that are distinctive of specialized content knowledge (SCK). In contrast, familiarity with common errors and deciding which of several errors students are most likely to make are examples of knowledge of content and students (KCS). (p. 401)

In their conclusion, the authors hope that this theory can better fill the gap that teachers know is important, but isn't purely about content and isn't purely about teaching. We can hope to better understand how each type of knowledge above impacts student achievement, and optimize our teacher preparation programs to reflect that understanding. Furthermore, that understanding could be used to create new and improved teaching materials and professional development, and better understand what it takes to be an effective teacher. With this in mind, you can gain some insight to what Ball was thinking when she gave this congressional testimony:


References


Ball, D. L., Thames, M. H., & Phelps, G. (2008). Content knowledge for teaching: What makes it special? Journal of Teacher Education, 59(5), 389–407. doi:10.1177/0022487108324554

RYSK: Gravemeijer's Local Instruction Theories as Means of Support for Teachers in Reform Mathematics Education (2004)

This is the 12th in a series describing "Research You Should Know" (RYSK) and part of my OpenComps.

Gravemeijer (from above) at the 2011 RME Conference
I began my recent reading of the literature on learning trajectories by reading Clements & Sarama's (2004) Learning Trajectories in Mathematics Education, and then went back to where the idea formally began, Simon's (1995) Reconstructing Mathematics Pedagogy from a Constructivist Perspective. Now I'm jumping to 2004 again with Koeno Gravemeijer's Local Instruction Theories as Means of Support for Teachers in Reform Mathematics Education. Koeno Gravemeijer (pronounced Koo-no Grav-meyer) has worked at multiple institutions in the Netherlands and spent time at Vanderbilt working with Paul Cobb, but he's best known for his long time association and leadership with the Freudenthal Institute and his advancements of Realistic Mathematics Education (RME).

When Martin Simon introduced the concept of hypothetical learning trajectories in his 1995 paper Reconstructing Mathematics Pedagogy from a Constructivist Perspective, he described them as part of a teaching cycle that was informed by the teacher's knowledge and then revised after assessment of student understanding. While much of the focus was placed on the idea of the trajectory, Simon made clear that no two trajectories will be alike, as each one is hypothesized for a unique group of students who are uniquely constructing knowledge. In other words, you can't just prescribe a trajectory and ask teachers to follow it to the letter. Instead, Simon suggested we needed to build an understanding of the knowledge teachers were using to inform and modify their trajectories:

A possible contribution that can be made by the analysis of data and the resulting model reported in this paper is to encourage other researchers to examine teachers' "theorems in action" and to make teachers' assumptions, beliefs, and emerging theories about teaching explicit. (p. 142)

This paper by Gravemeijer is, in part, a response to Simon's call to other researchers. Gravemeijer first states that in a constructivism-inspired reform mathematics, the traditional goals of instructional design must change:

What is needed for reform mathematics education is a form of instructional design supporting instruction that helps students to develop their current ways of reasoning into more sophisticated ways of mathematical reasoning. For the instructional designer this implies a change in perspective from decomposing ready-made expert knowledge as the starting point for design to imagining students elaborating, refining, and adjusting their current ways of knowing. (p. 106)

Next, Gravemeijer recognizes that while every teacher can use their knowledge to hypothesize a learning trajectory, we (researchers, teacher educators, curriculum designers) need to have some knowledge in common if we want to help teachers:

The example Simon (1995) worked out shows that designing hypothetical learning trajectories for reform mathematics is no easy task. We can, therefore, ask ourselves what kind of support can be given to teachers. It is clear that we cannot rely on fixed, ready-made, instructional sequences, because the teacher will continuously have to adapt to the actual thinking and learning of his or her students. Thus it seems more adequate to offer the teacher some framework of reference, and a set of exemplary instructional activities that can be used as a source of inspiration. (p. 107)

This is where Gravemeijer introduces the concept of a local instruction theory, which he describes as "the description of, and rationale for, the envisioned learning route as it relates to a set of instructional activities for a specific topic" (p. 107). I admit, it's difficult at first to discern this from a hypothetical learning trajectory, but I think the key is the relationship to instructional activities (which are more fixed/solid) instead of a trajectory's relationship to student understanding (which is more flexibile/fluid). By addressing the relationship of learning to the instructional activities, Gravemeijer uses local instruction theories to describe a common foundation teachers can use for building trajectories, saying that "Externally developed local instruction theories are indispensable for reform mathematics education" and that it is "unfair to expect teachers to invent hypothetical learning trajectories without any means of support" (p. 108). (If you're still confused, I think I can safely oversimplify it like this: Simon says trajectories are about student learning, not mathematical tasks. Gravemeijer agrees, but since trajectories are unique because student learning is unique, it helps if we have some agreed-upon ideas about how mathematical tasks should be designed.) Given Gravemeijer's long association with the Freudenthal Institute, he naturally describes how design principles from Realistic Mathematics Education (RME) provide the kind of instructional design framework for creating a local instruction theory.

Design Research and RME

Some curricula and instructional strategies are developed then subjected to treatment and control groups to test their effectiveness. That's not design research and not how RME has been developed. Instead, design research consists of cyclical iterations of thought experiments, teaching experiments, and retrospective analyses. It's similar to how teachers improve their instruction as they gain experience: they plan an activity for year one, then conduct that activity, then reflect on the activity so it will be better in year two. Of course, a team of researchers who are carefully theorizing, observing, collecting data, and analyzing the results across multiple classrooms can more quickly and effectively improve tasks and instruction than a teacher can alone.

Gravemeijer describes the design research he conducted with Paul Cobb and others around the development of mental computation strategies for addition and subtraction with elementary students. There are numerous papers and at least part of one dissertation all related to this work, so I won't describe it here. I will, however, describe the three RME design principles that Gravemeijer cites as helping form the local instruction theory that guided the design research process.

Guided Reinvention

Hans Freudenthal (1973) believed mathematics is best learned when students get to experience a process of learning that's similar to the way the mathematics was invented.

If mathematics is to be applied, applying mathematics should be taught and learned. Applying is often interpreted, as mentioned above, as substituting numerical values for parameters in general theorems and theories. This is a misleading terminology. Mathematics is applied by creating it anew each time -- I will expound this in more detail too. This activity can never be exercised by learning mathematics as a ready-made product. Drilling algorithms may be indispensable, but inventing problems to drill algorithms does not create opportunities to teach applying mathematics. This so-called applied mathematics lacks the flexibility of good mathematics. (Freudenthal, 1973, p. 118)

I've heard criticisms of this approach. "How in the world can a student reinvent mathematics that took mathematicians hundreds of years to understand?" That's a valid question, and the best answer is: "Through carefully designed curriculum and instruction." The goal is not to replicate the invention of the mathematics, but learn from history how a mathematical idea might be constructed in the mind of a student. Of course, this takes an extensive and special knowledge of the history of mathematics, and largely explains why Freudenthal's Mathematics as an Educational Task is almost 700 pages long.

Didactical Phenomenology

The concept of didactical phenomenology relates the mathematical "thought thing" and the phenomenon it describes. This is not a theory I know well but hope to study more in the future.

Mathematical concepts, structures, and ideas serve to organise phenomena -- phenomena from the concrete world as well as from mathematics -- and in the past I have illustrated this by many examples. By means of geometrical figures like triangle, parallelogram, rhombus, or square, one succeeds in organising the world of contour phenomena; numbers organise the phenomenon of quantity. On a higher level the phenomenon of geometrical figure is organised by means of geometrical constructions and proofs, the phenomenon "number" is organised by means of the decimal system. So it goes in mathematics up to the highest levels: continuing abstraction brings similar looking mathematical phenomena under one concept -- group, field, topological space, deduction, induction, and so on. (Freudenthal, 1983, p. 28)

Traditionally we teach an abstract mathematics and then find examples for students to make the mathematics concrete. With didactical phenomenology, we focus on progressive mathematization, suggesting "looking for phenomena that might create opportunities for the learner to constitute the mental object that is being mathematized" (Gravemeijer, p. 116). Yes, it's hard to understand without a lot of specific examples, and that's why Freudenthal wrote almost 600 pages on this topic. It's all in a book I have yet to read, so I'll forgive myself for giving a better description here.

Emergent Modeling

I can best describe emergent modeling with an example. Imagine an elementary class learning about fractions. Instead of giving students a formal model (like a numerator and denominator), the concept of emergent modeling says we should let students reach these models informally and progressively. If a task involves the sharing of parts of cookies with the students, students might begin with breaking apart actual cookies. Once realizing this isn't convenient, students might move to drawing cookies on paper. At some point they'll realize that drawing all the details of the cookie isn't necessary and just use a circle to represent a cookie. Up until this point, these are all models-of a cookie. The key step in this process is when students start using circles to model other contextual situations, like working with fractions of time, money, space, etc. Now the circle is a model-for a part-whole relationship, and not representing a specific object like a cookie. These models-for have the power to generalize to other contexts, and eventually students no longer need the circle and rely on formal mathematics to represent and work with fractions. Gravemeijer describes a similar process in this paper, except with how bead strings, unifix cubes, and rulers can lead to marked and empty number lines as students develop ideas of cardinality, ordinality, and distance as they learn mental strategies for addition and subtraction.

Conclusion

I hope by now you have some sense for a local instruction theory. The three RME principles above -- guided reinvention, didactical phenomenology, and emergent modeling -- do not describe a detailed instructional sequence of tasks and instructions for a teacher. They are, however, a way of theorizing how a particular instructional sequence should work, grounded in the design research conducted by Gravemeijer et al. This kind of local instruction theory is what allows teachers to design hypothetical learning trajectories that focus on the construction of student understanding, and provide some common ground for helping teachers become better at trajectory hypothesizing.

References

Freudenthal, H. (1973). Mathematics as an educational task (p. 680). Dordrecht, The Netherlands: D. Reidel.

Freudenthal, H. (1983). Didactical phenomenology of mathematical structures (p. 595). Dordrecht, The Netherlands: D. Reidel.

Gravemeijer, K. (2004). Local instruction theories as means of support for teachers in reform mathematics education. Mathematical Thinking and Learning, 6(2), 105–128. doi:10.1207/s15327833mtl0602_3

Simon, M. A. (1995). Reconstructing mathematics pedagogy from a constructivist perspective. Journal for Research in Mathematics Education, 26(2), 114–145. doi:10.2307/749205