Modeling Mathematical Aesthetics

Fractal-Geometry-HQ-Desktop-Wallpaper-24806Note: This post was written by my two doctoral students, Lara Jasien and Nadav Ehrenfeld, as part of the Virtual Conference on Mathematical Flavors. This essay responds to the prompt  “How do teachers move the needle on what their kids think about the doing of math?” It is also part of a strand inside that conference, inspired by an essay by Tim Gowers,Two Cultures in Mathematics.

Before we begin responding to Gowers’ essay, we’d like to share a little bit about what draws us to this conversation. As budding researchers of mathematics teaching and learning, we spend our days watching teachers go about their daily routines with their students. We look for the ways teachers support their students to engage in meaningful learning and position them as capable, curious thinkers. Our work is fundamentally concerned with the ways classroom culture shapes what it means to teach, learn, and do mathematics. Gowers’ essay provides us with an interesting new lens on the role of culture in mathematics. We want to share (what we think is) a problem-of-practice worth considering and then point to an often overlooked teaching move that we recently saw a teacher use in ways that counteracted this problem-of-practice.

As educators and learners of mathematics, our experiences usually involve engaging students in correctly solving mathematical problems that are predetermined, handed down to us over generations through textbooks and pacing guides (with slight variations). This means that students have few opportunities to engage in a core element of mathematics — finding and articulating problems that are interesting to solve. We think this is intimately connected to a missing aspect of mathematics culture in typical math education: the mathematical aesthetic. Mathematicians’ aesthetic tastes and values lead them to pursue some problems, solution strategies, and forms of proof write-ups over others. When mathematicians’ inquiry is driven by their aesthetics, they engage in exploration, noticing, wondering, and problem-posing.

The mathematical aesthetic is the mechanism by which mathematicians distinguish between what they experience as meaningful, interesting mathematics and trivial, boring mathematics. In his essay, The Two Cultures of Mathematics, W.T. Gowers identified two groups of mathematicians who find each other’s work equally distasteful (with a little dramatic flare): problem solving mathematicians and theoretical mathematicians. Typically, school instruction exposes students to problems that fit both cultures of mathematics: Some school mathematics is done for mathematics sake, some is done for the purpose of real life or pseudo real life (word problems) problem solving. Yet, when do students have the opportunity to develop aesthetic preferences for different ways of engaging with and thinking about mathematics?

In our work, we have seen classrooms with cultures that support students in posing questions to their peers — questions like, I wonder if there is a reason for that? or What’s your hunch?. In these classrooms, we see students begin to be interested in and passionate about mathematics. In our minds, when students develop such passionate tastes about meaningful mathematics, we are on a good track for empowering our students for success.

The questions we just mentioned are actually questions we recently overheard a teacher asking her students as her last statement before exiting small group conversations. We consider her enthusiastic questions to be a form of modelling mathematical aesthetics, prompting students to be curious, explore, wonder, and use their intuition. While ideally the classroom culture would eventually lead to students asking themselves and each other these kinds of aesthetic questions, we know that our own authentic intellectual curiosity as educators does not go unnoticed by our students. Importantly, this teacher did not ask these questions and then hang around and wait for student answers. She left the students with juicy questions that they could investigate together.

As teachers, we rarely get feedback on how our exit moves from small group conversations affect their conversation or the classroom culture. Of course, some exit strategies ­–– such as telling students the answer or funneling them towards it –– will clearly lead to cultures where students see mathematics as a discipline of quick-and-correct answer finding. This view of mathematics can preclude opportunities for students to develop as autonomous doers and thinkers of mathematics. Fortunately, options for productive exit strategies and modelling of intellectual interests are many. These options also present new decision-making challenges to teachers as what happens when we exit the conversation becomes far less predictable. Our students do not need to have the same mathematical tastes as we do, but we do want them to feel empowered and intellectually curious in our classrooms. By foregrounding noticing, wondering, and problem-posing as authentic mathematical practices, we can support students in developing their own mathematical aesthetic. Of course, doing so requires us to model genuine intellectual curiosity, make room for uncertainty and ambiguity in our tasks (groupworthy!), create access to multiple resources for pursuing mathematical questions (Google is acceptable!), and scaffold for conversation rather than bottom-lines (exit moves!). Leaving students with a juicy, natural question is a start.

Advertisements

Great Stuff from My Team in 2017

One of the great things about coming up in this profession is seeing all the great work my students (current and former) produce. As you may note, their work varies yet addresses some central themes. I hope you will read any papers that sound interesting.

Without further ado, here are some of the highlights from 2017:

Simpson, A., Bannister, N., & Matthews, G. (2017). Cracking her codes: understanding shared technology resources as positioning artifacts for power and status in CSCL environments. International Journal of Computer-Supported Collaborative Learning, 12(3), 221-249.
There is a positive relationship between student participation in computer-supported collaborative learning (CSCL) environments and improved complex problem-solving strategies, increased learning gains, higher engagement in the thinking of their peers, and an enthusiastic disposition toward groupwork. However, student participation varies from group to group, even in contexts where students and teachers have had extensive training in working together. In this study, we use positioning theory and interaction analysis to conceptualize and investigate relationships between student interactions across two partner pairs working with technology in an all-female cryptography summer camp and their negotiated positions of power and status. The analysis resulted in uneven participation patterns, unequal status orderings, and an imbalance of power in both comparison cases. We found a reflexive relationship between partner interactions around shared technology resources and negotiated positions of power and status, which leads us to conclude that interactions around technology function as an important indicator of negotiated positionings of power and status in CSCL settings, and vice-versa. With that said, we found qualitative differences in the ways emergent status problems impacted each team’s productivity with the cryptography challenge, which has important implications for future research on CSCL settings and classroom practice.
Chen, G. A. & Buell, J. Y. (2017). Of models and myths: Asian (Americans) in STEM and the neoliberal racial project. Race Ethnicity and Education, 1-19.
This paper examines historical and contemporary racializations of Asian(Americans) within the STEM system. The prevailing perception of Asian(Americans) as model minorities masks how their multiple and contradictory positionings in the STEM system perpetuate the neoliberal racial project and reproduce systems of racism and oppression. Through a multidisciplinary analysis of STEM education and industry, we demonstrate that the shifting racialization of Asian(Americans) secures advantages for White Americans by promoting meritocracy and producerism and justifies White supremacy. By serving these functions, the racialization of Asian(Americans) within the STEM system is central to the neoliberal racial project. This paper also suggests how STEM education researchers can reveal and resist, rather than veil and support, the neoliberal racial project in STEM.
Horn, I. S., Garner, B., Kane, B. D., & Brasel, J. (2017). A Taxonomy of Instructional Learning Opportunities in Teachers’ Workgroup Conversations. Journal of Teacher Education, 68(1), 41-54.
Many school-improvement efforts include time for teacher collaboration, with the assumption that teachers’ collective work supports instructional improvement. However, not all collaboration equally supports learning that would support improvement. As a part of a 5-year study in two urban school districts, we collected video records of more than 100 mathematics teacher workgroup meetings in 16 different middle schools, selected as “best cases” of teacher collaboration. Building off of earlier discursive analyses of teachers’ collegial learning, we developed a taxonomy to describe how conversational processes differentially support teachers’ professional learning. We used the taxonomy to code our corpus, with each category signaling different learning opportunities. In this article, we present the taxonomy, illustrate the categories, and report the overall dearth of meetings with rich learning opportunities, even in this purposively sampled data set. This taxonomy provides a coding scheme for other researchers, as well as a map for workgroup facilitators aiming to deepen collaborative conversations.
Garner, Brette,  Jennifer Kahn Thorne, and Ilana Seidel Horn. “Teachers interpreting data for instructional decisions: where does equity come in?.” Journal of Educational Administration 55, no. 4 (2017): 407-426.

Though test-based accountability policies seek to redress educational inequities, their underlying theories of action treat inequality as a technical problem rather than a political one: data point educators toward ameliorative actions without forcing them to confront systemic inequities that contribute to achievement disparities. To highlight the problematic nature of this tension, the purpose of this paper is to identify key problems with the techno-rational logic of accountability policies and reflect on the ways in which they influence teachers’ data-use practices.

This paper illustrates the data use practices of a workgroup of sixth-grade math educators. Their meeting represents a “best case” of commonplace practice: during a full-day professional development session, they used data from a standardized district benchmark assessment with support from an expert instructional leader. This sociolinguistic analysis examines episodes of data reasoning to understand the links between the educators’ interpretations and instructional decisions.

This paper identifies three primary issues with test-based accountability policies: reducing complex constructs to quantitative variables, valuing remediation over instructional improvement, and enacting faith in instrument validity. At the same time, possibilities for equitable instruction were foreclosed, as teachers analyzed data in ways that gave little consideration of students’ cultural identities or funds of knowledge.

Test-based accountability policies do not compel educators to use data to address the deeper issues of equity, thereby inadvertently reinforcing biased systems and positioning students from marginalized backgrounds at an educational disadvantage.

This paper fulfills a need to critically examine the ways in which test-based accountability policies influence educators’ data-use practices.

Supporting Instructional Growth in Mathematics (Project SIGMa)

Good news to share: another research grant has been funded by the National Science Foundation. Yay!

For this project, my research team and I will be working with Math for America in Los Angeles to design a video-based coaching method for their Master Teacher Fellow program.

sigma logo

This is what we pitched to the NSF:

This study addresses the need to develop processes for adequate and timely feedback to inform mathematics teachers’ instructional improvement goals. In this study, we propose using design-based implementation research to develop and investigate a process for documenting mathematics teachers’ instruction in a way that is close to classroom practice and contributes to teachers’ ongoing pedagogical sense making. The practical contribution will be a framework for formative feedback for mathematics teachers’ learning in and from practice. The intellectual contribution will be a theory of mathematics teachers’ learning, as they move from typical to more ambitious forms of teaching in the context of urban secondary schools. Both the practical and theoretical products can inform the design of professional development and boost other instructional improvement efforts.

In a recent Spencer study, my team and I investigated how teachers used standardized test data to inform their instruction. (That team was Mollie Appelgate, Jason Brasel, Brette Garner, Britnie Kane, and Jonee Wilson.)

Part of the theory of accountability policies like No Child Left Behind is that students fail to learn because teachers do not always know what they know. By providing teachers with better information, teachers can adjust instruction and reach more students. There are a few ways we saw that theory break down. First, the standardized test data did not always come back to teachers in a timely fashion. It doesn’t really help teachers adjust  instruction when the information arrives in September about students they taught last May. Second, the standardized test data took a lot of translation to apply to what teachers did in their classroom. Most of the time, teachers used data to identify frequently challenging topics and simply re-taught them. So students got basically the same instruction again, instead of instruction that had been modified to address central misunderstandings. We called this “more of the same,” which is not synonymous with better instruction. Finally, there were a lot of issues of alignment. Part of how schools and districts addressed the first problem on this list was by giving interim assessments –– basically mini versions of year end tests. Often, the instruments were designed in-house and thus not psychometrically validated, so they may have not always measured what they purported to measure. Other times, districts bought off-the-shelf interim assessments whose items had been developed in the traditional (and more expensive) manner. However, these tests seldom aligned to the curriculum. You can read the synopsis here.

Accountability theory’s central idea  ––  giving teachers feedback –– seemed important. We saw where that version broke down, so we wanted to figure out a way to give feedback that was closer to what happens in the classroom and doesn’t require so much translation to improve instruction. Data-informed action is a good idea, we just wanted to think about better kinds of data. We plan to use a dual video coaching system — yet to be developed — to help teachers make sharper interpretations of what is happening in their classrooms.

Why did we partner MfA LA? When I reviewed the literature on teachers’ professional learning, they seemed to be hitting all the marks of what we know to be effective professional development. They focus on content knowledge; organize their work around materials that can be used in the classroom; focus on specific instructional practices; they have a coherent and multifaceted professional development program; and they garner the support of teacher communities. Despite hitting all of these marks, the program knows it can do more to support teachers.

This is where I, as a researcher, get to make conjectures. I looked at the professional development literature and compared it to what we know about teacher learning. MfA may hit all the marks in the PD literature, but when we look at what we know about learning, we can start to see some gaps.

*Conjecture 1 Professional learning activities need to address teachers’ existing concepts about and practices for teaching.

 

Conjecture 2 Professional learning activities need to align with teachers’ personal goals for their learning.

 

Conjecture 3 Professional learning activities need to draw on knowledge of accomplished teaching.

 

*Conjecture 4 Professional learning activities need to respond to issues that come up in teachers’ ongoing instruction

 

*Conjecture 5 Professional learning activities need to provide adequate and timely feedback on teachers’ attempts to improve their instructional practice to support their ongoing efforts.

 

Conjecture 6 Professional learning activities should provide teachers with a community of like-minded colleagues to learn with and garner support from as they work through the challenges inevitable in transformative learning.

 

*Conjecture 7 Professional learning activities should provide teachers with rich images of their own classroom teaching.

 

The conjectures with * are the ones we will use to design our two camera coaching method.

We need to work out the details (that’s the research!) but  teacher’s instruction will be recorded with two cameras, one to capture their perspective on significant teaching moments and a second to capture an entire class session. The first self-archiving, point-of-view camera will be mounted on the teacher’s head. When the teacher decides that a moment of classroom discourse illustrates work toward her learning goal, she will press a button on a remote worn around her wrist that will archive video of that interaction, starting 30 seconds prior to her noticing the event. (As weird as it sounds, it has been used successfully by Elizabeth Dyer and Miriam Sherin!)  The act of archiving encodes the moment as significant and worthy of reflection. For example, if a teacher’s learning goal is to incorporate the CCSSM practice of justification into her classroom discourse, she will archive moments that she thinks illustrate her efforts to get students to justify their reasoning. Simultaneously, a second tablet-based camera would record the entire class session using Swivl®. Swivl® is a capture app installed in the tablet. It works with a robot tripod and tracks the teacher as she moves around the room, allowing for a teacher-centered recording of the whole class session. Extending the prior example, the tablet-based recording will allow project team members to review the class session to identify moments where the teacher might support students’ justifying their reasoning but did not do so. The second recording also captures the overall lesson, capturing some of the lesson tone and classroom dynamics that are a critical context for the archived interactions. Through a discussion and comparison of what the teachers capture and what the project team notices, teachers will receive feedback on their work toward their learning goals. We will design this coaching system to address the starred conjectures in the table

Anyway, I am super excited about this project. I am working with amazing graduate students: Grace Chen, Brette Garner, and Samantha Marshall. Plus, my partners at MfA LA: Darryl Yong and Pam Mason.

I will keep you posted!

 

 

 

Playful Mathematics Learning

I have had the great pleasure of spending the last several days at the Minnesota State Fair.

math on a stick

My colleague Melissa Gresalfi and I got a National Science Foundation grant to study a very special exhibit there called Math On-A-Stick. We have an awesome team of graduate students helping us with the research. They are Lara Heiberger, Panchompoo Fai Wisittanawat, Kate Chapman, and Amanda Bell.

PML Logo

Math On-A-Stick is the brainchild of Christopher Danielson,  educator, promoter of talking math with your kids, and mathematical toy maker.

christopher danielson

That is Christopher on the right. The woman in the pink jacket is a former math teacher. She made the beautiful quilt for Math On-A-Stick.

The exhibit is just a delight. Not only is it a lovely respite in a shady, relatively quiet corner of the fairgrounds, it is filled with math play. Here are a few of the stations in the exhibit.

On the left is a tile station. The tiles are half black, half colored, and children can make all kinds of patterns with them. The center image comes from the pentagon station. I could spend all day there myself. I made that creation. On the right are tessalating lizards and turtles.

Everyday there are visiting mathematicians and mathematical artists. The first day I was there, Megan Schmidt brought some of her spiral magic. Yesterday were hexaflexagons.

Today, Christopher was the Visiting Mathematician. He built a giant pattern machine that children could play with. It is made up of little “pattern machines,” and the buttons pop up and down, making a satisfying clicking noise.

Melissa and I are interested in studying two things about children’s encounters with the exhibit. First, we are interested in the design, investigating how the various activities support mathematical interactions between children, the exhibit, the mathematics educators, parents –– and each other. Second, we are interested in children’s engagement. We want to examine how the children engage with different parts of the exhibit, looking for relationships among children’s ideas about mathematics, reported experiences in math class, and the exhibit design.

Our primary data come from recordings the kids make while they are playing. We outfit them with GoPro cameras so we can see how they interact with the exhibit, recording their interactions, their general gaze, and the time they spend at the various stations.

IMG_9930

Melissa and Fai set up a stationary camera, while Lara pretends to be a kid at play.


IMG_9942 (1)

A couple of kids getting outfitted with GoPros

This is supplemented by entry and exit surveys, brief interviews, and stationary recordings of the stations (e.g. a camera positioned at the Pentagons so we can see how a cross section of children play with that station and compare that to the activity of our focal children).

IMG_9925

Data collection station. It’s a well oiled machine.

We weren’t sure how kids would feel about us approaching them and asking them to wear the cameras on their heads. It turns out that they love it. They are really happy to share, as are the amazing volunteers, who have been very agreeable to getting captured in the video footage as the children play.

Our research findings will help us identify more ways to make mathematics play a part of instruction. Already, many children are telling us that Math On-A-Stick math is different than what they do in school –– even kids who are inventing and problem solving in impressive and novel ways. We are looking forward to analyzing the hundreds of hours of data we collect and sharing what we learn with all of you.

 

What Does It Mean to Study Teachers’ Learning from a Sociocultural Perspective?

I try to be a plain-talking academic when I engage in the public realm of social media. Sometimes, despite my best efforts, I find myself wanting to use academic jargon. My goal in writing this blog is to have conversations with both educators and researchers, so I think it is okay to have “turns” of conversation that lean a little more on my research voice than my educator voice.

Sociocultural is jargon word that I have wanted to invoke from time to time when talking to my practitioner friends. In particular, the research I do uses sociocultural learning theories as a way of describing both how students and teachers learn.

But what does that mean? In order to understand, you need a little history on how we have come to think about learning the way we do.
In the late 19th and early 20th centuries, U.S. research on learning was dominated by behaviorism. Seeking a rigorous empirical basis for a study of behavior, researchers like E.L. Thorndike and B.F. Skinner sought to explain how learning happened by documenting what they could see empirically.

Out of this theory, we have ideas like operant conditioning, where actions are shaped by stimulus and responses in the environment to ultimately change behavior. Skinner famously made little operant conditioning chambers called “Skinner boxes” that successfully “taught” pigeons to dance. Through the boxes, food was dispensed in response to the pigeon’s movements. If he turned his head to the left –– the stimulus –– he would get a food pellet –– the response. The next time, he had to turn his head a little further to get his food. Eventually, through operant conditioning, the pigeon learned to turn in a full circle –– to “dance” –– to get food.

dancing pigeons

Behaviorism explained some forms of learning, but it couldn’t explain everything. In the 1950s, the cognitive revolution began. Researchers like Jerome Bruner began to critique behaviorism, noting that a sole focus on behavior precluded a study of how people created meaning, a central question in understanding why people do what they do. Researchers realized they could do empirical studies that included a theory of the mind. Using methods like case studies and talk aloud protocols, investigators could examine how people made sense of their activities in the world.

Cognitive science, as it came to be called, led to important insights like schema theory and conceptions. A schema is a general system for understanding how knowledge is represented and how it is used.

Researchers can look for evidence of different schemata (the plural of schema). Like the behaviorists, they observed what people did to understanding learning. However, they augmented this by asking people to explain their thinking through interviews and surveys.

To give an example of a schema, let’s take the word “dog.” When I say “dog” what do you imagine?

You probably think of four-legged animals that bark, are furry, have tails. But how do you know that these are all dogs?


How do you know that these are not?


This is the question that underlies the idea of schemata.

The examination of schemata started to point to the importance of culture. Schemata are closely related to prototypes. So, for example, when I say the word “furniture” what do you think of?

Linguists have found that when you say the word “furniture” to Americans, they think the best examples are chair and sofa.

When you say the word “möbel” to Germans, however, they think the best examples are bed and table. Our schemata and our prototypes –– the building blocks of concepts in the world –– are culturally specific.

By the early 1990s, this increasing recognition of the importance of language, culture, and context shifted our ideas about learning yet again. Language and culture were not just the setting for development and thinking –– some kind of external variable to be controlled for –– they were, in fact, fundamental components of these mental processes. This insight meant that, to explain some learning phenomena, researchers needed to do more than describe mental structures.

This required another broadening of research methods. Using linguistics, anthropology, and sociology, learning researchers wanted to account for how concepts stretched beyond individual minds and into the world. Deeply influenced by Soviet psychologist, Lev Vygotsky, researchers working in this sociocultural tradition examined learning as it happened in interactions in the world, requiring new units of analysis. That is, instead of studying individuals as they learned, researchers sought ways to study individuals in context.

My own research takes up these sociocultural insights to re-think how we study teacher learning. Let me paint a bit of a picture for you about the intellectual traditions that shape my work.

First, when I entered my doctoral program at UC Berkeley in the mid-1990s, debates between cognitive and sociocultural perspectives on learning were quite active in my courses and in research groups. Although most arguments centered on questions of student learning, there was a growing interest in what was often called “out-of-school learning.” Influenced by anthropological researchers like Jean Lave, a small group of scholars studied workplace learning, a particularly pressing topic in our modern information economy, where workers must constantly adapt to a rapidly changing world.

Meanwhile, in educational policy studies, there was a growing recognition that research on school organization, curriculum, and teacher professional development had overlooked a central question: How do teachers’ learn? Since almost all school improvement efforts want to improve instructional quality –– through curricular reform, changes in scheduling or assessment techniques –– they all depend on what happens inside of classrooms. And that, of course, depends on what happens with teachers.

For this reason, educational policy scholars like Judith Warren Little and Mike Knapp were recognizing that teachers’ learning is an underanalyzed component of any efforts at school change or instructional improvement. Yet it was not central to policy designs –– let alone to analyses of their effectiveness.

The moment was ripe for somebody to connect these ideas. My work starts with the policy-based observation that designs for instructional change must consider teacher learning. I then use methods and insights from sociocultural theories of learning to examine how teachers’ learning happens in the school as a workplace. As the sociocultural theorists suggest, what teachers know and learn is not solely a product of what is in their individual heads.

Concepts for teaching draw on culturally specific practices and language in the world. For instance, in the U.S., we often start grouping children by ability levels at a very young age. The concept of a “high ability 6 year old” makes sense for American teachers in a way that it would not to teachers in countries that do not track in the elementary years. There are consequences to that concept having social meaning, as educators make decisions about their schools and classrooms and parents advocate for certain experiences.

By using sociocultural perspectives to explain teachers’ learning, my research is culturally specific and theoretically specific. Although the details of what I find about U.S. teachers may not generalize to other countries, it is my hope that my descriptions of teachers’ learning can be more generalizable.

Structure Can Change Agency

One great privilege of the work I do are the many opportunities I get to share the things I care about with different groups of people. If you do it enough, you get a chance to clarify your own ideas, learn from others, and notice connections.

This past weekend, I had the honor to give a keynote talk at the Carnegie Math Pathways Forum. If you don’t know about their work, it is worth checking out. Briefly, their work addresses the enormous blockage in the math pipeline as students transition from secondary to post-secondary. A staggering number of students get placed in developmental math classes, and often, these courses become a holding bin students cannot get out of. The Carnegie folks have worked primarily with community college instructors to re-think developmental math curricularly and pedagogically. It’s fascinating and important work.

My talk was about the relationship between structure and agency, how both contribute to inequalities in mathematics education. When we are teaching in a classroom, it is easy to see problems of inequality as they look locally: high enrollments in developmental math, over-representation of students coming from poverty and students of color, a sense of student apathy. To make progress, however, instructors can learn by linking the local to broader social processes: the maldistribution of qualified math teachers, STEM classrooms that are hostile environments to minoritized students, a K-12 curriculum that often reflects the institution of schooling more than what it means to do meaningful mathematics. I argued that if we frame these problems through what we see locally, we give ourselves, as teachers, less leverage to make progress on them. I shared two key concepts for linking these social processes to what we see in our classrooms: social risk and status. I have written about both of these (click the links if you are curious), but briefly, social risk refers to the threats people feel are posed to their status in a community while status describes the perception of students’ academic capability and social desirability. Both of these ideas link the social process explanations for inequality to what teachers see in their classrooms locally.

Teachers can then work to design classrooms that reduce social risk by, in part, attending to status dynamics. In other words, to connect structure and agency, we need ways to think across scale and look at the social origins of problems too often narrated as individual issues. Instead of, for example, blaming students for being apathetic about mathematics learning, we need to recognize what their history has likely been in our current system and accept their apparent apathy as a reasonable response. Our task shifts from finger pointing (“My students just aren’t motivated!“) to having the productive challenge of honoring their experience while trying to change their ideas about math and learning.

In the end, then, structure can help us change agency in two ways. First, by recognizing that it is there, along with the social processes it holds in place, we can arrive at more productive framings of the problems we face locally. Second, we can leverage the structural designs in our classroom to invite students’ agency.

I have written about designing structures to promote agency before. If you don’t feel like reading that (I realize it’s summer!), maybe watch this video instead. It is quite a joy.

And don’t we all need more of that right now?

 

Professional Development is Broken, but Be Careful How We Fix It

This morning, Jal Mehta tagged me on a tweet to linking to his recent Education Week blog post, entitled “Let’s End Professional Development as We Know It.”

The following exchange ensued:

He then asked if I could share some of my research to back my perspective. I sent him an email with journal articles and such, but I thought I would share my ideas with y’all too.

Here is my argument about why putting professional development (PD) back in schools may be necessary but not sufficient to improving its impact on teachers’ instruction.

Unlike medicine and other scientific fields, where problems are taken-as-shared and protocols for addressing problems are roughly agreed upon, teaching problems are locally defined. What needs attention in one school may not need attention in another. For instance, some schools’ “best practices” may center on adapting instruction to English learners, while other schools’ might center on the mental health ailments that have become prevalent among affluent teens. Likewise, other professions share language, representations, and goals for critical aspects of their work — these all important resources for learning together. In teaching, we see repeatedly that terms acquire the meaning of their setting more often than they bring new meanings to these places. Take, for instance, Carol Dweck’s ideas about mindset. The various ways that her construct has taken hold in education led her to explain why what she means by mindset is not how the idea is being used. If we leave professional development entirely up to individual school sites, this means that “doing PD” on Topic X probably looks fairly different from place to place, so radically localized professional development will exacerbate this problem.

Leaving professional development to local sites also limits teachers’ access to expertise. When my colleagues and I have studied teachers’ collaborative learning, we found that the learning opportunities are not equally distributed across all teacher groups. Some of this has to do with how teachers spend their time (e.g., focused on logistics or deeper analysis of teaching). But some of it has to do with who is sitting around the table and what they have been tasked to do.

Teachers’ collaborative learning can be described as an accumulated advantage phenomenon, where the rich get richer. That is, teachers who have sophisticated notions of practice are able to identify teaching problems in complex ways and deploy more sophisticated strategies for addressing them. This follows from my previous points, since problem definition is an important part of teachers’ on-the-job learning. For instance, if we have a lot of students failing a course, how do we get to the bottom of this issue? In many places, high failure rates are interpreted as a student quality problem. In others, they are taken as a teaching quality problem. Interpretations depend on how practitioners think this whole teaching and learning business goes down. In other words, problem definition is rooted in teachers’ existing conceptions of their work, which in other professions, are codified and disseminated through standardized use of language and representations.

Unequal access to expertise is only one of many reasons the optimistic premise of teacher community often does not pan out. There is a tendency to valorize practicing teachers’ knowledge, and, no doubt, there is something to be learned in the wisdom of practice. That being said, professions and professionals have blind spots, and with the large-scale patterns of unequal achievement we have in the United States, we can infer that students from historically marginalized groups frequently live in these professional blind spots. For reasons of equity alone, it is imperative to develop even our best practitioners beyond their current level by giving them access to more expert others.

Even in highly collaborative, well-intentioned teacher communities, other institutional pressures (e.g., covering curriculum, planning lessons) pull teachers’ attention to the nuts-and-bolts of their work, rather than broader learning or improvement agendas. Add to this the norms of privacy and non-interference that characterize teachers’ work, you can see why deeper conversations around issues of teaching and learning are difficult to come by.

What about, you might say, bringing in expert coaches? Research shows that expert facilitators or coaches can make a difference. In fact, there is evidence that having expert coaches may matter more than expert colleagues when it comes to teacher development. At the same time, we suspect that expert facilitators are necessary but not sufficient, as coaches often get pulled into other tasks that do not fully utilize their expertise. In our current study, we see accomplished coaches filling in for missing substitute teachers, collating exams, or working on classroom management with struggling teachers. None of these tasks taps into their sophisticated instructional knowledge. Additionally, being an accomplished teacher does not guarantee you have the skill to communicate your teaching to others. In our data, we have numerous examples of really great teachers underexplaining their teaching to others.

Lee Shulman famously called out the missing paradigm of teacher knowledge, giving rise to a lot of research on pedagogical content knowledge (PCK). While PCK gave a very useful way to think about teachers’ specialized knowledge, little progress has been made on understanding how teachers develop this and other forms of knowledge, particularly in the institutional context of schools, which often presses teachers’ practice away from what might be deemed “good teaching.” As long as we don’t have strong frameworks for understanding how teachers learn, PD –– even localized, teacher-led PD –– risks being just another set of activities with little influence on practice.

Reinventing Mathematics Symposium at The Willows School

I am honored to be presenting tomorrow at the Reinventing Mathematics Symposium at the Willows School in Culver City, CA.

My workshop is on Playing with Mathematical Ideas: Strategies for Building a Positive Classroom Climate. Students often enter math class with fear and trepidation. Yet we know that effective teaching engages their ideas. How do we lower the social risk of getting students to share to help them understand mathematics more deeply? I will share what I have learned from accomplished mathematics teachers who regularly succeed at getting students to play with mathematical ideas as a way of making sense.

In my workshop, I will develop the concepts of status and smartness, as well as share an example of “playful problem solving.” Here is the Tony De Rose video we watched, with the question: How is Tony De Rose mathematically smart? If he were a 7th grader in your classroom, what chances would he have to show it?

Usually teachers like  resources, so I have compiled some here.

Books

Bellos, A. & Harriss, E. (2015). Snowflake, Seashell, Star: Colouring Adventures in Wonderland. Canongate Books Ltd; Main edition

Childcraft Encyclopedia (1987). Mathemagic. World Book Incorporated.

Jacobs, H. (1982). Mathematics: A Human Endeavor. W.H. Freeman & Co Publishers.

Pappas, T. (1993). The Joy of Mathematics (2nd Edition). World Wide Publishing.

Van Hattum, S. (2015). Playing with Math: Stories from Math Circles, Homeschoolers, and Passionate Teachers. Natural Math

Weltman, A. (2015). This is Not a Maths Book: A Smart Art Activity Book. Ivy Press.

Blogs that Feature Playful Mathematics

Math in Your Feet Blog

Talking Math With Your Kids

Visual Patterns

Math Munch

Some Inspiring Ignite* Talks that Give Ideas about Teaching Playfully

*Ignite talks are 5 minute long presentation with 20 slides and with the slides advancing automatically every 15 seconds. It’s the presentation equivalent of a haiku or sonnet.

Peg Cagle, What Architecture Taught Me About Teaching

Justin Lanier, The Space Around the Bar

Jasmine Ma, Mathematics on the Move: Re-Placing Bodies in Mathematics

Max Ray, Look Mom! I’m a Mathematician

There are tons more. The Math Forum does a great job of getting outstanding math educators to share their work in this series of talks.

Please feel free to add other good resources in the comments section!

 

What are the Grand Challenges in Mathematics Education

Back in March, the National Council of Teachers of Mathematics put out a call for Grand Challenges in Mathematics Education.

A Grand Challenge is supposed to spur the field by providing a focus for research. NCTM came up with the following criteria for a Grand Challenge in math education:

Research Commentary-Grand Challenges_1

So I ask you to help the brainstorm. What are the complex yet solvable problems we face in mathematics education that can have a great impact on people’s lives?

Add your thoughts in the comments below or through Twitter (@tchmathculture). Use the hashtag #NCTMGrandChallenge.