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The Proactive Role of the Teacher in Mathematics Education

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Title: The Proactive Role of the Teacher in Mathematics Education


1
The Proactive Role of the Teacher in Mathematics
Education
  • Koeno Gravemeijer
  • Freudenthal Institute for
  • Science Mathematics Education
  • Langeveld Institute
  • Utrecht University
  • koeno_at_fi.uu.nl

2
ConstructivismPeople construct their own
knowledge
3
The Proactive Role of the Mathematics Teacher
  • Reconcile the constructive activity and the
    intellectual autonomy of the students with the
    pedagogical agenda of the teacher
  • ? Proactive role of the teacher
  • Select and introduce tasks anticipating student
    thinking
  • Orchestrate classroom discussions
  • Establish and cultivate an inquiry classroom
    culture

4
Intellectual autonomy (Kamii)
  • Teacher authority and student autonomy
  • Student autonomy
  • Responsibility for being able to justify ones
    claims in the math lesson
  • Teacher authority
  • What mathematics is
  • How is mathematics learned in this classroom
  • Goals tasks

5
Choosing/designing instructional tasks
  • Choosing tasks with an eye on what it might bring
    about ?hypothetical learning trajectory-
    envision the mental activities of the students -
    anticipate how their thinking might help them to
    develop mathematical insights (Simon,
    1995) hypothetical need to check and revise

6
Example
  • Discussion of Area with student-teachers
  • Area length x width ?
  • Blind algorithm??

7
Rectangles problem 1. Determine how many
rectangles, of size and shape of the rectangle
that you were given, could fit on the top surface
of your table. Rectangles cannot be overlapped,
cannot be cut, nor can they overlap the edges of
the table. Be prepared to describe to the class
how you solved this problem.
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11
Rectangles problem 2. Bill said, If the table is
13 rectangles long and 9 rectangles wide, and if
I count 1, 2, 3, ..., 9, and then I multiply, 13
x 9, then I have counted the corner rectangle
twice. Respond to Bills comment.
12
Rectangles problem 3. I used the turned
rectangles method, and I got 32 for table A, and
22 for table B. Can we now say something about
which table is bigger?
13
The stick problem. Two people work together to
measure the size of a rectangular table one
measures the length and the other the width. They
use a stick to measure with. The sticks, however,
are of different lengths. Louisa says, The
length is four of my sticks. Ruiz says, The
width is three of my sticks. What can you say
about the area of the rectangular table?
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Original turned rectangles problem
17
Contrast
  • The hypothetical learning trajectory is very
    different from the classic Socratic way of
    developing an idea in interaction with the
    students
  • Who does the thinking?

18
  • Socratic lesson

19
  • Socratic lesson

20
  • Socratic lesson

21
  • Socratic lesson

22
  • Socratic lesson

23
  • Socratic lesson

24
Hypothetical learning trajectory versus Socratic
lesson
  • Doubling square (2), in the Socratic lesson, the
    teacher does the thinking teacher checks whether
    the students follows along
  • Area Simon (1), with the hypothetical learning
    trajectory, the students do the thinking the
    teacher tries to adapt to what the students are
    thinking.

25
Teachers need help
  • We cannot expect teachers to develop HLTs from
    thin air.
  • We should aim at offering teachers means of
    support for construing and revising HLT's
  • By developing prototypical instructional
    sequences and local instruction theories for
    various topics (fractions, long division, )

26
Instruction theories(different levels)
  • Hypothetical learning trajectory
  • Local instruction theory (topic)
  • Domain-specific instruction theory
  • Guided reinvention
  • tasks (routes levels)
  • symbolizations informal (arithmetic rack, PT
    meeting)
  • conventions
  • Emergent modeling
  • Didactical phenomenology

27
Classroom culture
  • Tasks inquiry math students have to engage in a
    problem solving activity
  • Resistance of students to teachers attempts to
    implement a problem solving approach (Desforges
    Cockburn Hiebert Stigler)
  • Explanation
  • That is what they are used to reproducing the
    teachers reasoning and procedures (Didactical
    contract)
  • Communication ? expectations
  • An everyday-life example

28
Communication ? expectations
  • Elicitation pattern
  • Could you please tell me the way to West Street?

29
Communication ? expectations
  • Elicitation pattern
  • Could you please tell me the way to West Street?
  • You take the second on the right, then the first
    on the left, and then you work straight into West
    Street.

30
Communication ? expectations
  • Elicitation pattern
  • Could you please tell me the way to West Street?
  • You take the second on the right, then the first
    on the left, and then you work straight into West
    Street.
  • OK, the second on the right, then the first on
    the left, and then straight ahead. Perfect, well
    done.
  • Now, could you also tell me the way to Central
    Avenue?

31
Didactical contract/social norms
  • Cobb Yackel emergent perspective
  • social ? psychological
  • classroom social norms ?individual beliefs
  • Beliefs about expectations and obligations,
    shaped by experience
  • Socio-mathematical norms
  • Mathematical practices

32
Social norms school-math
  • Elicitation pattern
  • No responsibility for the students
  • Donna (1)
  • Mr. K. How many?
  • Donna Eight
  • Mr. K. How many?
  • Donna Eh, seven(?)

33
Social normsInquiry math
  • Intellectual autonomy of the students (instead of
    having the teacher or textbook as the authority)
  • Act as a learning community
  • Learning as a group learning from and with each
    other
  • Obligations to explain justify try to
    understand, ask for clarification challenge

34
How to change the didactical contract
  • Establishing social norms ? experience
  • What is valued
  • What is rewarded
  • Using instances as opportunities to clarify norms
  • Example Donna (taken from Erna Yackel)

35
  • Mr. K. How many?
  • Donna Eight
  • Mr. K. How many?
  • Donna Eh, seven(?)
  • Next Mr. K. moves to other students. Later as it
    is
  • Established that 8 was the right answer, Donna
  • complains
  • Donna I said eight but you said I was wrong!
  • Mr. K. What is your name?
  • Donna Dona
  • Mr. K. What is your name?
  • Donna Dona
  • Mr. K. And if I would ask you again, What is
    your name?, would you say anything else but
    Donna?

36
Cultivating an inquiry classroom culture
  • Asking for explanations
  • Please explain your answer. (Why is that so? How
    do you know?)
  • Asking for clarifying questions
  • Who has a question for Jim?
  • Pass the problem along
  • Who can answer Paulas question?
  • Asking for a personal judgment
  • Ann says that it will cost 16.25, do you agree?
  • Promoting that students listen and try to
    understand
  • Did you follow what he said, could you explain it
    to me?

37
Cultivating an inquiry classroom culture
  • Revoicing (for instance to help students to
    follow the argument)
  • Modeling favorable behavior
  • Showing genuine interest in the students
    thinking
  • Building on the input of the students

38
Mathematics in the City, CUNY Cathy Fosnot
Maarten Dolk
39
Turkey video, Cultivating an inquiry classroom
culture
  • Try to explain in such a manner that everybody
    can understand.
  • Listen carefully, and see if you understand.
  • Who thinks he can explain what Amber and Vicky
    tried to do?
  • Do you have something to add?
  • Without telling them how many hours could you
    explain to them how they could figure that out?
  • Great question, did you understand
  • Tell them ..
  • Did you hear what he said ?

40
Central role of the teacher
  • Role of the students ? Participation rules of
    the game
  • Genuine interest example Researcher as a
    teacher How do they think?

41
  • Discussion on two data sets, which show the
    number of serious injuries in accidents with cars
    with airbags and cars without airbags.
  • The data are already summarized graph shows the
    extremes and the medians for both sets of data.
  • Until now, data sets that had to be compared had
    the same extreme high and low values.

42
  • Ben You cannot compare them this way, the
    starting points differ. It would have been
    better if they both would have been from 284
    thru 1000
  • T1. ??
  • Jack If you could change the numbers, which you
    cannot, then you could move this one.
  • L2. And what would you know then?
  • Jack Nothing, but it would be a better way of
    looking.
  • L1. But you said you cannot change the numbers.
    Here the lowest number is 284, and there it is
    400.
  • Ben Yes, but I am not talking about the
    original, if they would begin at 284 and end at
    1000, than you could look at the median.

43
  • Mary He does not use the numbers. He says,
    forget about the numbers for a moment and just
    look at the interval.
  • T1. I think, I get it.
  • T2. If we would know the size of this interval
    and of this interval, how would that help us?
  • Ben Well, than, which be would be the most would
    be the worst car. It would be like taking that
    one, however, there are two different numbers.
    It is no use to take four different numbers and
    then compare the medians.
  • T1. Let me see if I understand. Please check
    if I am correct. You say you cannot compare the
    medians, because you have to take the intervals
    into account. It is not enough to know the
    medians. You have to know where the upper half
    of the data is, and where the lower half is.

44
Socio-mathematical norms
  • Classroom norms specific to mathematics
  • What counts as a mathematical problem
  • What counts as a mathematical solution
  • What counts as a different solution
  • What counts as a more sophisticated solution
  • Criteria ? intellectual autonomy students

45
Socio-mathematical norms
  • What counts as a (mathematical) problem/solution
  • Mathematical problem ? reality (Verschaffel)
  • Jim has 5 planks of 2 meters.
  • gt How many planks of 1 meter can he make?
  • John has 4 planks of 2½ meters.
  • gt How many planks of 1 meter can he make?
  • (Width of the cut made by the saw?)

46
Socio-mathematical norms Mathematics ? Reality
  • Marys friend Ann is staying for diner, now
    there are 5 cheeseburgers for 6 people (father,
    mother, Mary, her brothers and Ann).
  • gt How should they share the cheeseburgers?

47
Socio-mathematical norms Mathematics ? Reality
  • Real-life solutions
  • Mary should share with Ann

48
Socio-mathematical norms Mathematics ? Reality
  • Real-life solutions
  • Mary should share with Ann
  • Go to the shop and buy one extra

49
Socio-mathematical norms Mathematics ? Reality
  • Real-life solutions
  • Mary should share with Ann
  • Go to the shop and buy one extra

50
Socio-mathematical norms Mathematics ? Reality
  • Mathematically productive solutions
  • 5 6 5/6
  • 5 6 ½ 1/3

51
Socio-mathematical norms Mathematics ? Reality
  • Socio-mathematical norms about to what extent
    reality has to be taken into account have to be
    developed in interaction (implicit, experience)
  • In general all classroom norms are based on
    experience
  • What is valued
  • What is rewarded

52
Developing mathematical interest
  • Need for a shift from solving a problem to
    thinking about the solution process from a
    mathematical perspective
  • Is there a better way?
  • Does it always work?
  • Can I prove that?
  • Mathematical progress

53
Mathematical practices
  • HLT Whos learning trajectory?
  • All students???
  • Individual learning routes???
  • Alternative sequence of mathematical practices
    all students are more or less on the same track
  • First students have to explain and justify,
  • Later they dont ask for justification anymore?
    mathematical practice

54
Toulmins argumentation scheme
data
conclusion
warrant
backing
55
Toulmins argumentation scheme
4 stamps of 15 cents
Total price 60 cents
56
Toulmins argumentation scheme
4 stamps of 15 cents
Total price 60 cents
4 x 15 60
57
Toulmins argumentation scheme
4 stamps of 15 cents
Total price 60 cents
4 x 15 60
2 x 15 30 30 30 60
58
Roles of the teacher Variety of roles
  • establishing social norms
  • presenting instructional tasks
  • identifying topics for discussion (mathematical
    issues)
  • orchestrating whole class discussions
  • keeping order keeping students involved
  • explaining conventions

59
Summary pro-active role
60
  • Anticipate
  • Make inferences about student knowledge,
    understanding, attitudes, interests
  • Select tasks, HLT ? Goals
  • Enact
  • Introduce instructional tasks
  • Analyze student activity
  • Frame topics for discussion
  • Orchestrate that discussion
  • Cultivate classroom culture
  • Reflect
  • Evaluate the learning trajectory
  • Assess student thinking
  • Look for potentional starting points

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A Local Instruction Theory as a means of support
for teachers
64
Helping students to invent
  • If you want students to invent valuable
    mathematics, you have to offer them support

65
Helping students to invent
  • If you want students to invent valuable
    mathematics, you have to offer them support
  • If you want teachers to help students to invent
    valuable mathematics, you have to offer them
    support

66
Helping students to invent
  • If you want students to invent valuable
    mathematics, you have to offer them support
  • If you want teachers to help students to invent
    valuable mathematics, you have to offer them
    support
  • If you want to help textbook authors to help
    teachers to help students to invent valuable
    mathematics, you have to offer them support

67
What type of support should be offered to
teachers?
  • We should aim at offering teachers means of
    support for construing and revising HLT's
  • By developing prototypical instructional
    sequences and local instruction theories for
    various topics (fractions, long division, )

68
Local Instruction Theory
  • Set of exemplary instructional activities
  • Rationale (theory) that underpins it
  • Learning route
  • Means of support
  • Instructional activities
  • Tools
  • Classroom culture

69
RME Theory
  • RME Design heuristics
  • Guided reinvention
  • Didactical phenomenology
  • Emergent modeling

70
Design heuristics
  • Guided reinvention through progressive
    mathematization
  • A route has to be mapped out that allows the
    students to (re)invent the intended mathematics
    by themselves. (Or experience it as such.)
  • history of mathematics
  • informal solution procedures

71
Design heuristics
  • Didactical phenomenology
  • Present-day applications starting points
  • ? Problem situations that may give rise to
    situation-specific solution procedures
  • Phenomenology of mathematics how the thought
    thing (concept, procedure, tool) organizes the
    phenomenon.

72
Design heuristics
  • Emergent modeling
  • Emergent modeling modeling as organizing the
    model and the conception of what is being
    modeled coevolve.
  • The model
  • overarching model
  • a series of symbolizations/tools

73
Design heuristics
  • Emergent modeling
  • At first a model is constituted as a
    context-specific model of acting in a situation,
  • The model changes character, it becomes an entity
    of its own,
  • and as such it can function as a model for more
    formal mathematical reasoning

74
Data Analysis as an example
  • Design Experiments Middle School Design
    Collaborative NCISLA (OERI) NSF
  • Paul Cobb
  • Kay McClain
  • Cliff Konold
  • Koeno Gravemeijer
  • Erna Yackel (Advisor)
  • Seventh graders (12-years old) - 12 weeks - 34
    sessions - univariate data
  • Eighth graders (13 years-old) - 14 weeks - 41
    sessions - bivariate data

75
Potential endpoint of the learning trajectory
  • mean, mode, median, quartiles, ...
  • as means/characteristics distribution
  • distribution as an object-like entity

76
Distribution as an object
a) All Dutch, c) Families with parents
lt30 b) All married Dutch d) beds for adults
77
Data Aanalysis Minitools
  • Minitool 1

78
Classroom episodesBattery life span
79
  • Casey And I was saying, see like theres
    seven green that last longer.
  • --------------------------------------------------
    -----------------
  • Janice Shes saying that out of ten of the
    batteries that lasted the longest, seven of
    them are green, and thats the most number, so
    the Always Ready batteries are better because
    more of those batteries lasted longer.

80
  • The next student to explain his reasoning, Brad,
    directed the teacher to place the value tool at
    80.
  • Brad See, theres still green ones Always
    Ready behind 80, but all of the Tough Cell is
    above 80. I would rather have a consistent
    battery that I know will get me over 80 hours
    than one that you just try to guess.
  • Teacher Why were you picking 80?
  • Brad Because most of the Tough Cell batteries
    are all over 80.

81
  • Barry Like, if youre using them for
    something real important and youre only
    going to have like one or two batteries, then
    I think you need to go with the most constant
    thing. But if youre going like, "Oh well, I
    just have a lot of batteries here to use,"
    then you need to have most of the highest.

82
Data Aanalysis Minitools
  • Minitool 2

83
Classroom episodesSpeed trap
84
  • Janice If you look at the graphs and look at
    them like hills, then for the before group
    the speeds are spread out and more than 55,
    and if you look at the after graph, then more
    people are bunched up close to the speed
    limit which means that the majority of the
    people slowed down close to the speed
    limit.

85
Cascade of inscriptions
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Three interrelated processes
  • Model shift from model-of to model-for
  • overarching model visual model of a data set
  • The constitution of some new mathematical reality
  • network of mathematical/statistical relations
    notions of density, shape, spread, skewness
    implicit notions of measure and variable
  • a series of symbolizations/tools
  • Value bars
  • Dotplot
  • Four equal groups
  • Box plot

101
Local Instruction Theory
  • Guided Reinvention
  • Didactical Phenomenology
  • Solving applied problems, which gives rise to
    mathematizing or organizing
  • 1. Organizing measurement values ? data points on
    an axis
  • 2. Organizing the distribution in of data points
    ? density
  • 3. Organizing density ? density function

102
Local Instruction Theory
  • Emergent Modeling
  • Model of a set of measures
  • Model for reasoning about a distribution
  • 25 25 25 25

103
Local Instruction Theory
  • Tools and Imagery
  • Use of new tools is grounded in imagery of
    earlier activities
  • History in the learning process ltgt meaning
  • Problematizing tool use as a basis for
    introducing more sophisticated tools experience
    the reinvention process

104
Local Instruction Theory
  • Set of exemplary instructional activities
  • Rationale (theory) that underpins it
  • Learning route
  • Means of support
  • Instructional activities
  • Tools
  • Classroom culture

105
Local Instruction Theory
  • Local instruction theory as a framework of
    reference
  • The teacher will still need to construe his or
    her own hypothetical learning trajectories
  • Adaptations to
  • this teacher
  • these students
  • this moment in time

106
  • Thank you
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