it is time to reveal what students with mld know, rather ... is time to... · it is time to reveal...

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Marja van den Heuvel-Panhuizen Faculty of Social and Behavioural Sciences Faculty of Science Freudenthal Institute It is time to reveal what students with MLD know, rather than what they do not know

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Page 1: It is time to reveal what students with MLD know, rather ... is time to... · It is time to reveal what students with MLD know, rather than what they do not know

Marja van den Heuvel-Panhuizen

Faculty of Social and Behavioural Sciences

Faculty of Science

Freudenthal Institute

It is time to reveal

what students with MLD know,

rather than what they do not know

Page 2: It is time to reveal what students with MLD know, rather ... is time to... · It is time to reveal what students with MLD know, rather than what they do not know

• implies a change in assessment:

Assessing (MLD) students’ mathematical potential

• implies a change in teaching:

Building on what (MLD) students already know

Knowing what students know is the starting point of good instruction

Looking for what students know

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• implies a change in assessment:

Assessing (MLD) students’ mathematical potential

• implies a change in teaching:

Building on what (MLD) students already know

Knowing what students know is the starting point of good instruction

Looking for what students know

Page 4: It is time to reveal what students with MLD know, rather ... is time to... · It is time to reveal what students with MLD know, rather than what they do not know

Examples

IMPULSE project

1. Offering students problems in which they can

show their competence

1a. Within curriculum: Subtraction problems

1b. Beyond curriculum: Combinatorial problems

FaSMEd project

2. Offering students optional auxiliary tools:

Percentage problems

“Going across the grain” study by Watson (2002)

3. Advanced mathematical thinking by

low attaining students

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Example 1a

Offering students problems

by which they can show their

competence Subtraction problems that

elicit strategies

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Study with Special Education students

56 students from 14 classes in SE school

8-12 years old, mathematics level Grade 2

15 problems

Example 1a

Is there evidence for this?

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next

29 euro discount

62 euro

Example 1a

Direct Subtraction

DS strategy

Taking Away Context

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next

Example 1a

Indirect addition

IA strategy

Adding On Context

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IA use and problem format

Example 1a

Adding On Context

Taking Away Context

Bare number

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IA use and numbers involved

56-52 31-29 51-39 47-15 56-28

Example 2a

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Conclusions

o SE students can make spontaneous use of IA

• DS 63%

• IA 34%

• Average IA use per student 4.6 (min 0, max 8)

o SE students are rather flexible in applying IA

o SE students are quite successful when applying IA

• DS 51% correct

• IA 68% correct

Example 1a

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Example 1b

Offering students problems

in which they can show their

competence:

Combinatorial problems

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84 students (age M = 11.1) from 5 SE schools

76 students (age M = 9.4) from 5 RE schools

mathematics levels Grade 2-5

Participants:

6 combinatorial problems in ICT environment

Instrument:

Example 1b

Can special education students solve combinatorial

problems?

Research question:

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Example 1b

Correctly solved problems

SE students RE students

56% 57%

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Example 1b

• systematic

• semi-systematic

• non-systematic

Strategy use:

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Frequency (%)

of strategy use

Example 1b

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Example 2

Offering students optional

auxiliary tools:

Percentage problems

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• Web-based

• Monitoring function

• Problems based on key competencies

• Auxiliary tools

Example 2

Grade 6 teacher about his student Ducan:

“He belongs to the low-level stream in my class and

now he did three of the six problems correctly!”

Six problems on percentage

Digital Assessment Environment

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Example 2

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Example 2

The tool

icon is

clicked

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Example 2

The purple

bullet is

moved up

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Example 2

Red bullet

is moved

to the left

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Example 2

The

answer is

filled in

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Example 2

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66

Example 2

Wrong answer,

but what do the

auxiliary tools

tell the teacher ?

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66

Example 2

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Example 2

Wrong answer,

but what do the

auxiliary tools

tell the teacher ?

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Example 2

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Example 3

Advanced mathematical

thinking by low attaining

students

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Example 3

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“Going across the grain” study by Watson (2002)

Deficiency-based approach

Proficiency-based approach

Example 3

“ ‘Low attaining students’ are generally

classified […] on the basis of

accumulated incompetence in tests and

other written work.”

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“All could do this after some thought”

These low attainers showed that they can

- identify and use patterns

- work with abstractions and relations

Example 3

23×7 = 161 ………. ………. ……….

“Students soon realized that the answers to the 1st and 2nd

column were obtained by adding 7. …”

7×23 = 161 161/23 = 7 161/7 = 23

Then they were asked to continue the horizontal pattern,

which was completely new for them

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Research on MLD needs a

proficiency-based approach

It is time to reveal

what students with MLD know,

rather than what they do not know

[email protected]