Math Infusion into Science Project James Lauckhardt, Ph.D. Center for Advanced Study in Education CUNY Graduate Center

S T E M

Math Infusion into Science Project

James Lauckhardt, Ph.D.Center for Advanced Study in Education

CUNY Graduate Center

The Math Infusion into Science Project (MiSP)

NSF Funded development, research, and evaluation grant awarded to investigate the benefit of contextualized learning (Math infused Science)

• A project that grew from the Math Science Technology Partnership program

• Emphasizes the importance of thinking differently than traditional siloh-style learning

• The recommendation to make connections between math and science is built upon the rationale that the two disciplines contain similar functionalities (Bosse, Lee, Swinson, & Faulconer, 2010)

MiSP Intervention Details26 Math Infused Science Units Developed by Two Curriculum Experts

• Target grade level is 8th grade

• Intended to include Earth Science Regents, Living Environment Regents, and 8th Grade General Science content areas

• 5-day activities that include a teacher’s guide, and introduction, 2-3 lab activities, and assessment worksheets for students

• The math infused in each unit included:

Level 1: Graphing - Identifying/Interpolating/Extrapolating Level 2: Slope - Understanding and Calculating Level 3: Linear Equations – Understanding and Calculating

MiSP Intervention DetailsTeachers Identified 6 Units to Teach Throughout the Year

• Trained in approximately 16 total units that they were interested in learning about, and chose 6 based on their experience and preference

• Infused in the first, second, and third quarters of the school year, leaving the fourth quarter for test prep and wrap-up

• Two units infused per quarter

• Teachers received the units that included the appropriate level of math based on the time of year the unit was being taught.

First Quarter - Level 1: Graphing - Identifying/Interpolating/Extrapolating Second Quarter - Level 2: Slope - Understanding and Calculating Third Quarter - Level 3: Linear Equations – Understanding and Calculating

2010 - 2011

Academic

Attitude

Participant/Data Type Cohort 2 Cohort 3Cohort 1

7th Grade NYS test Math Score

Pre/Post MiSP Content Assessment

Monthly MiSP Do Now Assessment


8th Grade NYS test Science Score

Pre/Post MiSP Attitude Assessment






9th Grade NYS test Math and Science Score for a sub-sample of

Cohort 1






Pre/Post MiSP Attitude Assessment Pre/Post MiSP Attitude Assessment

Stud

ent L

evel

Dat

aTe

ache

r Lev

el D

ata

Academic

Attitude


SCOR – Observation Assessment


SCOR – Observation Assessment

6 Unit Reflection Surveys

Summer training Feedback Survey

End of Project Feedback Survey

6 Unit Reflection Surveys

Summer training Feedback Survey

End of Project Feedback SurveyEnd of Project Feedback Survey

Semi-Annual Reflection Surveys

2011 - 2012 2012 - 2013

Data Collection Procedures

Cohort 2: 2011 - 2012

Cohort 3: 2012 - 2013 – Sub Sample

Cohort 1: 2010 - 2011

8 Schools

20 Teachers

10 Infusion 10 Comparison

1,650 Students


14 Schools

33 Teachers


2,205 Students

2,036 Infusion 169 Comparison

4 Schools

12 Teachers – All Infusion

~ 350 Students

Sample Characteristics

Cohort 1: 2010 - 2011

20 Teachers


Class Characteristics

GroupAssignment

General Science

Living Environme

nt

Earth Scien

ce

Comparison 22 7 3

Infusion 31 3 -

Cohort 1: 2010 - 2011

1,650 Students


Sample Characteristics

Demographic Characteristic

MiSP Group

Total Comparison

Infusion

Gender Male 48.40

%48.30

%54.80

%Female 51.60

%51.70

%45.20

%Ethnicity

Asian 10.20%

8.30%11.90

%African-American

7.90% 3.90%11.50

%White 71.40

%73.80

%69.30

%Hispanic 10.30

%14.00

%7.00%

Other 0.10% 0.00% 0.20%Eligible for Free of Reduced Lunch

27.30%

24.80%

29.50%

Limited English Proficiency

4.10% 3.30% 4.90%

Special Ed or IEP 6.90% 8.30% 8.80%


Description of Student Assessment Tools

29 Questions

Type Cognitive Complexity Level of Math

16 Multiple Choice Questions

13 Open-ended Questions

8 Knowledge Questions

14 Application Questions

7 Reasoning Questions

16 Level One Questions

7 Level Two Questions

6 Level Three Questions

Pre/Post MiSP Attitude Assessment


29 Questions

Confidence Using Linear

Equations

Confidence with Graph

Construction

Math Self-Efficacy

Math Interest Math Applicability

Math is important for completing tasks in science

Math makes learning science easier

Math is interesting

I am interested in a Math related career

I am good at Math

I can get good grades in Math

Setting up a graph

Identifying independent and dependent variables

Using a graph to write the equation of a line

Using a data table to calculate slope

Standardized NYS Test Scores:

• 7th grade Math State Assessment Score (Scale and Level)

• 8th Grade Math State Assessment Score (Scale and Level)

• 8th Grade Science State Assessment Score (Scale and Level)

• 8th Grade Science Regents Score (if applicable)

• For 2010 – 2011 8th Grade students, in the process of collecting their 9th grade Math and Science Regents scores


Observation Rubric:

• SCOP-Revised: Science Content Observation Protocol

Rubric assesses the following domains on a scale of 0 (poor/ not evident) to 6 (excellent/extremely evident):

o Learning Objectiveso Developing Understandingo Sense-Makingo Classroom Culture

Description of Teacher Assessment Tools

Pre/Post Intervention Content Knowledge:

• MiSP Developed Assessment

Asks teachers to1. Solve common MiSP-based content problems2. Identify areas in which they feel students will have

trouble3. Provide teachers with sample MiSP student work and

have them identify errors and comments they might make to help students better understand the content.


Scored by two Math/Science Content Experts

6 Unit Feedback Surveys:

• MiSP Developed Assessment

Completed upon finishing one of the 6 units they chose Asks teachers to

1. Indicate the length of time the lesson took to complete

2. Evaluate the lesson based on their experience


Group N Pre-MiSP Mean % correct Post-MiSP Mean % correct Mean Diff.

Infusion 641 40.70 54.78* 14.08

Comparison 559 44.01 49.48* 5.47

Preliminary Student Outcome Results

Pre/Post Group Differences

KAR Area

Infusion Comparison

Pre-MiSP lesson

Post-MiSP lesson

Change (Post-Pre)

Pre-MiSP lesson

Post-MiSP lesson

Change (Post-Pre)

Knowledge 49.24% 73.63%* 24.39% 54.25% 66.15%* 11.90%

Application 39.02% 58.09%* 19.07% 42.90% 53.43%* 10.53%

Reasoning 34.52% 40.00%* 5.48% 34.73% 35.70% .97%


Pre/Post Group Differences by Cognitive Complexity

Level

Infusion Comparison

Pre-MiSP Post-MiSP Difference Pre-MiSP Post-MiSP Difference

One 48.66% 69.01%* 20.35 53.45% 62.27%* 8.82

Two 54.05% 64.36%* 10.31 56.58% 60.44%* 3.86

Three 17.45% 36.70%* 19.25 19.14% 32.87%* 13.73


Pre/Post Group Differences by Level of Math

Pre Post Pre Post Pre Post Pre Post Pre Post Pre Post Pre Post Pre PostComp Inf Comp Inf Comp Inf Comp Inf

1 2 3 4Quartiles

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

19.914.0

28.4

9.8

25.2

17.7

27.3

10.3

26.123.4 23.2

21.8

28.8

44.9

21.1

58.0

Perc

enta

ge

5.9 18.67.5

17.0

2.7 1.4

16.1

36.9

Quartile Categorization at Post-test Based on Pre-test Categories

Infusion Control56

58

60

62

64

66

68

70

72

69.8

60.7

Differences in 8th grade math assessment ratings of "pro-ficient" by group controlling for 7th grade proficiency lev-

els

8th grade math assessment

Group

% C

ateg

oriz

ed a

s Pr

ofici

ent

9.1% difference

What We’ve Learned about Interconnected Learning

• Interconnected learning is doable for teacher and students within a regular class period

• Teachers need professional development in both pedagogy and content being infused

• Students learn each content area in greater depth

• When technology is included there must be options for hands on work

• Students recognize the importance of infusion and develop more positive attitudes towards both content areas

• Stakeholder buy-in is critical for success

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Issues We Have Encountered – DATAG, help!

• Deidentification of data – Who, what, where, why, how

• Lack of access to individual item-level data

• Students learn each content area in greater depth

• Utilization of data results in the classroom– What support is given?– How do we know it is being “utilized” effectively– Are there tangible improvements documented?

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• WISEngineering

• Simulation and Modeling in Technology Education (SMTE)

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Two of Our Other Relevant Projects

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S T E M

• WisEngineering

WiseEngineering is Next Generation Learning Grant that is using engineering pedagogy to teach mathematics using a web-based delivery system that allows for instruction to incorporate both computer based and hands on learning. Lessons engage students in a community based design task, reflections and embedded assessments

Design Cycle – Design Challenge 24

25Design Cycle – Develop Knowledge

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S T E M

• SMTE Simulation and Modeling in Technology

Education (SMTE) is a DR-K12 project to develop and research the academic potential of a mathematics and engineering infused hybrid instructional model and a set of prototypical materials that integrate 3-D simulation, educational gaming, and real-world physical modeling into middle school technology education programs.

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Math Infusion into Science Project James Lauckhardt, Ph.D. Center for Advanced Study in Education CUNY Graduate Center