Top Banner
What Happens When We “STEMify” Our Schools? Mapping the direction of Owatonna’s STEM initiative. Tom Meagher, PhD District STEM Coordinator Owatonna Public Schools Owatonna, MN MnCOSE 2015
29
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: Msta 2015

What Happens When We “STEMify” Our Schools?

Mapping the direction of Owatonna’s STEM initiative.

Tom Meagher, PhDDistrict STEM Coordinator

Owatonna Public SchoolsOwatonna, MNMnCOSE 2015

Page 2: Msta 2015

The status of STEM Education in MNResults of how students taking the ACT fared

based on interest and performance in STEM fields on 2013 ACT exams.

Differences in student interest and academic performance shows more divergence when examined by ethnicity.

Results of this study did not explore if students had previous schooling in STEM.

Page 3: Msta 2015

Minnesota College Readiness as Measured by ACT Exam 2013

Page 4: Msta 2015

MN ACT Data by ethnicity & gender

“Essentially, stronger and earlier support structures and interventions related to career and educational planning and academic preparedness are needed to see real differences in these still troubling numbers.” [College Board]

Page 5: Msta 2015

Models of STEM Teaching & Learning

Science, technology, engineering and math are taught, but are separate subjects.

Science

Engineering Math

Technology

Page 6: Msta 2015

STEM subjects are integrated.

Science

Engineering Math

Technology

STEM

Page 7: Msta 2015

STEM is embedded in all subject areas

Math

Technology

STEM Curriculum

Science

Engineering

Page 8: Msta 2015

What STEM means in ISD 761

Teaching of Science, Technology, Engineering, & Math is shifting from traditional instruction to integrated lessons where students solve problems and engineering challenges in classes.

STEM embedded among all subject areas emphasizes that all students can learn rigorous academic subject matter.

Students recognize that the main goals of lessons build with each other and relate to real world learning.

Lessons are designed to build:

“STEM literacy & STEM fluency”

Page 9: Msta 2015

Developing a learning modelWe agree with the emphasis for STEM literacy &

fluency, however STEM experience is essential to develop literacy and fluency skills.

Students are engaged in active investigations, inquiry and engineering challenges as common experiences.

We want students to publish their work and share it with others “Show-it”. This allows for multiple forms of student dialogue and publication.

When all these ideas are combined a STEM learning model emerges:

Page 10: Msta 2015

A teaching & learning model for Owatonna STEM Schools

Page 11: Msta 2015

STEM learning model guides instruction in all content areas such

as: ELL: Using STEM experience for front loading language development.

Environmental Education “ESTEM”: Builds STEM learning on a foundation of environmental principles examining how society, culture and ecosystems interact.

Physical Education & Music incorporate science and engineering into kinesthetic lessons.

Special Education: Integrating STEM into IEP and inclusion learning creates opportunities for differentiation.

Perpich Foundation & Art: Integration of Arts into STEM lessons at all grade levels.

NEXUS: Using STEM to address social & racial achievement gaps in student learning.

PAGE: Addressing gender equity through STEM.

Page 12: Msta 2015

Measuring the Impacts of the Owatonna STEM Education Initiative

Student Attitudes Towards STEM interest survey using tool developed by North Carolina University (NCU).

STEM teaching efficacy survey also created by NCU School of Education with a National Science Foundation Grant.

NWEA and Dibels student academic growth data.

MCA III proficiency scores, delineated by ethnicity and gender for each grade level and STEM site.

Community engagement and involvement with STEM schools & ESTEM Teams

Page 13: Msta 2015

Student attitudes towards Math

1.0

2.0

3.0

4.0

5.0

African 3.7

Asian4.5

Hispanic3.7

Multiracial3.7

Native American3.0

Caucasian3.9

Response to: "I am good at math"

Mean scores of major ethnic groups

SD

D

N

A

SA

Page 14: Msta 2015

Student attitudes towards Science

1.0

2.0

3.0

4.0

5.0

Series31.0

1.0

1.0

1.0

1.0

1.0

Response to: "I know I can do well in science."

Mean scores for major ethnic groupsSD

D

N

A

SA

Page 15: Msta 2015

Student attitudes towards careers in science

1.0

2.0

3.0

4.0

5.0

Series31.0

1.01.0

1.0

1.0

1.0

Response to: "I would consider a career in science"

Mean scores of major ethnic groups

SD

D

N

A

SA

Page 16: Msta 2015

Student attitudes toward engineering careers

1.0

2.0

3.0

4.0

5.0

Series31.0

1.0

1.0

1.01.0

1.0

Response to: "I know I could do well at a career in engineering"

Mean scores for major ethnic groups

SD

D

N

A

SA

Page 17: Msta 2015

Gender attitudes of engineering careers

1.0

2.0

3.0

4.0

5.0

Series31.0

1.0

1.01.0

1.0

Response to: "I would consider a career in engineering.

Mean MALE scores for major ethnic groups

SD

D

N

A

SA

1.0

2.0

3.0

4.0

5.0

Series31.0

1.0 1.0

1.0

Response to: "I would consider a career in engineering."

Mean FEMALE scores for major ethnic groupsSD

D

N

A

S

A

Page 18: Msta 2015

Responses from students on “Student Attitudes Towards STEM Learning Survey

Prompt: “What did you learn this year that had an impact on you?” & “What would you tell other students about STEM?”

4th Grade students at McKinley WORDLE of response data:

Page 19: Msta 2015

Responses from students on “Student Attitudes Towards STEM Learning Survey

Prompt: “What did you learn this year that had an impact on you?” & “What would you tell other students about STEM?”

5th Grade students at McKinley WORDLE of response data:

Page 20: Msta 2015

Responses from students on “Student Attitudes Towards STEM Learning Survey

Prompt: “What did you learn this year that had an impact on you?”

6th Grade students at Willow Creek WORDLE of response data:

Page 21: Msta 2015

Teacher attitudes towards STEM

Page 22: Msta 2015

Growth Area for Professional Development & Instructional Support

Page 23: Msta 2015

Teachers’ perceptions of STEM

Page 24: Msta 2015

Student academic performance

Preliminary results show improvement in test scores.

Significant differences are observed among ethnic groups in reading and math.

Growth rates in reading and math are highest among minority and low SES students across the K-8 STEM students.

Students with 2 years of STEM appear to have higher scores than peers with less than 2 years.

Analysis of two years worth of student performance scores will show more detailed information.

Page 25: Msta 2015

Mean Math MCAIII performance by ethnicity for sum percent of “meets” &

“exceeds” benchmark.

2010-11 2011-12 2012-13 2013-14

African 17.8 32 37.4 48.1

Hispanic 35.3 61.1 44.4 50

White 69.7 71.1 71.7 75

5.0

15.0

25.0

35.0

45.0

55.0

65.0

75.0

85.0

95.0

Sum

Perc

ent

pro

fici

ency

for

"meets

" &

"exc

eeds"

bench

mark

s

Page 26: Msta 2015

Mean Reading MCAIII performance by ethnicity for sum percent of “meets” & “exceeds” benchmark.

2011-12 2012-13 2013-14

African 58.3 40.7 28.5

Hispanic 53 33.3 50

White 84.2 58.6 60.8

5

15

25

35

45

55

65

75

85

95

Sum

Perc

ent

pro

fici

ency

for

"meets

" &

"exc

eeds"

bench

mark

s

Page 27: Msta 2015

Academic progress at McKinley STEM School: Reading

Sate Non-ELL

School ELL

State Non-SpEd

School SpEd

State FRP School FRP

0

0.1

0.2

0.3

0.4

0.5

0.0035

0.3288

0.021

0.3056

0.0686

0.1344

Comparison of Non-ethnic cells Reading MCA

Whi

te (s

tate

)

Nativ

e Am

erica

n

Africa

n

Asian

Hispan

ic -0.1

-5.55111512312578E-17

0.1

0.2

0.3

0.4

0.5

0.0283

0.3917

0.092

-0.0161

0.3187

Comparison of growth among ethnic groups: Reading MCA

Page 28: Msta 2015

Academic progress at McKinley STEM School: Math

Sate Non-ELL

School ELL

State Non-SpEd

School SpEd

State FRP School FRP

0

0.1

0.2

0.3

0.4

0.5

0.0034

0.3022

0.0265

0.3674

0.0818

0.1986

Comparison of Non-ethnic cells Math MCA

White (s-tate)

Native American

African Asian Hispanic

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

0.0317

2.1764

0.3139

-1.2326

0.4988

Comparison ethnic groups Math MCA

Combined Math Reading Combined Math reading

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.2361

0.3461

0.1247

-0.2237-0.2651

-0.1819

MMR Growth

Achievement Gap Reduction

Page 29: Msta 2015

Questions?