EC A Partnership for Research with Elementary Math and Science - - PowerPoint PPT Presentation

Every Day, Every Child:

A Partnership for Research with Elementary Math and Science Instructional Specialists

ED EC

This material is based upon work supported by the National Science Foundation under Grant No. DRL-

• 1316520. Any opinions, findings, and conclusions or

recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Elementary Science Instruction

• 3 basic models, with sub-categories (Gess-

Newsome, 1999)

– Classroom generalist model (traditional self- contained) – Specialist: Student Instructional Models*

• Departmentalized model, or Collaborative Specialist (Nelson

& Landel, 2007) >>> Team-Teaching

• Pull-out model >>> Science as a special

– Specialist: Teacher Mentoring Models

• Resource/Coaching model
• Science support team model

Our focus: Elementary Science Instructional Specialists

Operational definition: An instructional specialist is a full time (elementary) classroom teacher who teaches two or more classes of students in a specific content area. …but the devil is in the details

Our Project - Five Studies

EDEC is an exploratory research project to

• Study 1: understand and categorize instructional

specialist models in mathematics and science;

• Study 2: investigate the content knowledge,

preparation and needs of teachers in these roles;

• Study 3: determine the instructional effectiveness
• f instructional specialists; and
• Study 4: determine the impact of instructional

specialists on student learning and attitudes towards mathematics and science.

• Study 5: identify the prevalence of models of

content specialization in mathematics and science in elementary schools nationally.

Science Specialist Sample

• Year one – 15 total

– 10 participated as science specialist only – 5 participated as both math & science specialist

• Year two – 15 total

– 8 participated as science specialist only – 7 participated as both math & science specialist (two had been science only & added math)

• 19 total specialists completed at least part of study (4

lost due to retirement, reassignment, & attrition)

• 6 districts, 13 schools

Specialists & Self-Contained Matches: Demographics

Demographic Elementary Science Specialists Science Self-Contained Participants Mean age (years) 46.6 44.3 Mean teaching experience (years) 15.6 18.2 Mean school % FRL students 48.4 52.5 Mean school % students of color 35.3 36.7

Diversity of Models in Our Sample

Model Other subjects taught besides science # of Teachers Team-Teaching (within- grade) All but reading (1) or mathematics (1) 2 Team-Teaching (within- grade) 2-3 of Spanish literacy, math support in Spanish, social studies 2 Team-Teaching (within- grade) Math (all 6) plus some combination of writing, social studies, and/or art 6 Team-Teaching (within- grade) Social studies (2); word study (1) 2 Team-Teaching (across- grades) Reading, social studies, art (1); None (1) 2 Science as a special Technology (2); Reading (1); None (2) 5

Study 2

Study 2 Research Question & Measures

• RQ: How do factors related to teacher

preparation & content knowledge differ for instructional specialists & non-specialist teachers?

• Measures

– Online survey (preparation) – Harvard MOSART (content knowledge)

• Astronomy/Space Science, Earth Science, Life

Science, Physical Science subtests

Findings – Formal Preparation

• Specialists were more likely to have completed a

science content degree (N = 5, 26%) than self- contained teachers (N = 0)

• Specialists and self-contained teachers were equally

likely to have completed a science education degree (N = 3, 16% for specialists; N = 3, 19% for self- contained)

Findings – Preparedness

• Specialists rated themselves higher (p < 0.05, two-tailed

independent samples T-test) on survey questions assessing:

– Preparedness to teach science – Familiarity with NGSS – Preparedness to teach engineering content – Agreement with:

• “I know the strengths & weaknesses of each of my students in

science”

• “I have enough time with my students to meet their needs in

science”

• “I have enough time to plan for all the subjects I teach”

Findings – Content Knowledge

MOSART Test Specialists (N=19) Self-Contained (N=16) Mean Difference p value (1- tailed) Effect size (Hedges’ g) Mean SD Mean SD Astro/Space 74.74% 14.81 pp 62.67% 22.84 pp 12.07 pp 0.036* 0.6243 Earth 87.16% 9.94 pp 80.00% 12.38 pp 7.16 pp 0.035* 0.6293 Life 85.26% 10.42 pp 81.87% 12.91 pp 3.40 pp 0.201 0.2851 Physical 70.00% 13.54 pp 60.67% 15.10 pp 9.33 pp 0.034* 0.6388 OVERALL 80.42% 9.21 pp 72.93% 13.74 pp 7.49 pp 0.034* 0.6367

Study 3

Study 3 Research Questions & Measures

• RQ1: How does the quality of instruction of science

specialists compare to that of matched non-specialist teachers?

• RQ2: What factors related to preparation, content

knowledge, & instructional model predict qualify of instruction?

• Measures

– Modified AIM Observation protocol (Horizon Research) – Online Survey + MOSART scores

Study 3 Findings – Instructional Quality

* Indicates p < 0.05, two-tailed

Score Type Teacher Type N of Observations Mean SD Effect Size (Hedges' g) Adjusted Total Specialist 47 2.8436 0.65112 0.3688 Self-Contained 44 2.6015 0.65049 Targeted Idea Specialist 47 2.9362 0.81838 0.3063 Self-Contained 44 2.6818 0.82892 Initial Ideas Specialist 30 2.7333 0.69149

• 0.0607

Self-Contained 28 2.7857 0.99469 Engaging with Phenomena Specialist 45 2.8667 0.78625

• 0.0826

Self-Contained 43 2.9302 0.73664 Using Evidence to Make Claims* Specialist 39 2.6923 0.95018 0.5155 Self-Contained 41 2.2439 0.76748 Sense Making* Specialist 21 2.4286 0.87014 0.6577 Self-Contained 24 1.875 0.78741 Classroom Culture Specialist 47 3.0851 0.58346 0.3312 Self-Contained 44 2.8409 0.86113

Differences in Instructional Quality

• Specialists scored significantly higher on the

following lesson aspects, with medium effect sizes:

– Using evidence to make claims – Sense-making

• What factors might predict these differences? What

is it about being a specialist that made the difference?

Study 3 – Predictors of Observation Scores

• Variables included in stepwise regression:

– Teacher Type (specialist / self-contained) – Composite MOSART scores (content knowledge) – Number of semester science or science education courses completed by teacher – Years of teaching experience – Time per week spent teaching science – Time per week spent planning for science – Whether teacher had completed science PD in last 3 years* *Note: Nearly all specialists had completed recent science PD while very few matches had done so, making this variable nearly identical to the variable for teacher type

Study 3 Findings – Predictors of Observation Scores

Best model predicting score on using evidence to make claims was one that only included MWSP – minutes per week of science planning

Model Summary Model R R Square Adjusted R Square

• Std. Error of the

Estimate 1 .302a .091 .079 .79657

• a. Predictors: (Constant), MWSP

ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 4.598 1 4.598 7.246 .009b Residual 45.686 72 .635 Total 50.284 73

• a. Dependent Variable: EvClaims
• b. Predictors: (Constant), MWSP

Study 3 Findings – Predictors of Observation Scores

Best model predicting score on sense-making was one that only included MWSC – minutes per week spent teaching science content

Model Summary Model R R Square Adjusted R Square

• Std. Error of the

Estimate 1 .380a .145 .124 .77686

• a. Predictors: (Constant), MWSC

ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 4.289 1 4.289 7.106 .011b Residual 25.348 42 .604 Total 29.636 43

• a. Dependent Variable: SenseMake
• b. Predictors: (Constant), MWSC

Summary

• Elementary science specialists in our sample scored

higher than self-contained teachers on measures of content knowledge and preparation to teach science

• Specialists appeared to be more skilled at leading

students through the processes of using evidence to make claims and sense-making.

– Differences primarily attributable to specialists having MORE TIME to both plan for and engage students in science lessons

Limitations

• Sample size (< 20 per teacher type)
• Possible limitations of content knowledge measure
• Data on time spent planning for & teaching science

are self-report

Thank you!

• Participating students & teachers
• Today’s audience

Joe Brobst, Ed.D. Science, Mathematics, & Technology Education Western Washington University Joe.Brobst@wwu.edu (302) 383-5194 (cell)