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Early Learning in Mathematics (ELM)

The Efficacy of a Kindergarten Curriculum

Implemented in Whole Classroom Settings

Scott K. Baker, PhD

Pacific Institutes for Research / University of Oregon



Ben Clarke, PhD

Pacific Institutes for Research



Hank Fien, PhD

University of Oregon



Keith Smolkowski, PhD

Oregon Research Institute



Chris Doabler, PhD

Pacific Institutes for Research



David Chard, PhD

Southern Methodist University



IES Conference June 2010

Acknowledgements

Institute of Education Sciences

The research reported here was supported by the Institute of

Education Sciences, U.S. Department of Education, through

Goal 2 development grant, #R305K040081, and a Goal 3

efficacy grant, #R305A080114, to Pacific Institutes for

Research. The opinions expressed are those of the authors

and do not represent views of the Institute or the U.S.

Department of Education.

Additional Oregon Project Staff

Kathy Jungjohann / Karen Davis: Curriculum development

Mari Strand Cary / Rhonda Griffiths: Coordination and research

Chris Doabler: Observation measurement and research

Early Learning in Mathematics

(ELM)

• 4-year randomized efficacy control trial

• Measuring the efficacy of a kindergarten

mathematics curriculum in Oregon and Texas.



• Research Design

• Randomized Controlled Block Design

• Classrooms within school matched on full / half

day and randomly assigned to treatment (ELM)

or control conditions 3

Purpose of the 4-year project

• Study 1: Efficacy trial of the whole group

curriculum (ELM) on kindergarten students’

mathematics achievement

• Study 2: Efficacy trial of small group ELM

component – Roots – on the achievement of

at-risk students

• Examine potential mediation variables, dose-

response variables, and moderation factors

Structure of the Curriculum



• Daily Calendar Lessons / Activities

– 15 minutes daily, whole class “circle” time

– Monthly booklets with objectives and

application activities

• 120 Core Lessons divided into 4 quarters

– 30 minutes whole class instruction

– 15 minutes teacher directed written work

– End of quarter assessment of progress

ELM Instructional Content

• National Math Advisory Panel (2008)

recommends a focused, coherent progression

of mathematics learning with emphasis on

proficiency with key topics

• ELM focuses on key strands rather than a

broad array of mathematical content

– Numbers and Operations

– Geometry NCTM Curriculum Focal

Points for K (2006)

– Measurement

– Vocabulary (NCTM Process Standard, 2000)

ELM Conceptual Framework





Development of Mathematics-related

Mathematical Vocabulary and

Concepts / Models Discourse









Procedural Fluency

Research questions

• What is the immediate impact of ELM taught in

general education kindergarten classrooms on

mathematics achievement compared to standard

district practice?

• Is impact moderated by student level of risk for

mathematics difficulties?

• Does rate of teacher models or student practice

opportunities mediate a condition effect?

• Is there evidence of an interaction between

condition and student practice on student

outcomes?

Study Sample

• Assignment at the classroom level blocked on

school

– Districts = 3

– Schools = 24

• Intervention classrooms = 34

• Control classrooms = 30

• Students nested in classrooms

– Whole class instruction

– N = 1,349

Student Demographics

• 56.3% eligible for free or reduced lunch

• 38.4% English Learners

• 8.4% special education



• 49.5% White

• 36.4% Latino

• 4.8% Asian / Pacific Islander

• 2.3% African American

Hypothesized Model of ELM Impact

Intervention Mediators Proximal Distal

Outcomes Outcomes



Models of Math

Representations



Instruction

ELM Math Procedural Student Math

Quality and Math

Instruction Fluency Achievement

Content





Math Vocabulary

Descriptive data on implementation

• Classroom fidelity observations – treatment

and control

• Classroom observations focusing on

instructional interactions – treatment and

control

• Teacher logs addressing content coverage –

treatment and control classrooms

Implementation Fidelity

• General ratings (8 items)

– Models skills/concepts appropriately and with

ease

– Engages students in learning throughout the

lesson

• Uses ELM / completes all lesson activities

(dichotomous)

• For each ELM activity (range 1-7 per lesson):

Full (2) / Partial (1) / Not Taught (0)

Implementation Fidelity Data:

ELM Lesson Activities

• 81 ELM (fidelity) observations during the year

• Fall : mean = 1.71 (SD = .19)

• Winter: mean = 1.65 (SD = .33)

• Spring: mean = 1.62 (SD = .43)

• Overall: mean = 1.65 (SD = .36) (83% of Full)

• 2 of 81 lessons had a mean below Partial (1)

level of implementation

Student measures of impact

• Test of Early Mathematics Ability (TEMA)

• Early Numeracy – CBM

– Oral Counting

– Number Identification

– Quantity Discrimination

– Missing Number

Method and Analysis Framework

• Competing curricula

– All students received instruction

– Time balanced across conditions

• Sample

– At risk (some or high risk)

• < 40th percentile

• 66% of student sample

– No risk

• ≥ 40th percentile

• 34% of student sample

Nested Time × Condition Analysis

• Outcome: net differences from pre to post

• Nested students within classrooms

– Control for nonindependence (e.g., ICCs)

– Controls for teacher effects

• Maximum likelihood (restricted)

– Includes all cases with data at either T1 or T2

– Reduces bias from missing data

• Moderation added Time × Risk × Condition

interaction

• Effect sizes: Hedges’ g

Sample Means, SDs, and Ns

T No Risk Some Risk

ELM Control ELM Control

TEMA Raw T1 29.0 (6.8) 28.8 (7.3) 14.1 (6.0) 14.6 (6.2)

T2 39.6 (6.3) 39.1 (7.9) 28.6 (8.4) 26.9 (8.0)

TEMA Percentile T1 66.5 (16.4) 65.1 (17.4) 14.5 (11.4) 15.4 (11.7)

T2 70.4 (18.3) 68.1 (20.8) 35.5 (23.6) 31.0 (22.4)

CBM Total T1 120.3 (44.0) 116.7 (43.5) 45.0 (32.6) 45.5 (35.5)

T2 193.1 (35.8) 187.9 (38.1) 138.4 (50.3) 126.6 (50.5)

Sample Size T1 203 181 397 343

T2 190 174 341 312

Note. Standard deviations (SDs) presented in parentheses. For students with some risk at T1, we collected

TEMAs from 53 fewer students in ELM classrooms and 48 fewer students in control classrooms.

TEMA Percentile Scores

Gains by Condition

• Gains

– Control: 10.94

– ELM: 14.73

– Difference: 3.79

• Test of Condition

– t = 2.10

– df = 61

– p = .0396

– ES = +0.14

• T1 differences were not

statistically significant (t = 0.57)

CBM Total Scores

Gains by Condition

• Gains

– Control: 77.20

– ELM: 84.87

– Difference: 7.67

• Test of Condition

– t = 1.99

– df = 61

– p = .0509

– ES = +0.14

• T1 differences were not

statistically significant (t = 0.60)

TEMA Raw Scores

Condition by Risk Status

• Main Effects

– Difference in gains: 1.32

– t = 2.41, df = 61, p = .0190

• Condition by Risk Status

– t = 2.47, df = 61, p = .0162

– No Risk ≥ 40th %tile

• Difference in gains: 0.04

• t = 0.51, df = 61, p = .9586

– Risk < 40th %tile

• Difference in gains: 1.98

• t = 3.29, df = 61, p = .0017

CBM Total Scores

Condition by Risk Status

• Main Effects

– Difference in gains: 7.67

– t = 1.99, df = 61, p = .0509

• Condition by Risk Status

– t = 2.24, df = 61, p = .0289

– No Risk ≥ 40th %tile

• Difference in gains: -0.27

• t = -0.05, df = 61, p = .9570

– Risk < 40th %tile

• Difference in gains: 10.81

• t = 2.54, df = 61, p = .0138

Effect Sizes (Hedges’ g)

Measure Not At Risk At Risk



Tema Raw Score +0.006 +0.242**



EN-CBM Total +0.014 +0.215*



*p < .05; **p < .01

Summary

• ELM classrooms outperformed controls

– TEMA raw and percentile scores

– EN-CBM Total

• Students at risk

– Improve on all measures more than no-risk students

– Control students at risk catching up on no-risk students

• TEMA: 14.0 percentile gain on no-risk students

• EN-CBM: 9.6 point gain on no-risk students

– ELM students at risk catching no-risk students faster

• TEMA: 18.6 percentile gain on no-risk students

• EN-CBM: 20.63 point gain on no-risk students

• No condition effects for students with no risk

Preliminary Analysis of Association between

Observation Data and Student Outcomes

Intervention Mediators Proximal Distal

Outcomes Outcomes

Coding of Academic Teacher-Student

Interactions (CATS) Observation Instrument

 CATS uses a frequency count approach to measure

teacher-student instructional interactions

 Observers code behavior occurrences in a continual, serial fashion.

 Utilizes a strict coding structure



STUDENT BEHAVIORS TEACHER BEHAVIORS

Individual responses Teacher models

Group responses Academic feedback

Covert responses

Mistakes



 CATS based on evidence of effective instruction in early literacy

and beginning mathematics, and adapted from the STICO

observation instrument (Smolkowski & Gunn, 2010)

26

Hypothetical Case of a

Instructional Interaction

The Role of Teacher Modeling and

Student Practice in Student

Outcomes

Preliminary Mediation Analysis

• Does rate of teacher models or student

practice opportunities mediate condition

effect?

• Rates of (a) teacher models, (b) student group

practice opportunity and (c) individual student

practice opportunities entered as mediators to

determine if they decreased condition effect

– Condition effect was still significant

– No evidence to support this mediation hypothesis

Secondary Analysis

• If student practice overall is not mediating

impact, perhaps the value (quality) of practice

differs by classroom and is related to condition

Interaction between Rate of

Practice and Condition

• By condition do rates of practice opportunities

show the same pattern of impact on student

outcomes?

• Are treatment – control differences on student

outcomes similar in classrooms with high rates

of practice vs. low rates of practice?

Interaction between Rate of

Practice and Condition

• Number of Classrooms Control ELM Total

Above 6 26 32

by Treatment Condition Median

and Median Rate of Below 24 8 32

Individual and Group Median

Total 30 34 64

Practice Opportunities

• Practice Opportunity Control ELM Total

Quartiles in Rate per Minimum 0.4 1.0 0.4

Minute 25th %ile 0.8 1.9 1.2

Median 1.3 2.3 1.9

75th %ile 1.7 3.0 2.4

Maximum 4.1 4.1 4.1

TEMA Scores by Rate of Practice

• Within ELM condition

– High-practice classrooms outperform low-practice classrooms

– Difference = 2.59, t = 2.58, df = 29, p = 0.0151

• Within control condition

– No difference between high- and low-practice classrooms

– Difference = 0.39, t = 0.31, df = 29, p = .7575

• Within classrooms with an above-median practice rate

– ELM classrooms (might) outperform control classrooms

– Difference = 2.33, t = 1.85, df = 29, p = .0747

• Within classrooms with a below-median practice rate

– No difference between ELM and control classrooms

– Difference = 0.14, t = 0.14, df = 29, p = .8935

EN-CBM Scores by Rate of Practice

• Within ELM condition

– No difference between high- and low-practice classrooms

– Difference = 9.83, t = 1.46, df = 29, p = 0.1538

• Within control condition

– No difference between high- and low-practice classrooms

– Difference = -7.59, t = -0.92, df = 29, p = .3635

• Within classrooms with an above-median practice rate

– ELM classrooms outperform control classrooms

– Difference = 19.37, t = 2.35, df = 29, p = .0257

• Within classrooms with a below-median practice rate

– No difference between ELM and control classrooms

– Difference = 1.95, t = 0.29, df = 29, p = .7731

Next steps

• Have just completed implementation of Study

1 in Dallas, Texas

• Have just completed implementation of Study

2 in Oregon

• Will implement Study 2 in Dallas, Texas in

2010-11

• Ongoing analysis to investigate impact of

condition and mediation and moderation

variables associated with impact



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