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Using the SIOP Model to Promote theAcquisition of Language and ScienceConcepts with English LearnersJana Echevarria a , Catherine Richards-Tutor a , Rebecca Canges b &David Francis ca California State University , Long Beachb Metropolitan State College of Denverc University of HoustonPublished online: 05 Dec 2011.

To cite this article: Jana Echevarria , Catherine Richards-Tutor , Rebecca Canges & David Francis(2011) Using the SIOP Model to Promote the Acquisition of Language and Science Concepts withEnglish Learners, Bilingual Research Journal: The Journal of the National Association for BilingualEducation, 34:3, 334-351, DOI: 10.1080/15235882.2011.623600

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Bilingual Research Journal, 34: 334–351, 2011Copyright © the National Association for Bilingual EducationISSN: 1523-5882 print / 1523-5890 onlineDOI: 10.1080/15235882.2011.623600

Using the SIOP Model to Promote the Acquisitionof Language and Science Concepts with English Learners

Jana Echevarria and Catherine Richards-Tutor

California State University, Long Beach

Rebecca CangesMetropolitan State College of Denver

David FrancisUniversity of Houston

In this article we report findings from research through the Center for Research on the EducationalAchievement and Teaching of English Language Learners (CREATE), a National Research andDevelopment Center. In our study we examined the efficacy of a model of instruction for Englishlearners, the Sheltered Instruction Observation Protocol (SIOP) Model, in one content area, sci-ence. Assessments measured the acquisition of academic language and science concepts amongEnglish learners, former English learners, and English Only students in middle school scienceclassrooms. Results indicated that students in the SIOP group performed better than controls,although not to a significant degree. Reasons for these findings are explored. Due to differen-tial attrition of schools in the control group, caution must be used in interpreting the study’sfindings.

Jana Echevarria is Professor Emeritus at California State University, Long Beach and is a coauthor of the SIOP Model.She is a Co-PI for CREATE, the National Research and Development Center for English language learners funded byIES. Her research focuses on effective instructional methods for English learners.

Catherine (Cara) Richards-Tutor is currently Associate Professor at California State University, Long Beach, whereshe recently received the Early Career Achievement Award. Her research focuses on effective interventions for studentsat risk, including English learners, and response to intervention models.

Rebecca Canges is currently Assistant Professor at Metropolitan State College of Denver. Before receiving herdoctorate at University of Southern California, she was a special education middle school teacher. Her research focuseson effective instruction for English learners and social acceptance of students with disabilities.

David Francis obtained his PhD in 1985 from the University of Houston. He is a Fellow of Division 5 of APA andan inaugural Fellow of AERA. His research has been funded by NICHD and IES and focuses on reading development,reading disabilities, and at-risk populations, including ELLs.

Address correspondence to Jana Echevarria, California State University, Long Beach, Department of AdvancedStudies in Education & Counseling, 1250 Bellflower Blvd., Long Beach, CA 90840. E-mail: jechev@csulb.edu

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INTRODUCTION

Learning about science is difficult for American students. Every indicator shows that scienceperformance in school for U.S. students overall is persistently low (National Center for EducationStatistics, 2009). The problem is even more critical in the current environment of standards-basedinstruction, high-stakes testing, and accountability.

In the present study, funded through the Center for Research on the Educational Achievementand Teaching of English language Learners (CREATE), a National Research and DevelopmentCenter, we set out to test the effects of a model of instruction for improving the performanceof English learners on their acquisition of content area concepts and language development inscience. With a growing emphasis on science in schools coupled with the expansion of No ChildLeft Behind (NCLB) testing to science, English learners’ ability to read, write, and discuss sci-ence concepts is more critical than ever (Cavanaugh, 2007), even though not all states use testresults for accountability purposes.

The study’s approach was to provide a set of instructional strategies and techniques to scienceteachers to assist them in helping English learners access science content. Typically, scienceinterventions focus on science content and inquiry. Although many of the features of the projectare compatible with an inquiry approach to science, this study is unique in that its explicit goalwas to provide teachers with the kind of teaching techniques intended to make science contentcomprehensible for English learners as well as to develop their academic language.

THE ACADEMIC PERFORMANCE OF ENGLISH LEARNERS

The academic achievement of English learners is of critical concern because of their large andgrowing numbers. During the decade from 1998–99 to 2008–09, the English learner (EL) popula-tion in pre-K–12 schools increased 51%, but the total pre-K–12 population, which includes thesestudents, grew only 7.2% (NCELA, 2011). English learners’ performance in science is signifi-cant because of its importance in the overall curriculum and to students’ future success (Lee &Luykx, 2006; Short, Vogt, & Echevarria, 2011). Since NCLB testing began including science inassessments, increased attention has been directed toward this content area (Cavanaugh, 2007).Schools are carefully examining the time spent on teaching science as well as the science curricu-lum being used to ensure that it is aligned to state and national standards. For English learners,science lessons need to be meaningful so that they can comprehend the lesson’s content, partici-pate fully in class, and be able to express themselves using the language of science (Dong, 2005;Echevarria & Colburn, 2006).

Rather than viewing diverse students as deficient, English learners can use their linguisticand cultural experiences as “intellectual resources” for learning science (Lee, Luykx, Buxton, &Shaver, 2007). For Spanish-speaking students, the use of cognates is an effective way of usingtheir native language as a bridge to comprehending vocabulary in English and expanding theirrepertoire of English words (García, 1991). For example, the English word bacteria trans-lates to bacterias in Spanish and genetic information translates to la información genética.Teachers should explicitly teach cognates since English learners may not recognize the relation-ship between a word they know and a similar word in English (Carlo et al., 2004; García, 1991).Developing this type of academic language is necessary for English learners to be successful inscience classes.

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THE LANGUAGE OF SCIENCE

The language and literacy demands of science are acute for English learners: They must masterrigorous standards-based content, use and understand the language of science, and understandEnglish. Becoming proficient in the specialized language of science supports students’ success inthe both science activities and assessments (Moje, Collazo, Carrillo, & Marx, 2001). Aside fromthe array of vocabulary words (e.g., mitosis, photosynthesis), other terms for completing tasksand assignments are part of the language of science. Many of the language and literacy tasksthat students are expected to perform are often assumed to be part of their existing repertoire ofskills, when in actuality, these skills need to be taught and practiced (Echevarria & Short, 2010):for instance, asking students to classify or categorize concepts and vocabulary, form and writea hypothesis, and describe and sequence steps in a scientific process. All of these skills can bedeveloped with proper support but are extremely challenging for students who are learning newcontent in a new language.

One way of supporting language learning is to provide opportunities for students to inter-act with one another and discuss the lesson’s information, concepts, and vocabulary (August &Shanahan, 2006). Vocabulary knowledge in science expands when students have frequent oppor-tunities to encounter new words and are provided examples that are representative of the wordin rich contextual settings (August, Artzi, & Mazrum, 2010; Rupley & Slough, 2010). High-quality hands-on science activities are an ideal medium for students learning English (Lee et al.,2007). When working with, manipulating, and thinking about science material, it is often possi-ble for a student to understand concepts and terms, even without the vocabulary to express thelearning. Students will eventually learn language—the language of science and general academiclanguage—if they engage in meaningful, authentic activities that require them to use languagein ways that it is used naturally outside the classroom (Ellis, 2007). Acquisition of languageis also enhanced by having both content and language objectives for every lesson (Echevarria,Vogt, & Short, 2010a, 2010b). In this way, teachers focus on teaching standards-based content aswell as its associated language. Language objectives may highlight specific vocabulary but mayalso focus on more general language development, such as using past tense or turning questionsinto statements. For example, if the class is going to observe cells and document their obser-vations, the content objective might be, Students will pose a question to be investigated anddocument the findings. The language objective might be, Students will discuss observations andwrite conclusions using complete sentences.

SCIENCE TEACHERS AND ENGLISH LEARNERS

An increasing number of science teachers will teach English learners—and in greater numbers—as current demographic trends continue. While NCLB encourages schools to provide pro-fessional development in science, generally teachers are inadequately prepared in sciencedisciplines and classroom instruction (Penfield & Lee, 2010). Research frequently highlightsthe need for teachers to integrate a student’s linguistic and cultural background into theirlessons so that the scientific practices and vocabulary become more meaningful (Cuevas, Lee,Hart, & Deaktor, 2005). Ideally, all teachers would have an understanding of the issues thatimpact English learners such as second-language acquisition, effective teaching practices, and

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sociocultural factors such as cultural norms and values. One thing is certain, content teachersneed more preparation for working with English learners; they need to know and implementresearch-based practices that are most effective for these students. Lee (2005) suggests “Scienceinstruction typically has failed to help [ELs] learn science in ways that are meaningful and rele-vant to them, while also failing to help them develop proficiency in oral and written English”(p. 504). Instructional approaches that support language learning while teaching content arenecessary to reach English learners. One such model of instruction, the Sheltered InstructionObservation Protocol (SIOP) Model, has been shown to improve the achievement of Englishlearners across content areas and grade levels (Short, Echevarria, & Richards-Tutor, 2011).

The SIOP Model offers a framework for teachers to present content concepts to Englishlearners (e.g., science, social studies, and math) through strategies and techniques that makenew information comprehensible to the students. While doing so, teachers develop students’language skills across the four domains (reading, writing, listening, and speaking), whichhas been advocated by science education researchers (Cuevas et al., 2005; Lee, 2005; Lee,Maertren-Rivera, & Penfield, 2008). They may accomplish this in multiple ways suited to theparticular lesson (i.e., asking students to engage in peer discussions or a class debate, read text-book chapters or supplementary materials, complete a graphic organizer, or write in a sciencejournal).

The SIOP Model has eight components and 30 features that, taken together, have been shownto improve student achievement (Echevarria, Richards-Tutor, Chinn, & Ratleff, 2011; Echevarria,Short, & Powers, 2006; Honigsfeld & Cohan, 2008; McIntyre, Kyle, Muñoz, Chen, & Beldon,2010; Short, Fidelman, & Louguit, in press). The eight components include: Lesson Preparation,Building Background, Comprehensible Input, Strategies, Interaction, Practice & Application,Lesson Delivery, and Review &Assessment. The six features under Lesson Preparation exam-ine the lesson-planning process, including the incorporation of language and content objectives,the use of supplementary materials, and the meaningfulness of activities. Building Backgroundfocuses on making connections with students’ background experiences and prior learning anddeveloping their academic vocabulary. Comprehensible Input considers adjusting teacher speech,modeling academic tasks, and using multimodal techniques to enhance comprehension. TheStrategies component emphasizes explicit teaching of learning strategies to students so that theyknow how to access and retain information. It also stresses scaffolding instruction, and pro-moting higher-order thinking skills. The features of Interaction remind teachers to encourageelaborated speech and to group students appropriately for language and content development.Practice & Application calls for activities to extend language and content learning while LessonDelivery ensures teachers present a lesson that meets the planned objectives. As part of theReview & Assessment component, four items consider whether the teacher reviewed the key lan-guage and content concepts, assessed student learning, and provided feedback to students on theiroutput.

The SIOP Model is not a step-by-step approach. Rather it is a system for lesson planningand teaching that ensures research-supported combinations of features are present in every les-son. As a framework, it allows for some natural variation in teaching styles and lesson delivery,including inquiry lessons. However, as a tested model that improves student achievement, theSIOP’s features need to be practiced daily in a systematic way, not selectively and occasionally(Echevarria et al., 2006; Echevarria et al., 2011; Guarino et al., 2001).

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In the current study we extend the extant research on the SIOP Model to examine its effi-cacy in one content area, science. Science was selected because of its importance in the overallcurriculum and also because it is a subject that is included in NCLB testing.

PURPOSE AND RESEARCH QUESTIONS

The purpose of this study was to examine the impact of the SIOP Model, as delivered by class-room teachers, in middle school science classes. We sought to answer the question: What are theeffects of the SIOP Model on the acquisition of academic language and science concepts amongEnglish learners (ELs) in middle school science classrooms?

This study took place over 2 years. During Year 1, lesson plans and assessments weredeveloped and pilot tested. In Year 2, permission to participate was secured, and schools wererandomly assigned to treatment or control conditions. Each school in the study had one or twoseventh-grade science teachers, depending on the size of the school. Teachers were asked tovolunteer for participation in the study, and all agreed.

METHODS

Design

In this study, a small, cluster-randomized trial with randomization at the school level was usedto examine the impact of the SIOP Model. Ten middle schools in one large urban district inSouthern California were randomly assigned to either treatment (SIOP Model) or control (nor-mal classroom science instruction). However, before the onset of data collection, two schoolsin the control condition dropped out of the study so results must be interpreted as a quasiex-periment, with some caution. Moreover, because we did not apply a propensity score matchingprocedure prior to randomization, we were somewhat limited in our ability to describe the stateof equivalency of the remaining schools prior to the onset of the study, other than to examinecomparability of schools on the study-based pretest measures. These comparisons are presentedin the Results section.

Teachers in the SIOP condition received training in the SIOP Model and then taught fourscience units using lesson plans and teaching methods that followed the SIOP Model. Controlteachers taught the same four topics of study using methods that they would normally use toteach these topics. Students in both conditions were given a pretest at the beginning of eachscience unit and a posttest at the end to measure growth in acquisition of science language andscience content comprehension. Teachers typically gave a test at the end of each unit to assesscomprehension of content concepts.

Participants

Middle schools in one large urban district were categorized for selection for the study basedon the number of English learners at each school site. Schools with large (over 25% ELs)and moderate numbers (4–10% ELs) were included, and those with small numbers of English

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learners (less than 3% ELs) were excluded. The schools in each category (large and moderate)were randomly assigned to either treatment (SIOP Model) or control (normal classroom scienceinstruction), ensuring that there was an equal distribution of type of school population in eachcondition.

With the attrition of two schools in the control after randomization, there was a total of threeschools in the control group and five schools in the SIOP condition. The percent of Englishlearners at SIOP and control schools was similar: SIOP schools ranged from 4.9% to 27.2%English learners, and control schools ranged from 4.7% to 39.9% English learners. In all of theschools, seventh-grade science included one semester of Biology.

With the large and increasing number of English learners in schools, many mainstream teach-ers have a combination of native English speakers, English learners, and former English learnersin their classes. In order to examine the impact of the SIOP Model on each of these subgroups,the sample was divided into: English Learners (ELs), Fluent English Proficient (FEP) students(those who were once ELs but were redesignated), and native English speakers, referred to asEnglish Only (EO). The FEP students were divided into two groups, FEP three years or less andFEP over three years. There was significant representation of all subgroups in both treatment andcontrol schools, as seen in Table 1.

There were eight seventh-grade teachers in the treatment group and four in the control with atotal of 27 sections of science classes included in the SIOP condition and 15 sections in the controlcondition. Teaching experience of the 12 teachers ranged from over 15 years to less than 1 year(first-year teacher). All of the control teachers were fully certified in science. In the treatmentcondition, one teacher was in the process of completing her science certification, and one wascertified to teach health. Due to large numbers of English learners in the state, all teachers arerequired to have (or be working toward) an authorization to teach English learners in addition totheir content area certification. Theoretically, teachers with an EL authorization are better preparedto provide appropriate instruction to English learners. Six of the eight SIOP teachers and three ofthe four control teachers had completed their EL authorization at the time of the study.

Measures

Student Assessments

To be successful in science, English learners must learn general academic language, the aca-demic language of science, as well as science concepts (Merino & Scarcella, 2005; Short &

TABLE 1Sample Sizes for SIOP and Comparison Groups Designation by Language Level of Participants in Each of

the Treatment and Control Groups

Language Designation SIOP % Comparison %

English Learners 105 16.2 112 30.1Fluent English Proficient (3 years or less) 212 32.7 121 32.5Fluent English Proficient (More than 3 years) 89 13.7 20 8.1English Only 243 37.4 109 29.3Total 649 372

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Fitzsimmons, 2006). In the short duration of the study, it would not be expected that a signifi-cant amount of general academic language would be acquired; however, acquisition of specificvocabulary and concepts associated with each science unit was expected, as it was the intent ofthe study.

The student measure used was designed by project researchers who have an expertise in mea-surement to quantify acquisition of the concepts and language of science of each of four unitsof study. All science language and concept assessments were pilot tested the year prior to fullimplementation of the study (Year 1) and were modified based on results of the pilot test for Year2 implementation. An assessment was given before and after each of the four units taught duringthe course of the study. For each unit (Cell Division, Cell Structure and Function, Photosynthesisand Respiration, and Genetics), the assessment consisted of a reading passage on the sciencetopic to be tested, e.g., photosynthesis and respiration, followed by three to eight (average of3.5) multiple choice questions, three to eight (average of 3.5) short answer/fill in the blank ques-tions, and one to two essay questions. All of the information the students needed for answeringthe questions was in the reading passage on the assessment so that the assessment would measurestudents’ ability to understand the language and concepts they had been taught, not how muchthey retained from the lessons. That is, the assessment was designed to measure science contentcomprehension of the material in the passage as opposed to measuring retention of informationthat had been presented in the science instruction or accumulated knowledge in science. Thenonessay portions measured comprehension while the essay portion was designed to measurestudents’ use of science language in writing. A sample of questions from one assessment can befound in the Appendix.

Scoring for the objective portions of the unit assessments was done by graduate studentresearchers using an answer key. A point was given for each correct answer and no points for anincorrect response. As would be expected, the assessments with more multiple-choice and shortanswer/fill-in items had higher reliabilities than those with fewer items, with internal consistencyestimates for these nonessay components ranging from .462 to .786 for individual units.

The scoring of the essay components and the psychometric properties of the essay compo-nent are described below in the Procedures section. Because (a) the number of treatment unitswas small, (b) we did not have hypotheses about possible differential treatment effects by con-tent area, and (c) the individual unit tests were short, we combined tests from the differentinstructional units to create a single pretest and a single posttest reflecting performance across allinstructional units. Hereafter these tests are referred to as the combined pretest and the combinedposttest respectively. Internal consistency estimates of reliability were .894 for the combinedpretest and .915 for the combined posttest.

Lesson-Rating Instrument

The SIOP protocol was used to rate the science lessons on level of implementation. The fullinstrument is available from the authors by request. The protocol is a valid and reliable measure ofhigh-quality instruction for English learners (Guarino et al., 2001). SIOP teachers’ lessons wererated five times to measure growth in implementing SIOP lesson plans (facilitated by coaching)and because we were measuring their level of fidelity to the SIOP Model. Since control teach-ers designed their own lesson plans and were unfamiliar with the SIOP Model, no growth wasexpected, and their lessons were rated only once to get a “snapshot” of SIOP features used in

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their practice. It was expected that some features would be present in the control lessons sincethe SIOP Model reflects best practice for English learners, and the majority of control teacherswere certified in teaching English learners. The two observers who rated the lessons were famil-iar with the SIOP protocol and had used it previously. To ensure reliability, both observers and aresearcher rated videotaped lessons; interrater reliability was calculated at 87%.

Procedures

Development of the Instructional Units

During the pilot year of the study (Year 1), researchers developed two units of instructionthat were field-tested in two large urban districts by five teachers. During the summer followingthe field testing, researchers collaborated with science teachers using the results to modify anddevelop lesson plans for four instructional units: Cell Structure and Function, Photosynthesis andRespiration, Cell Division, and Genetics. The instructional units were aligned to state standardsin science, English language arts, and English-language development (ELD) and were designedusing the district’s adopted textbook and other curriculum materials.

Lesson plans varied in the activities that were used. However, there were several key elementspresent in all of the lesson plans: introduction of content and language objectives and key vocab-ulary, activities to practice all four language skills (i.e., listening, speaking, reading, and writing),frequent opportunities for student–student interaction, use of manipulatives and graphic organiz-ers, modeling of lesson tasks, and review of key vocabulary, content concepts, and the lesson’sobjectives at the end of every lesson.

Teacher Preparation

Since the purpose of the Year 2 study was to test the impact of the SIOP Model on studentachievement, treatment teachers did not receive any additional training in science content orscientific inquiry, only in the SIOP Model. They were provided an intensive two-and-a-half-daytraining to introduce them to the SIOP Model and its components. The training included a discus-sion on second-language acquisition and the type of teaching that makes content comprehensiblefor English learners followed by introduction of each of the SIOP Model’s eight components.Each component was presented in the same way: The component and its research backgroundwere introduced via PowerPoint presentation, participants watched a video that illustrated effec-tive classroom implementation of the component and its features, and participants were askedto rate the lesson using the protocol and justify their rating. This process led to a thorough dis-cussion of each feature. On the final day, each participant was presented with a binder of SIOPlesson plans for the four units of study, including descriptions of activities and hand outs, and theassessments for every instructional unit. Teachers were given time to review the binders and askclarifying questions. Each teacher was prepared to implement the SIOP lessons at the conclusionof the training.

Classroom Instruction

Treatment teachers delivered SIOP lessons created by the research team while control teach-ers taught the same units using the same textbook but used their own lesson plans and teaching

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methods. Each of the SIOP lesson plans included the following elements: state standard, lessontopic, content and language objectives, key vocabulary, motivation (background building), pre-sentation, practice and application, and review and assessment. A key feature of the SIOP Modellesson plans used in the study was the inclusion of both content and language objectives sincethe integration of English-language development across the curriculum is critical for improvingEnglish learners’ English proficiency (Echevarria & Short, 2010; Lee, 2005).

Coaching

To ensure that teachers’ delivery of the lesson plans followed the SIOP Model, coaching wasprovided to each treatment teacher by researchers who were experienced in implementing themodel. The process for coaching was: (a) the teacher and coach (researcher) reviewed the lessonplan together prior to the observation, (b) the coach observed and rated the lesson using the SIOPprotocol, and (c) a debriefing session followed when the teacher shared his or her reflectionwith the coach and the coach reviewed the rating and comments she had written on the SIOPprotocol. This collaborative process of observing lessons and providing teachers with feedbackwas conducted approximately every other week.

Administration of Assessments

Both treatment and control teachers were given a pacing guide for teaching the instructionalunits. This was done to ensure that students in each condition were receiving approximately thesame amount of instructional time on each unit. Before teaching a unit, the pretest was admin-istered to the students, and upon completion of the unit, students were administered the unit’sposttest. Researchers distributed and collected the assessments for each unit at both the treatmentand control sites.

Scoring of Essay Components of Assessments

The essay questions were scored by two graduate research assistants and one projectresearcher using the Illinois Measure of Annual Growth in English (IMAGE) writing rubric. Thiswriting rubric has high reliability for middle school populations (.91) and also has been shownto have high interrater reliability using both exact agreement and exact + adjacent agreement(Illinois State Board of Education, Assessment Division, 2004). The rubric scores students’ writ-ing along five dimensions: language production, focus, support/elaboration, organization, andmechanics. Each dimension is rated on a scale from 1 to 6, with the exception of Mechanics, afeature that is evaluated as either 1 (not developed) or 2 (developed). In all cases, higher num-bers indicate superior performance. Anchor points for the rating scales ranged, for example, forLanguage Production, from a score of 1 if the student wrote one- or two-word labels or wordlists to a score of 6 if the student used a variety of sentence lengths and structures.

All scorers had experience working with English learners; each had either been a teacher orhad worked in classrooms with English learners. We examined reliability across raters by using

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correlations as well as weighted kappa. When examining the essays for each of the four assess-ments individually, Pearson correlations between raters ranged from .48 to .66, while weightedkappa ranged from .34 to .52. When all essays were combined into a single composite score,correlations were estimated at .837 and .916 at the pretest and posttest respectively. Internalconsistency estimates of reliability for the essay components were high, ranging from .844 to.905 for the essay components for the four individual instructional units, and from .89 to .92 whenthe essay components were combined across the four instructional units. For the same reasonsthat the nonessay components were combined across instructional units to form a single com-bined pretest and a single combined posttest, we computed a total pretest essay score and a totalposttest essay score across the four science assessments. These combined essay component andnonessay component posttest scores were used to test the effects of the SIOP intervention usingthe corresponding pretest score as a covariate.

Analysis Model

To determine if the SIOP instruction affected students’ science language and concept develop-ment, multilevel analyses of covariance were used, with pretest scores serving as the covariate.In addition, we examined differences between SIOP and Control schools at the pretest usinga multilevel analysis of variance model. This analysis was undertaken to ensure comparabilityof the groups prior to the onset of instruction because the number of randomized schools wassmall and because two schools dropped from the control group prior to pretesting. Multilevelmodels were chosen for all analyses because students are nested within sections, sections arenested within teachers, and teachers within schools, with schools assigned to treatment and con-trol. Specifically, hierarchical linear modeling (HLM) was used. In all analyses, the dependentmeasures were the composite test scores created by aggregating scores from the four individualunit assessments. Scores for the essay and nonessay components were analyzed separately.

The multilevel model for pretests included random effects for school, section within teacher,and students within section. The multilevel model for posttests included random effects forschool, section within teacher, and students within section. Before testing hypotheses about dif-ferences between SIOP and control conditions, we estimated unconditional models to assess themagnitude of variance attributed to schools, sections within schools, and students within sections.Treatment group (i.e., SIOP vs. Control) was entered in the multilevel models at the school level.Effects of SIOP on posttest scores were estimated controlling for students’ pretest science scoresas well as their language level designation (ELL, FEP up to 3 years, FEP 3+, and EO), bothof which were entered into the multilevel models for posttests at the student level. The pretestcovariate was centered at the grand mean.

RESULTS

Impact of SIOP on Attainment of Concepts and Language of Science

Since there was differential attrition with two schools from the control groups withdrawing par-ticipation, results of these analyses must be interpreted with caution, particularly with regardto causality. The means and standard deviations for both the SIOP and control group from the

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TABLE 2Means and Standard Deviations for Nonessay Items at Pretest and Posttest

CONTROL SIOP

PRETEST POSTTEST PRETEST POSTTEST

Unit of Instruction Mean SD Mean SD Mean SD Mean SD

Cell Division 2.68 1.37 2.67 1.41 2.57 1.45 2.86 1.43Cell Structure 5.22 3.01 7.28 2.92 6.26 3.14 7.53 3.04Genetics 5.83 3.64 8.29 3.79 5.45 3.34 8.14 3.96Photosynthesis 3.08 1.64 3.79 1.67 3.24 1.76 4.08 1.69Combined 15.48 7.31 19.36 8.60 15.86 7.81 20.83 8.66

TABLE 3Means and Standard Deviations for Essay Items at Pretest and Posttest

CONTROL SIOP

PRETEST POSTTEST PRETEST POSTTEST

Unit of Instruction Mean SD Mean SD Mean SD Mean SD

Cell Division 12.22 3.20 12.83 3.67 12.99 3.14 13.87 3.87Cell Structure 18.31 8.50 24.63 7.93 22.02 9.34 26.56 9.62Genetics 19.16 7.19 24.88 8.44 18.21 7.52 26.91 9.06Photosynthesis 14.21 3.47 14.44 3.61 14.11 3.51 15.33 3.41Combined 41.77 20.89 56.41 24.62 43.78 24.72 61.21 27.86

four science language pre- and postassessments are provided in Tables 2 and 3 along with thecomposite scores. Table 2 displays the summary statistics for nonessay items. The total possiblepoints for the combined nonessay items was 35. Table 3 displays the same information for theessay items. The maximum total possible points for each essay was 26, and the combined totalpossible across the four assessments was 156 points. For both the essay and nonessay compositescores, the mean was higher in an absolute sense for the students in SIOP instruction than forstudents in typical instruction at both the pretest and posttest.

Results for the unconditional models for both pre- and posttests are presented in Table 4.We present results for the pretest in Tables 4 and 5 because of the breakdown in randomizationdue to the attrition of two schools from the control condition. Table 4 shows the variance com-ponents for the unconditional models, whereas Table 5 shows variance components and fixedeffects for differences between SIOP and control. The unconditional models presented in Table 4provide an initial examination of variance within and between groups, in this case schools andteachers. The unconditional HLM model showed that variance components for the essay com-ponent of the pre- and posttest were substantially larger than for the nonessay component. Forboth measures at both time points, variability due to sections within teacher and variability due to

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TABLE 4Estimates of Variance Components from Unconditional Models for Pretest1 and Posttest Scores from Essay

and Nonessay Science Assessments

Nonessay Essay

Random Effects Estimate χ2 p Estimate χ2 p

PRETEST Schools 6.5 7.5 .006 80.7 16.5 <.001Sections within Teacher 12.8 162.0 <.001 68.7 66.9 <.001Residual 39.4 394.5

POSTTEST Schools 16.3 17.9 <.001 139.6 22.3 <.001Sections within Teacher 13.3 142.7 <.001 79.9 58.3 <.001Residual 46.5 555.7

1We present estimates of the variance components for the pretest because of the breakdown in the study design due tothe attrition of two schools from the control group. Examination of the pretest is warranted given the quasiexperimentalnature of the design following the loss of schools.

schools was statistically significant. At the pretest, 11% of the variance in the nonessay compo-nent resided at the school level in comparison to 22% at the section level and 67% at the studentlevel. The essay component had a slightly higher percentage of variability at the school (14%)and student (72.5%) levels. At the posttest, more of the variability resided at the school level forboth the nonessay (21%) and essay (18%) components, with a somewhat smaller percentage atthe student and section levels. Most striking was the increase in overall variability at the posttest,especially in the essay component, where total variance increased 42.5% from 543.9 to 775.2 ascompared to 29.6% for the nonessay component.

Results for conditional models are presented in Table 5. The top half of Table 5 presentsresults for group differences at the pretest. The top half of Table 5 presents both random effects(i.e., variance components) and the associated chi-squared tests of significance, as well as testsof fixed effects (i.e., mean differences between SIOP and control) for the two pretests. Theseresults show that SIOP and comparison schools were minimally different from one another at thepretest time point. Differences between schools averaged 0.7 points on the nonessay componentof the pretest and 1.0 points on the essay component of the pretest. Both differences favored theSIOP schools, as was also indicated in the overall means in Table 2.

The bottom half of Table 5 presents results for the two posttests. Both random effects andfixed effects and the associated tests of significance are presented. In analyzing the posttest, weincluded the pretest measure as a student-level covariate to reduce residual variability and to con-trol for the minimal pretest advantage favoring the SIOP group. The fixed effects estimates in thebottom half of Table 5 indicated that posttest scores for students in SIOP schools did not differfrom those for students in control schools controlling for the pretest. There was an approximate0.9-point advantage for students in SIOP schools on the nonessay component of the posttest andapproximately a 5.5-point advantage on the essay component of the test. Neither of these differ-ences was statistically significant, although both were in the direction of favoring the studentsin the SIOP schools even after adjusting for the slight pretest advantage for the SIOP students.Results did not change substantially when student language subgroup was included as a secondstudent-level predictor in the model. Language subgroup status did not interact with treatmentgroup, indicating that the differences between SIOP and comparison were relatively consistent

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TABLE 5Conditional Model Results for Pretest1 and Posttest Scores from Essay and Nonessay Science Assessments

Nonessay Essay

Random Effects Estimate χ2 p Estimate χ2 p

PRETEST Schools 7.8 8.4 .003 95.5 17.5 <.001Sections within Teacher 12.9 162.1 <.001 69.0 67.1 <.001Residual 39.4 394.5

Fixed Effects Estimate s.e. p Estimate s.e. p

SIOP2 0.7 2.4 .759 1.0 7.9 0.9026

Nonessay Essay

Random Effects Estimate χ2 p Estimate χ2 p

POSTTEST Schools 7.1 20.1 <.001 77.9 25.3 <.001Sections within Teacher 3.6 46.4 <.001 24.3 23.5 <.001Residual 30.0 292.4Pretest Covariate3 0.7 0.03 <.0001 0.8 0.03 <.0001SIOP1 0.9 2.1 0.6725 5.5 6.8 0.4180

1We present results for group differences on the pretest because of the breakdown in the study design due to the attri-tion of two schools from the control group. Examination of group differences on the pretest is warranted given thequasiexperimental nature of the design following the loss of schools.2SIOP Effect is coded such that positive numbers indicate superior performance for schools in the SIOP condition.3The test for heterogeneous regression slopes was nonsignificant for both essay and nonessay outcomes.

TABLE 6Model-Based Estimates of Posttest Means for Four Language Subgroups in SIOP and Comparison Schools

Nonessay Component Essay Component

Treatment Group Language Group Estimate s.e. Estimate s.e.

SIOP English Learner 19.7 1.4 61.2 4.4FEP1 (<=3 yrs) 21.7 1.3 67.5 4.1FEP (> 3 yrs) 21.9 1.4 68.5 4.4English Only 20.6 1.3 62.2 4.2

Comparison English Learner 18.7 1.7 56.8 5.3FEP (<=3 yrs) 21.9 1.7 64.5 5.2FEP (> 3 yrs) 20.2 1.9 61.2 5.9English Only 19.8 1.7 56.8 5.3

1FEP indicates students redesignated as Fluent English Proficient with the number of years since the redesignationindicated in parentheses.

across the four subgroups of students. Nevertheless, Table 6 provides model-based estimates ofmeans on the essay and nonessay components of the posttest for students in SIOP and com-parison schools in each of the four language subgroups along with standard errors because ofpossible interest to readers designing future studies and meta-analysts.

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Although these results lacked statistical significance, it is important to consider estimates ofthe effect sizes in light of the relatively low power of the study, given the small number of schools(n = 8) and teachers (n = 12) involved. Effect size estimates were calculated using Hedges’ g(Hedges, 2007; What Works Clearinghouse, 2008) using the posttest estimates of the adjustedmean differences between SIOP and Control schools (see Table 5) and the posttest standarddeviations (see Tables 2 and 3). The results indicate that the effect of SIOP on the nonessaycomponent of the posttest was associated with g = .103 (i.e., 0.9 / 8.66), whereas the effect onthe essay component of the posttest yielded g = .197 (i.e., 5.5 / 27.86).

DISCUSSION

This study employed school-level randomization to test the efficacy of the SIOP Model for pro-viding instruction in classrooms with significant proportions of English learners and formerEnglish learners, as well as English Only students. As stated previously, due to the fact thatthere was differential attrition in the control group, results of this study should be interpretedcautiously, particularly with respect to causality.

The study showed that there was significant variability in student performance across allaspects of the study. Not surprisingly, students differed from one another based on their status asEnglish learners, with those students still limited in their English proficiency performing mostpoorly, while students who had been redesignated as fluent English proficient scored slightlybetter than English Only students, albeit not significantly so. The study did not find statisticallysignificant differences between the posttest performance of students instructed through the SIOPModel and those instructed in comparison schools. Although groups did not differ appreciablyfrom one another at the pre- and posttest and differences on both essay and nonessay componentsfavored the SIOP group, these differences were not statistically significant. However, effect sizesranged from .103 to .197 for the nonessay and essay components of the posttest respectively.

There are several reasons that may explain why the overall differences between the SIOP andcontrol groups were not stronger. First, at the research design level, we were limited in that weonly had eight schools and 12 teachers willing to participate in the study. Initially, we intended tohave a larger number of schools involved in the study, but the realities of school-based researchpresented a number of obstacles, including lack of districts willing to participate, perhaps becauseof the demands of increased accountability.

Also, the concentration of English learners at certain schools precluded random assignment oflarge numbers of schools (some schools had insignificant numbers of ELs). Therefore, althoughwe had 27 sections of SIOP instruction, 15 sections in the control, and over 1,000 students inthe study, power was limited due to the limited number of schools and teachers. Ideally, thestudy would have involved a larger number of schools, more teachers, and a more balancedrepresentation of sections within teachers.

Another challenge was that extensive SIOP training was not possible because of districtscheduling constraints, i.e., Biology was only 1 semester long, and SIOP training took placejust prior to the beginning of data collection. Ideally, learning and implementing the SIOP Modelwith coaching and other supports would have taken place over several months prior to mea-suring student performance. Changing teacher practice requires significant time and on-goingsupport (Darling-Hammond & Richardson, 2009; Saunders, Goldenberg, & Gallimore, 2009;

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Quint, 2011), and both would be necessary for most teachers to reach a level of comfort thatallows the practices reflected in the SIOP Model to become routine and automatic. Additionally,the intervention in this study was only 8 weeks long. This is a very short period of time in whichto expect teachers to develop a strong working knowledge of the SIOP Model, and an equallyshort time for a change in instruction to significantly impact the achievement of middle schoolstudents.

In fact, given the short duration of the professional development and the intervention perioditself, the effect sizes give some room for optimism. It is quite possible that given more exposureto high-quality SIOP science instruction, the students would have performed better. In otherresearch, improvement in students’ achievement has been shown to increase significantly inproportion to the number of years they participated in a science program that had many of thefeatures of the SIOP Model (Amaral, Garrison, & Klentschy, 2002).

Finally, and perhaps most importantly, the level of SIOP Model implementation was not opti-mal. With random assignment, teachers are “assigned” to an intervention they are expected tolearn and use with fidelity. The level of cooperation, interest in the study, and level of SIOPimplementation varied across the SIOP teachers. Some were enthusiastic about the interven-tion and were interested in research while others merely met their obligation to participate.One expects such variability in treatment uptake among practitioners. However, in small stud-ies such as this one, such variability works to further reduce power and undermine treatmentimpact.

In this study, when teacher implementation was high, student achievement rose somewhat dra-matically (Echevarria et al., 2011). The finding of improved achievement with improved teacherimplementation supports the inference that the posttest scores were not significantly differentbetween SIOP and comparison schools because there was no sufficient distinction between theSIOP teachers’ instruction overall and that of the control teachers. This result is descriptive andcorrelational in nature (Echevarria et al., 2011) and therefore does not replace the direct contrastbetween SIOP and comparison conditions that had been assigned at random. However, theseimplementation results are at least promising, as are the estimates of effect sizes.

In working with English learners, educators often question the advisability of teaching classesthat consist of a mix of English Only (EO) students and those who are not yet fully proficientin English. An examination of the language subgroups (EL, FEP, and EO) showed that teachingwith the SIOP Model was appropriate for all students. That is, there was no evidence to suggestthat students who were English Only students were negatively impacted by having a teacherwho was delivering SIOP-based instruction. In fact, there was no evidence that SIOP interactedwith student language status, in either a positive or negative way. This finding is important inaddressing the issue of mixed proficiency levels in the same class. The performance of all studentgroups improved on average, which shows that although initially designed for English learners,the SIOP Model can benefit EO students as well.

In conclusion, there needs to be further research on the SIOP Model with a focus on moreintensive professional development to increase fidelity to the model. Whether additional time inthe model would have benefitted the teachers and their students in the present study remains amatter of speculation but seems likely given the complexity of changing teacher practice and therelatively brief exposure to the model that was afforded teachers and students. Although showingmodest growth, student performance was better for students in the SIOP group, particularly whenteachers implemented the features to a high degree.

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Echevarria, J., Vogt, M. E., & Short, D. (2010a). Making content comprehensible to elementary English learners: TheSIOP model. Boston, MA: Pearson/Allyn & Bacon.

Echevarria, J., Vogt, M. E., & Short, D. (2010b). Making content comprehensible to secondary English learners: TheSIOP model. Boston, MA: Pearson/Allyn & Bacon.

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Hedges, L. V. (2007). Effect size estimation in cluster-randomized trials. Journal of Educational and BehavioralStatistics, 32, 341–370.

Honigsfeld, A., & Cohan, A. (2008). The power of two: Lesson study and SIOP help teachers instruct ELLs. Journal ofStaff Development, 29(1), 24–28.

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APPENDIX: SIOP SCIENCE CELL DIVISION LANGUAGEASSESSMENT POSTTEST

After reading a passage with information on cells and cell division, including illustrations,students were given the following assessment:

Answer the following questions:

I. Which statement describes mitosis? Circle the best answer.1. A cell’s cytoplasm divides itself and produces two new cytoplasms.2. A cell’s nucleus divides itself and produces two new nuclei.3. Organelles divide themselves and produce new organelles.4. The cell grows to its mature size.

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II. Complete each sentence with one of the words in the list. Each word can be used only once.

DNA mutation mitosis cytokinesisinterphase chromatin organelles chromosomescell cycle cancer cytoplasm tumor

1. ________________________ is the soup-like substance that surrounds the nucleus.2. During ______________________, organelles divide themselves into two sets of

organelles.3. The mass that is formed by abnormal cells in cancer is called a/an

________________________.4. The chromatids detach and move to the two ends of the cell in this stage of the cell

cycle: ________________________.III. In October 2005, a farmer from Pennsylvania grew a 1,469-pound pumpkin from a very

small seed in 6 months. Use the information you read about the cell cycle to explain howthis could happen. Write as much as you can. Use scientific terms.

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