The effects of educative curriculum materials on teachers’ Use of instructional strategies for English language learners in science and on student learning

Contemporary Educational Psychology xxx (2014) xxx–xxx

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Contemporary Educational Psychology

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The effects of educative curriculum materials on teachers’Use of instructional strategies for English language learnersin science and on student learning

http://dx.doi.org/10.1016/j.cedpsych.2014.10.0050361-476X/� 2014 Published by Elsevier Inc.

⇑ Corresponding author.E-mail addresses: [email protected] (G.N. Cervetti), [email protected] (J.M.

Kulikowich).

Please cite this article in press as: Cervetti, G. N., et al. The effects of educative curriculum materials on teachers’ Use of instructional strategies forlanguage learners in science and on student learning. Contemporary Educational Psychology (2014), http://dx.doi.org/10.1016/j.cedpsych.2014.10.0

Gina N. Cervetti a,⇑, Jonna M. Kulikowich b, Marco A. Bravo c

a University of Michigan, School of Education, Room 4039, Ann Arbor, MI 48109, United States of Americab The Pennsylvania State University, College of Education, 101 Cedar Building, University Park, PA 16802, United States of Americac Santa Clara University, School of Education and Counseling Psychology, Loyola Hall, Room 120 L, 500 El Camino Real, Santa Clara, CA 95053, United States of America

a r t i c l e i n f o

Article history:Available online xxxx

Keywords:Educative curriculum materialsTeacher learningScience instructionEnglish language learnersInstructional strategies

a b s t r a c t

This experimental study tests the extent to which specially-designed curriculum materials supportedteachers in using instructional strategies for English Language Learners (ELLs) as they implemented aninnovative science curriculum for fourth and fifth grade students. Specifically, we examine the impactof a set of educative features—optional notes to the teacher suggesting strategies for use with ELLs—onteachers’ (n = 15) use of strategies as they enacted the curriculum, on teachers’ ELL pedagogical knowl-edge, and on ELL’s science and vocabulary learning. Comparison teachers taught the same 40-sessionspace science curriculum, but they did not have access to the educative features. We used observationsto monitor fidelity to the main curriculum, and to document teachers’ use of instructional strategies withELLs. Treatment teachers who had access to the features used more strategies to support ELLs in theirclassrooms, used a wider range of strategies and acquired more new strategies than did comparisonteachers. While no differences were detected on student (n = 358) science and vocabulary learningbetween treatment and comparison groups, correlation analysis illustrated close association betweenteacher strategy use and ELL’s learning. The results suggest potential for teacher learning from educativefeatures and positive impact on ELL’s learning.

� 2014 Published by Elsevier Inc.

1. Introduction

English Language Learners (ELLs) represent the fastest growingsector of the school age population (Gándara & Hopkins, 2010). Instates like California, one in four students is designated as an Eng-lish Language Learner (California Department of Education (CDE).,2014). This population growth is now being felt in states not accus-tomed to serving ELLs. Nebraska for example experienced a 301%increase in the ELL population between 1996 and 2006 (Batalova,Fix, & Murray, 2006). With such unprecedented and projectedgrowth, all teachers will likely have ELLs in their classroom andwill require support in addressing the needs of this population.

Although the number of English language learners (ELLs) in USclassrooms is rising rapidly, there is substantial evidence thatmany elementary teachers feel inadequately prepared to workeffectively with language learners, particularly in content areas

(Gandara, Maxwell-Jolly, & Driscoll, 2005; Lee, Maerten-Rivera,Penfield, LeRoy, & Secada, 2009). This is not surprising given thatvery little ELL professional development is offered to teachers.The National Clearinghouse on English Language Acquisition2008 report found that only about a quarter of teachers with ELLsin their classrooms receive professional development to assist thispopulation. The challenge in teaching an increasingly linguisticallydiverse population of students is particularly significant in sci-ence—both because science instruction often involves the intro-duction of scores of unfamiliar new words (Armstrong & Collier,1990) and also because few elementary teachers feel generallywell-prepared to teach science (Fulp, 2002; Weiss, Banilower,McMahon, & Smith, 2001). In the 2000 Horizon Research NationalSurvey of Science and Mathematics Education, only 4% of respon-dents had undergraduate degrees in science or science educationand 40% percent reported having taken four or fewer college-levelscience courses (Fulp, 2002; Weiss et al., 2001). Given the low lev-els of preparation and confidence in teaching science and teachinglinguistically diverse students, perhaps it is not surprising thatstudies of otherwise effective science instruction have often failed

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2 G.N. Cervetti et al. / Contemporary Educational Psychology xxx (2014) xxx–xxx

to show effects for ELLs (e.g., Lynch, Kuipers, Pyke, & Szesze, 2005).If this is to change, teachers will need many opportunities and sup-ports to improve their abilities to work effectively with ELLs.

The goal of this study was to test the potential for speciallydesigned curriculum materials—what we call educative curriculummaterials, following Davis and Krajcik (2005)—to support teachersin adapting science instruction to scaffold their ELLs’ learning. Theeducative materials offered treatment teachers a set of research-based strategies for uses with their ELLs, along with rationaleslinked both to the enactment of the particular lesson being taughtand to principles of language development. We also examinedwhether the instructional strategies described in the materialsbecame part of teachers’ pedagogical repertoires for teaching ELLs.

1.1. Instructional strategies for English language learners

A common instructional model employed to support the con-tent learning needs of ELLs immerses students in regular con-tent-area instruction while accompanying scaffolds are used toamplify the curriculum to facilitate learning (Walqui, 2006). Thismodel, commonly referred to as Sheltered Instruction, presents ELLswith the same instruction their native English-speaking peersreceive, only with instructional strategies that make the contentmore accessible. While several programs have evolved from Shel-tered Instruction (e.g., Cognitive Academic Language LearningApproach [CALLA], Chamot & O’Malley, 1996; Sheltered InstructionObservation Protocol [SIOP]; Echevarria, Vogt, & Short, 2008; Spe-cially Designed Academic Instruction in English [SDAIE], Peregoy &Boyle, 2008), most share a common pedagogical approach sup-ported by second language acquisition research.

Many of the scaffolds that have been developed as part of Shel-tered Instruction are concerned with mitigating the frustration andcognitive challenge of layering the linguistic complexity of scienceinstruction on top of challenging and abstract science concepts.With both a cognitive and linguistic load with which to contend,it is argued that by making abstract concepts more concrete, con-tent area learning is facilitated for ELLs (Wong-Fillmore, 2007).This is critical, given content areas such as science are replete withabstract concepts. To make these concepts more comprehensiblefor ELLs pedagogical considerations are suggested that includethe use of such tools as images and videos instead of just text ortalk (Lee, 2005), involving manipulatives and realia with academicvocabulary (August, Branum-Martin, Cardenas-Hagan, & Francis,2009), as well as involving more kinesthetic activity (Lara-Alecioet al., 2012) to make for more enduring understandings. Whilesuch instructional strategies are also considered beneficial for allstudents, they are critical for ELLs. Without these scaffolds, nativeEnglish speaking students may still gain access to the contentthrough hearing or asking questions about the content. Suchopportunities are limited for students who do not speak the lan-guage fluently (Gibbons, 2003).

Attention to ‘comprehensible input’ (Krashen, 2002) is also aconcern when preparing instruction for ELLs. Comprehensibleinput refers to the efforts put forth to make language understand-able to students. Typical language blind spots that require instruc-tional attention include figurative language such as idiomaticexpressions and hyperbole (Cooper, 1999). An obstacle in scienceis the presence of dual meaning words, many of which have every-day meanings and more technical meanings in content areas (e.g.,volume, formula, expression) (Bravo & Cervetti, 2008).

The manner in which language is spoken to ELLs also requiresconsideration. How much time teachers wait for a student torespond to questions, rate of speech, and enunciation all play a rolein ELLs’ understanding of classroom processes, content and lan-guage learning goals (Echevarria et al., 2008).

Please cite this article in press as: Cervetti, G. N., et al. The effects of educative clanguage learners in science and on student learning. Contemporary Educationa

A third identified instructional support that has shown positiveacademic achievement for ELLs is consideration of their native lan-guage as a linguistic resource (Cuevas, Lee, Hart, & Deaktor, 2005;Fradd, Lee, Sutman, & Saxton, 2002; Moschkovich, 2010). Forexample, explaining instructions for activities in the students’native language (Lee & Fradd, 1996), calling attention to cognatesto uncover meanings of unfamiliar vocabulary (Carlo et al., 2004),and inviting ELLs to use their native language to discuss topics witha bilingual classmate (Echevarria et al., 2008), have proven to facil-itate content area learning. Such instructional support has not onlya cognitive benefit, but also an affective one as well (Krashen,2002). Acknowledging and validating ELLs’ native language createsa more conducive language and content learning environment, asELLs feel safer to practice their English skills, and by consequence,improve their understanding of content.

Leveraging ELLs’ native language in content area learning, mak-ing the language of content more comprehensible, and addressingthe cognitive load involved in content area learning have beentested and found to be effective when teachers build efficacy andknowledge in delivering instruction with these modifications(Echevarria, Richards-Tutor, Chinn, & Ratleff, 2011; Lara-Alecioet al., 2012; Lee, Maerten-Rivera, Penfield, LeRoy, & Secada,,2008; Short, Fidelman, & Louguit, 2012). For example, Echevarriaet al. (2011), found ELL achievement outcomes on measures of lan-guage and science learning were strongly correlated to fidelity tothe SIOP model. The researchers argued that some teachersrequired more sustained engagement with the pedagogical consid-erations, suggesting difference between high-implementing andlow-implementing teachers was an issue of degree rather thantype of scaffolds enacted to support ELLs.

The current study tests the potential of curriculum materials tosupport teachers’ work with ELLs in science by offering teacherssuggestions about the strategies mentioned in the introductorysections that they might use with the ELLs in their classrooms tomake the curriculum more supportive of their learning. In describ-ing the instructional strategies and rationales for the use of thestrategies, we expected that the materials would support teachersin enacting and acquiring new strategies and that they would inturn support ELL students’ science learning. Further, we hypothe-sized that enacting strategies with ELLs would be associated withELLs’ science learning to a greater degree for the treatment groupthan for the comparison group.

1.2. Educative curriculum materials for enactment support andteacher learning

Educative curriculum materials are designed to both supportteachers’ enactment of particular curricula and to support teachers’learning about instruction as they use the materials (Davis &Krajcik, 2005). Like traditional forms of professional development,educative curriculum materials aim to improve the quality ofinstruction in classrooms by supporting teachers’ enactment ofinstructional materials and to support teacher learning. Unlike pro-fessional development, educative curriculum materials do notinvolve face-to-face interaction among teachers or between teach-ers and professional developers. Instead, the curriculum materialsinclude material designed to support curriculum enactment andteacher learning. Educative curriculum materials support enact-ment by providing information that helps teachers understandthe instructional choices of the developers, solve problems ofimplementation as they teach, and modify instruction to meetthe needs of their contexts and students (Schneider, Krajcik, &Marx, 2000). As Beyer, Delgado, Davis, and Krajcik (2009) note, tra-ditional curriculum materials aim only at student learning andassume that teachers will closely follow the activities as describedin order to ‘‘deliver’’ instruction (p. 979). As such, rationales for

urriculum materials on teachers’ Use of instructional strategies for Englishl Psychology (2014), http://dx.doi.org/10.1016/j.cedpsych.2014.10.005


G.N. Cervetti et al. / Contemporary Educational Psychology xxx (2014) xxx–xxx 3

instructional choices and options for modification are largelyabsent. In contrast, educative materials ‘‘speak to teachers, notmerely through them’’ (Remillard, 2000, p. 347). In doing so, edu-cative curriculum materials aim to provide implementation sup-port while offering teachers a meaningful role in the design ofthe instruction (Remillard, 2000). Davis and Krajcik suggest thatone of the roles of educative curriculum materials is to ‘‘promotea teacher’s pedagogical design capacity’’—the ability to use supportsembedded in curriculum materials to adapt the materials (p. 5,emphasis in original).

Educative curriculum materials also aim to support teacherlearning. Researchers have suggested that, because curriculummaterials are part of teachers’ everyday practice of planning les-sons and assessing student learning, they are well positioned toprovide support for the acquisition of knowledge about contentand about pedagogy that might become part of a teacher’s knowl-edge base and pedagogical repertoire (Ball & Cohen, 1996;Collopy, 2003; Davis & Krajcik, 2005; Remillard, 2000). In empha-sizing the products of teaching, traditional curriculum materialsdiscourage teachers from considering the descriptions of instruc-tion as pedagogical ideas and strategies that might be useful inother instructional contexts or delivered in a unique way thattakes into account contextual factors. In contrast, educative cur-riculum materials offer teachers support for their learning aboutteaching by illustrating and explaining the instruction describedin the guides, particularly through narrative descriptions ofenactments and through explanations of the how and why theinstructional suggestions offered in the teacher’s guides aredesigned to support student learning. In providing instructionalsuggestions that are tied to the enactment of specific lessons,educative curriculum materials are aligned with an importanttenet of high quality professional learning opportunities. Specifi-cally, researchers of teacher learning commonly suggest thatthe most useful knowledge is integrally situated at the intersec-tion with application so teachers can see how new ideas can beapplied in their day-to-day practice (Borko & Putnam, 1996;Penuel, Fishman, Yamaguchi, & Gallagher, 2007; Remillard,2000; Webster-Wright, 2009). In addition, teachers report thatthey most value the kinds of professional learning opportunitiesthat offer procedural knowledge that is immediately applicableto their classroom practice (Scribner, 1999).

Researchers have started to formulate design characteristics ofeducative curriculum materials (Ball & Cohen, 1996; Collopy,2003; Davis & Krajcik, 2005; Remillard, 2000). Most educative cur-riculum materials embed notes to teachers in specific lessons in ateacher’s guide. These notes might provide narrative descriptionsof how other teachers enacted a particular piece of the lesson,descriptions of the rationale behind particular practices, tips forinstruction, opportunities for differentiation, or background infor-mation about concepts under study. For example, Schneider et al.(2000) developed educative materials that included descriptionsof each unit and each lesson that explained how and why the les-sons were sequences to connect and develop students’ ideas andskills, including how concepts in a particular lesson would be builtupon later in the unit. They also included background informationto support teachers’ content knowledge and notes related to vari-ous forms of pedagogical content knowledge, such as how andwhy to use specific strategies offered in the guide. The featureswere designed to support high quality implementation of the base-line instruction and to augment teachers’ knowledge about thecontent and pedagogical content knowledge for science teaching.Bodzin, Peffer, and Kulo (2012) developed a set of educative curric-ulum materials for middle school science that included bothinstructional guidance for baseline implementation, such as mate-rials designed to support teachers’ content knowledge, and alsosuggestions for adapting learning activities for different learners.


Several studies have examined the potential of educative curric-ulum materials to support teacher learning and the nature of tea-cher learning through educative curriculum materials (Beyer &Davis, 2009; Collopy, 2003; Schneider et al., 2000). Each studyfocused on mathematics or science teachers using curriculum witheducative elements, such as background information about con-tent, the rationale for the sequence of instruction, or sample dia-logues of classroom discussions. They found that teachers tendedto use educative features addressing pedagogical content knowl-edge and lesson-specific ideas more readily than features address-ing knowledge about content and pedagogy (Schneider et al.,2000). Collopy (2003) studied two teachers’ use of a set of educa-tive curriculum materials designed to support teachers’ learningabout the curriculum’s approach to mathematics instruction,which emphasized discussion of mathematical ideas and theinvention of problem-solving strategies. As in the current study,many of the educative features took the form of embedded notesto the teacher but, unlike the current study, the features weredesigned to support teachers’ implementation of the baseline cur-riculum, rather than modifications. Collopy observed changes inthe instructional practice of one of the two teacher participants.For example, Collopy found that this teacher shifted her instruc-tional focus away from the steps students needed to use in orderto provide correct answers and toward mathematical reasoning.

While these studies suggest that educative curriculum materi-als can deepen understanding of content and produce dramaticchanges in some teachers’ attitudes and approaches to instruction,they also found that curriculum materials do not always supportteacher learning. Some teachers either do not attend to the educa-tive elements or do not change their practices despite reading theeducative curriculum materials carefully (Collopy, 2003). Individ-ual teacher differences (e.g., linguistic insider, science background)can mitigate teacher learning (Echevarria et al., 2011).

The current study adds to the literature on educative curricu-lum materials in two important ways. First, this study is uniquein that it examines the impact of educative curriculum featuresthat offer optional instructional strategies that can be used to mod-ify instruction to meet the needs of particular students—thosewhose first language is not English. Although the instructionalmaterials included educative features that function in many ofthe roles described in other research on educative materials, thefocus of this study is not on the features designed to support teach-ers in enacting the core of the curriculum unit, but on the featuresdesigned to support teachers in the strategic use of instructionalmodifications. Several other researchers have developed educativecurriculum materials with supports for adaptations of curricula,but, to our knowledge, none have included strategies specificallydesigned to support ELLs and none have examined the efficacy ofthe educative features offering adaptation support (Bodzin et al.,2012; Duncan, El-Moslimany, McDonnell, & Lichtenwalner, 2011;Lin, Lieu, Chen, Huang, & Chang, 2012).

In addition, unlike much of the existing research on educativecurriculum materials, we examined student learning as an out-come of teachers’ use of educative curriculum materials. One otherstudy has looked at student learning: Lin et al. (2012) developed aset of educative curriculum materials focused on supporting teach-ers in teaching the nature of science (NOS). The teacher’s guideincluded rationales to explain the pedagogical approaches usedto support students’ nature of science understandings and guid-ance for implementation, including alternative questions andactivities that teachers might use during implementation. All 10participants taught the experimental curriculum. The researchersdocumented changes in beliefs about their pedagogical contentknowledge for the nature of science. The researchers found thatthe four teachers who had less background in NOS (i.e., less course-work) had similar student outcomes and similar levels of teaching



Table 1Teacher characteristics in treatment and comparison groups.

Treatment Comparison

Mean total years teaching 9.5 12.3Percent ELL in class 36.25% 45.35%Percent of ELL who were first

language Spanish speakers84% 82%

Course work and professionaldevelopment related to ELL

None:1 None:2

Some PD orcoursework: 3

Some PD orcoursework: 4

Certificate: 2 Certificate: 2Degree: 0 Degree: 1

Languages spoken English or Englishand Other: 4

English or Englishand Other: 6

Basic Spanish: 1 Basic Spanish: 3Proficient orFluent Spanish: 1

Proficient orFluent Spanish: 0

Location California: 4 California: 6Colorado: 1 Colorado: 2Oregon: 1 Oregon: 1

Table 2Sample size information for treatment and comparison classrooms.

Classroom ELLs Non-ELLsn (%) n (%)

Treatment1 4 (17.40) 19 (82.60)2 16 (55.17) 13 (44.83)3 5 (26.32) 14 (73.68)4 11 (44.00) 14 (56.00)5 11 (52.38) 10 (47.62)6 6 (22.22) 21 (77.78)

Comparison7 12 (46.15) 14 (53.85)8 9 (56.25) 7 (43.75)9 27 (93.10) 2 (6.90)10 5 (18.52) 22 (81.48)11 4 (12.50) 28 (87.50)12 15 (75.00) 5 (25.00)13 5 (17.86) 23 (82.14)14 14 (70.00) 6 (30.00)15 3 (18.75) 13 (81.25)


performance as teachers who had more NOS experience at the out-set of the study. The current study provides a more rigorous test ofstudent learning by using an experimental design.

1.3. Research questions and hypotheses

Fifteen teachers taught a 40-session space science unit twiceacross two academic years. The six treatment teachers had accessto a set of embedded educative curriculum features (ECF’s), includ-ing notes describing strategies that they could use with ELLs intheir classrooms. The nine comparison teachers taught an identicalunit without the presence of ECF’s. Our examination focuses on thefollowing research questions and hypotheses.

1. Will the presence of the ELL-focused educative notes increasethe quantity and range of the instructional strategies thatteachers use in order to support their ELLs in science? Wehypothesized that treatment teachers who had access to theeducative notes would use more ELL-focused instructionalstrategies than comparison teachers and that they would usea wider range of different ELL-focused instructional strategiesthan comparison group teachers.

2. Will teachers who have access to the ELL-focused educativenotes add new instructional strategies to their pedagogical rep-ertoires for supporting ELLs in science? We hypothesized thattreatment teachers who had access to the educative noteswould add to their repertoires of ELL-focused instructionalstrategies at a higher rate than teachers in the comparisongroup.

3. Is teachers’ use of instructional strategies with ELLs more clo-sely associated with student learning in classrooms whereteachers had access to the ELL-focused educative notes?Although we hypothesize that treatment teachers would usemore ELL-focused instructional strategies, the use of more anda wider range of strategies is not necessarily beneficial in andof itself. We hypothesized that the ELL-focused instructionalmoves used by treatment teachers would be related to ELLs’learning to a greater degree than ELLs’ learning in the compar-ison group. Specifically, we anticipated that the use of ELL-focused instructional strategies in the treatment group wouldbe associated with greater gains in science learning for ELLsthan for the comparison classrooms. We also examined theeffects of treatment condition on students’ pre-post vocabularyknowledge in science.

2. Methods

2.1. Participants and settings

2.1.1. TeachersThe participants in this study were 15 fourth and fifth grade

teachers from three Western states from districts serving a highpercentage of ELL. Participation requirements included teaching aself-contained classroom with at least 20% ELLs and agreeing toteach the treatment unit once each year for up to two years. Notall teachers had 20% ELLs during the year that is the focus of thisreport.

The 15 participants in this study are part of a larger, multi-com-ponent research project. They are drawn from a larger pool ofteachers who participated in the research project during the2009–2010 school year, all of whom had been randomly assignedto the treatment or comparison conditions. The 15 teachersincluded in this study were asked to teach their units a second timeduring the 2010–2011 year because they had relatively high levelsof completion in the first year. We reasoned that we would learnmore about the impact of the curriculum materials from teachers


who actually taught the materials. We initially invited 10 treat-ment teachers and 10 comparison teachers to continue. Severalteachers were unable to participate for a variety of reasons, includ-ing layoffs, retirement, reassignment to different grade levels, andlooping with the same classroom of students. Six of the 10 treat-ment teachers and one of the 10 comparison teachers declinedthe invitation to continue with the project in Study Year 2. Weextended invitations to additional Study Year 1 teachers who hadhigh levels of unit implementation in Study Year 1. The final distri-bution of teachers for Study Year 2 was six treatment teachers andnine comparison teachers (see Table 1).

2.1.2. StudentsPre-post vocabulary and science knowledge scores for the 358

students who participated in the second year of data collectionwere analyzed. One hundred forty-four students represented treat-ment classrooms; 214 comparison. Additionally, 147 were ELLsand 211 were Non-ELLs. Table 2 presents a summary of informa-tion for classrooms and students. Fifty-three ELLs were enrolledin treatment classrooms compared to 94 ELLs who were enrolledin the comparison classrooms. The primary data analysis for thisinvestigation focuses on the scores for science learning of the147 ELLs.




2.2. Instructional materials

We examined teacher and student learning across two condi-tions. Teachers in the treatment condition used an integrated sci-ence-literacy curriculum unit that included a step-by-step guidefor 40 sessions of space science instruction with educative notesproviding science background information, instructional sugges-tions, instructional rationales, and the strategies for ELLs that arethe focus of this study. Teachers in the comparison group receivedthe same step-by-step guide, but with support material limited toa suggested writing activity per lesson and occasional signaling ofassessment opportunities. All teachers received the instructionalunit, including a teacher’s guide, student books, student sciencenotebooks, and a kit of materials for use in firsthand investigations.The only difference between the materials provided to treatmentand comparison teachers was the presence or absence of educativenotes in the teacher’s guide.

The ECF’s for ELLs were developed based on an extensive reviewof the literature on second language acquisition and approachesshown to advance student learning (e.g., Carlo et al., 2004;Echevarria et al., 2008; Jimenez, Garcia, & Pearson, 1996;Krashen, 2002; Lee, Deaktor, Hart, Cuevas, & Enders, 2005). Forexample, one strategy infused across the treatment curriculumaddressed how to use cognates to assist Spanish-speaking ELLs inaccessing unfamiliar English words. A second strategy describedin several ECF’s encouraged teachers to provide opportunities forstudents to write or talk in their first languages or in a first lan-guage-English hybrid in order to focus the students on makingsense of the science ideas rather than the conventions of writtenor spoken English. A third set of ECF’s provided additional supportfor reading strategies such as comprehension monitoring. Exam-ples of two strategies as they appeared in the treatment teacher’sguide are included in Fig. 1. The ECF’s also included a number ofexplanations about ways to overcome potential linguistic chal-lenges for ELLs in science, including explaining idiomatic expres-sions, attending to potentially confusing dual meaning words(e.g., model, claim), being sensitive to language fatigue, and allow-ing more opportunities to rehearse with a language partner beforediscussing in a whole class setting. Specific strategies were contex-tualized as practical applications of broader lessons from research,

Cognate Strategy. Many words in science are Eng

spelling and meaning in the two languages. In fact,

are everyday words in Spanish (sol/luna). Pointing

speakers (and other English language learners with

the reading comprehension of the [title removed] b

cognates are, then provide some examples of comm

students to provide some as well. Finally, have stud

they read the text and to list as many as they can. T

word they don’t know when they read, they should

cognates in the book follows.]

Language Buddies. Accessing student’s native lan

understand important science content. Establish pa

language and encourage them to use their native la

Fig. 1. Examples of Strategies for ELL incl


understandings about language and culture, and understandingsabout the linguistic demands of science. (See Cervetti, Bravo,Duong, Hernandez, & Tilson, 2008, for a review of the literatureand description of many of the strategies for ELLs included in thetreatment unit). It is important to note that the strategies weredesigned to help teachers both capitalize on the unique linguisticresources that ELLs bring to the study of science, and also to miti-gate the linguistic demands that ELLs may encounter in science.Two to three ECF’s for ELLs were strategically placed in each lessonbased on appropriateness for support for the learning tasks and lin-guistic demand of the task. The ELL ECFs offer not just a ‘‘what todo’’ for ELLs, but a rational as to ‘‘why’’ these practices would beeffective, a missing component of other science curriculum materi-als. The ECFs also offer opportunity to build expertise, as the prac-tice are repeated across literacy and science sessions.

2.3. Instruments and data collection

The analysis for this study used the following subset of mea-sures from the larger study: classroom observations, teacher inter-views, student science and vocabulary assessments, and observermark-up of the teacher’s guide.

2.3.1. Classroom observationsTrained observers conducted three observations of about

60 min in each classroom during each year of the study using adetailed observation protocol, the Science Classroom ObservationProtocol (SCOP) (Billman & Cervetti, 2012). The SCOP is designedto document the wide array of instructional practices observed ininquiry-based science instruction, including science instructionthat involves a strong focus on reading, writing, and language.Observers document instruction in 10-min segments alternatingbetween 7 min of narrative note-taking and 3 min of real-time. Afive level coding scheme is used, which was designed to documentmaterials, groupings, and activities. The SCOP also includes a 32-item checklist of instructional strategies for supporting ELLs thatobservers use to document the teacher’s use of strategies with ELLsduring each 10-min segment (see Appendix A). The checklist wasdeveloped through a cross-reference of teacher education textsused to support teacher learning of ELL pedagogy. It was then

lish/Spanish cognates—words with a similar

some academic words in English (solar/lunar)

out the existence of cognates to Spanish-

a Latin-based native language) can facilitate

ook. To use this strategy, first explain what

on cognates (visit/visitar; plant/planta). Ask

ents go on a cognate hunt in the book before

ell students that when they come across a

see if the word is a cognate. [A list of

guage can help English language learners

irs of students that can speak the same native

nguage during the Shared Listening routine.

uded in the treatment teacher guide.



Sample Science Knowledge Item

How would you explain what a year is?

a. The time it takes for the Earth to

turn once on its axis.

b. The time it takes for the Sun to

orbit the Earth.

c. The time it takes for Earth to orbit

the Sun (correct response).

d. The time it takes for the Moon to

orbit the Earth.

Sample Vocabulary Item

To move around an object in space

a. Orbit (correct response).

b. Claim

c. Rotate

d. Sphere

Fig. 2. Sample items from the student assessments.


shared with three experts in the ELL field to further refine the cat-egories (e.g., Building or using background knowledge including L1,(First language) Scaffolding using images or realia). The checklistrepresents a comprehensive set of scaffolds for ELLs that werenot developed to align with the ECF’s in the curriculum but to pro-vide an overall set of instructional strategies identified to be effec-tive in amplifying instruction for ELLs.

Thirteen observers attended a three-day training in Study Year1. The training included a detailed introduction to the SCOP fol-lowed by practice using the protocol and coding scheme. Interrater(IRR) reliability checks, calculated as percentage of absolute agree-ment across all observers, were conducted throughout the trainingand divergences in coding and understanding of the scheme wereaddressed. Because we were not able to reach an acceptable IRR bythe end of the three-day training, we conducted two further IRRchecks—one before data collection began and one after the firstround of data collection. Video clips and directions were distrib-uted to observers who recorded notes and coded the instruction.In the second check, we achieved an IRR of 78% counting bothmissed codes and overcoding as disagreement. This same trainingwas repeated in August 2010 for the group of five observers whoconducted the observations in Study Year 2. During this training,the team achieved an average IRR rate of 90%. Four additionalIRR checks were conducted during the data collection period withan average IRR at 83%.

2.3.2. Teacher interviewsAll participating teachers were interviewed five times each

year—before and after implementation of the intervention unitand, briefly, following each of three observations. Project staff con-ducted all interviews using a structured protocol. The pre-imple-mentation and post-implementation interviews each yearfocused on the teachers’ goals and priorities, perceptions of stu-dents’ learning and engagement as well as how classroom andschool contexts influenced teaching practices. Teachers’ responsesto the ECF’s in the teacher’s guide were also collected. The briefpost-observation interviews asked teachers about modificationsmade to the observed lesson, particularly those intended to meetthe needs of various subgroups in the classroom, including ELLs.

2.3.3. Marked-up teacher’s guideThe marked-up teacher’s guide was used to track teachers’

fidelity of implementation. Immediately following the classroomobservations, observers used a printed copy of the observed lessonto mark any part of the lesson that the teacher implemented dur-


ing the lesson—whether part of the left-hand step-by-step plan orthe optional right-hand ECF’s. We assigned fidelity scores (percent-ages) for left-hand implementation and right-hand implementa-tion based on the observer markups. For the right-hand ECF’s,only observable notes were included in the calculation. Back-ground information about the rationale for a particular instruc-tional routine would not be included because it is not actionableor observable.

2.3.4. Student science knowledge assessmentAll students took a pre-post assessment of space science con-

cepts addressed in the instructional unit. The pre-post scalesincluded 20 multiple-choice items that were scored dichoto-mously. Internal consistency estimates for pre-post scales were.74 and .80, respectively. Item responses from 1296 students whoparticipated in Study Year 1 were analyzed to assess the initialdimensionality of the scales. We ran confirmatory factor-analyticprocedures using LISREL 8 (Jöreskog & Sörbom, 1999). Scores atpretest and posttest were unidimensional as supported by one-fac-tor solutions, respectively. Further, pre-post scales had very com-parable factor loadings. Adjusted goodness-of-fit (AGFI) and RootMean Square Error of Approximation (RMSEA) were identical forpre-post measures with estimates of .97 and .03, respectively.These goodness-of-fit index values suggest good model-data fit(e.g., MacCallum, Browne, & Sugawara, 1996; McDonald, 1999) asthe AGFI is greater than .95 and the RMSEA is less than .05. Across-validation study was conducted for the item scores analyzedin the present investigation. For the significantly smaller samplesize (i.e., Study Year 2), AGFI and RMSEA were .93 and .04 at pre-test. At posttest, the AGFI was .91 and the RMSEA was .05 forone-factor results. The AGFI values are acceptable, and the RMSEAestimates are good as they are less than .05 (e.g., MacCallum et al.,1996). Collectively, the series of results provided support for thereliability and validity of scores. As the example illustrates, theitems were constructed to measure procedural or conditionalknowledge (Alexander, 1997) rather than basic declarative factsabout planets, moons, and the solar system. A sample item isincluded in Fig. 2.

2.3.5. Student vocabulary assessmentAll students took a 10-item multiple-choice, pre-post assess-

ment of space science vocabulary. Results of CFA analyses sup-ported the comparable unidimensionality of the scale at pretestand posttest. AGFI and RMSEA values were .98 and .035, respec-tively, for both pre- and post-scales. The indices of model-data fit




are good (e.g., MacCallum et al., 1996; McDonald, 1999). Cron-bach’s a was .65 for the pre-post scale. A sample item is includedin Fig. 2.

2.4. Procedures

Trained researchers administered the assessments to studentsin their regular classrooms. Pre-assessments and post-assessmentswere administered 10 or 11 weeks apart to allow time for teachersto complete the 40-session space science unit. Students wereadministered the vocabulary assessment prior to the scienceassessment. Administration of both assessments took approxi-mately 60 min to complete. The assessments were read aloud tostudents in order to mitigate any confounding of reading abilitywith science and vocabulary knowledge. Teachers completed abackground survey and watched an orientation video while stu-dents took the assessments.

2.5. Data analysis

Data analysis procedures focused on two levels of analysis. Toaddress research questions 1 and 2, we documented teachers’use of instructional strategies with the ELLs in their classroomsand compared results for treatment and comparison classrooms.To address research question 3, which pertains to ELLs’ (n = 147)science learning, we examined the data using multilevel modelingprocedures. Level 1 was the student-level of analysis while Level 2was the classroom-level of analysis. As noted by other researchers(e.g., Snijders & Bosker, 1999), our sample sizes are very small atboth levels of analysis. Because of this sampling limitation, we alsostudied descriptive statistics at the classroom level, the level atwhich treatment was assigned randomly, to explore the patternof results obtained.

3. Results

The first research question asked whether or not access to edu-cative notes related to teachers’ use of more ELL-focused strategiesand a wider range of different ELL-focused strategies in treatmentclassrooms than in comparison classrooms. Observation codesfrom the SCOP were used to compute the mean number ELL-focused strategies as well as the total number of unique strategiesused. We calculated the mean number of strategies that observersdocumented per 10-min segment of instruction at each observa-tion. We also calculated the total number of unique strategies usedby each teacher during each observation (across all 10-minsegments).

Differences between treatment conditions in mean number ofstrategies and number of unique strategies were analyzed at theclassroom level using parametric and nonparametric procedures.Only the distribution for mean number of strategies indicated lackof normality; however, given the small sample size of classrooms,we ran both independent t-test and Mann–Whitney U procedures.There were no significant differences between treatment condi-tions (p’s > .13). However, as displayed in Table 3, the descriptivestatistics illustrate that teachers representing the treatment condi-

Table 3Means, standard deviations, and mean ranks for mean number of strategies, number of un

Measure Treatment

Mean SD

Mean Number of Strategies 6.57 3.24Number of Unique Strategies 20.67 6.62New Strategies 7.67 4.80


tion had a higher mean number of strategies as well as a highernumber unique strategies than did their peer teachers representingthe comparison condition. Cohen’s d for mean number of strategieswas .85. Cohen’s d for number of unique strategies was .76. Bothestimates are medium to large effects (Cohen, 1988) as interpretedin standard deviation units. Effect sizes for the comparison of meanranks were r = .36 and r = .38, respectively. These estimates are inthe medium to large range (i.e., .30–.50) based on interpretationof effect sizes reported as correlation coefficient values.

In order to address the second question about the degree towhich teachers added new instructional strategies for ELLs to theirpedagogical repertoires, we coded the number of new, unique ELL-focused strategies reported by each teacher during the formalinterviews and post-observation check-in interviews in responseto questions about strategies they use to support ELLs learning inscience. We assigned each teacher a ‘‘learning’’ score based onthe sum of the new, unique strategies that the teacher reported fol-lowing the first interview. (Strategies reported at the first inter-view were considered already known strategies). Teachers in thetreatment group had a mean learning score of 7.7; that is, follow-ing the first interview, they reported a mean of 7.7 new strategies.Teachers in the comparison group had a mean learning score of 5.1.The distribution for new strategies was approximately normalbased on skewness and kurtosis estimates. Analysis of means andmean ranks (see Table 3) also demonstrated that treatment teach-ers reported knowing more new strategies than teachers repre-senting the comparison group. Although the results were notstatistically significant, p = .18, the effect size for comparison ofmeans was medium to large (i.e., Cohen’s d = .76) as interpretedin standard deviation units. For difference in mean ranks, the effectsize was medium (i.e., r = .31) based on interpretation of effect sizeas a correlation coefficient.

The third research question focuses on ELLs’ learning as the out-come. Specifically, we wanted to determine not only if there weredifferences between treatment and comparison classrooms on stu-dents’ knowledge of both vocabulary and science, but we alsowanted to examine whether the mean number of strategies, thenumber of unique strategies, and number of new strategies thatteachers acquired were correlated with ELLs’ student learning atthe classroom level. Finally, and while not a primary focus of ourstudy, we compared and contrasted effects for ELLs and Non-ELLsusing separate sets of multilevel models to determine whether ornot the patterns were similar for both samples.

3.1. Science vocabulary knowledge

ELL Sample. Results showed significant variation among class-rooms. The intraclass correlation coefficient (ICC) was .20. Meansand standard deviations for pre-post vocabulary scores by class-room are displayed in Table 4.

We followed multilevel modeling strategies outlined byRaudenbush and Bryk (2002) and Singer (1998) and used byButler (2012) in her study of how achievement goals and motiva-tional strategies in teaching are related to students’ perceptionsof instruction. First, we entered the percentage of ELLs enrolledas a classroom, contextual variable along with pre-vocabulary

ique strategies, and new strategies by treatment condition.

Comparison

Mean Rank Mean SD Mean Rank

10.00 4.50 1.77 6.6710.08 16.78 3.89 6.619.67 5.11 2.08 6.89



Table 4Means and standard deviations for pre-post vocabulary knowledge by classroom forELL and non-ELL students.

Classroom Pretest Posttest

ELL Non-ELL Total ELL Non-ELL TotalM M M M M M(SD) (SD) (SD) (SD) (SD) (SD)

Treatment1 4.50 6.00 5.74 5.75 7.95 7.57

(2.08) (1.49) (1.66) (1.26) (1.39) (1.59)2 4.56 3.92 4.28 4.88 5.69 5.24

(2.03) (1.38) (1.77) (2.16) (1.75) (1.99)3 4.80 5.93 5.63 7.60 7.50 7.53

(1.30) (2.13) (1.98) (2.61) (2.50) (2.46)4 4.91 6.36 5.72 6.18 7.00 6.64

(1.45) (1.65) (1.70) (1.83) (1.80) (1.82)5 5.45 5.60 5.52 7.09 8.10 7.57

(2.02) (2.99) (2.46) (2.34) (1.66) (2.06)6 6.17 7.19 6.96 8.83 8.48 8.56

(2.14) (2.09) (2.10) (0.75) (1.29) (1.19)

Comparison7 3.83 6.43 5.23 7.00 8.00 7.54

(1.99) (2.47) (2.58) (1.76) (1.92) (1.88)8 4.67 7.43 5.88 6.89 9.29 7.94

(1.22) (2.37) (2.25) (1.05) (1.25) (1.65)9 4.33 3.00 4.24 5.04 5.50 5.07

(1.92) (0.00) (1.88) (1.70) (3.54) (1.77)10 5.80 8.45 7.96 7.60 8.86 8.63

(3.03) (1.60) (2.14) (1.52) (1.04) (1.21)11 6.50 7.75 7.59 7.25 8.50 8.34

(1.29) (2.01) (1.97) (1.71) (1.35) (1.43)12 4.60 7.20 5.25 6.13 8.20 6.65

(2.20) (2.17) (2.43) (1.96) (1.64) (2.06)13 5.00 6.70 6.39 6.80 8.30 8.04

(2.00) (1.79) (1.91) (1.10) (1.36) (1.43)14 5.00 5.67 5.20 7.07 8.33 7.45

(1.47) (2.16) (1.67) (1.38) (2.25) (1.73)15 6.67 6.77 6.75 7.67 7.08 7.19

(2.52) (2.01) (2.02) (2.31) (1.66) (1.72)

Mean TotalsTreatment 5.02 5.97 5.63 6.38 7.54 7.12

(1.87) (2.15) (2.09) (2.32) (1.91) (2.14)Comparison 4.72 7.19 6.11 6.35 8.29 7.44

(1.98) (2.14) (2.40) (1.82) (1.60) (1.95)All 4.83 6.67 5.91 6.36 7.97 7.31

(1.94) (2.22) (2.29) (2.01) (1.77) (2.03)

Table 5Means and standard deviations for pre-post science knowledge by classroom for ELLand non-ELL students.

Classroom Pretest Posttest

ELL Non-ELL Total ELL Non-ELL TotalM M M M M M(SD) (SD) (SD) (SD) (SD) (SD)

Treatment1 8.75 11.32 10.87 11.50 15.42 14.74

(3.78) (3.64) (3.71) (3.42) (3.10) (3.43)2 5.69 6.46 6.03 8.00 8.77 8.34

(1.78) (2.99) (2.38) (2.37) (3.98) (3.15)3 7.60 9.00 8.63 9.80 11.93 11.37

(0.89) (3.31) (2.91) (1.79) (4.14) (3.74)4 8.18 9.79 9.08 12.00 11.36 11.64

(3.31) (3.73) (3.57) (3.03) (4.14) (3.64)5 8.00 10.40 9.14 11.73 13.40 12.52

(2.90) (3.50) (3.35) (2.76) (2.91) (2.89)6 12.67 11.33 11.63 15.00 14.76 14.81

(3.14) (4.20) (3.97) (4.47) (3.81) (3.87)

Comparison7 6.58 11.07 9.00 13.33 15.07 14.27

(3.29) (3.95) (4.25) (2.87) (3.45) (3.26)8 5.67 10.43 7.75 10.78 16.29 13.19

(2.55) (2.76) (3.53) (3.31) (2.81) (4.12)9 6.19 4.00 6.03 8.41 9.00 8.45

(2.95) (1.41) (2.91) (2.89) (5.66) (2.98)10 7.60 10.50 9.96 11.20 16.00 15.11

(3.36) (2.96) (3.18) (5.76) (3.02) (4.01)11 10.25 12.25 12.00 15.25 17.18 16.94

(2.63) (4.08) (3.95) (3.30) (3.24) (3.26)12 6.40 10.20 7.35 9.00 12.40 9.85

(2.26) (3.56) (3.05) (2.78) (4.98) (3.63)13 8.80 8.43 8.50 13.40 13.39 13.39

(1.30) (2.94) (2.70) (1.52) (3.88) (3.55)14 6.00 7.67 6.50 11.36 12.67 11.75

(2.63) (5.82) (3.78) (3.18) (3.93) (3.37)15 8.33 7.85 7.94 11.33 9.62 9.94

(4.93) (3.89) (3.92) (6.66) (3.80) (4.23)

Mean TotalsTreatment 7.89 9.93 9.18 10.83 12.93 12.16

(3.27) (3.92) (3.81) (3.57) (4.27) (4.14)Comparison 6.65 10.02 8.54 10.60 14.56 12.82

(2.91) (3.95) (3.90) (3.73) (4.21) (4.46)All 7.10 9.99 8.80 10.68 13.88 12.55

(3.09) (3.93) (3.88) (3.66) (4.30) (4.34)


scores at the student-level of analysis. Both predictor variableswere significant fixed effects. For percentage of ELLs, estimateswere: b = �.020, SE = .009 (p < .05). For pretest scores, estimateswere: b = .30, SE = .07 (p < .0001). Inclusion of these two variablesreduced the ICC from .20 to .12. Variation at the student-level ofanalysis was reduced by 40 percent. Descriptively, the coefficientsindicate that as percentage of ELLs representation increased, post-vocabulary scores decreased. As pretest scores increased, post-scores also increased. These patterns of result are expected.

Next, we examined the effects of treatment assignment, meannumber of strategies as well as their interaction. There were no sig-nificant fixed effects (i.e., p’s > .34).

Non-ELL Sample. For the Non-ELL sample, the ICC for the uncon-ditional model was .20. Only pretest vocabulary scores wererelated significantly to posttest scores, b = .51, SE = .04 (p < .0001).With inclusion of this predictor variable, the ICC reduced to .09.

3.2. Science knowledge

Our approach for analyzing the science knowledge scoresmatched those procedures used to analyze vocabulary scores.The unconditional model for the ELL sample indicated significant


variation among classrooms. The ICC was .27 (see Table 5 formeans and standard deviations).

Similar to results reported for vocabulary knowledge, percent-age of ELLs enrolled was a significant classroom predictor variable(i.e., b = �.058, SE = .015, p < .01). Pretest scores were related toposttest scores; b = .45, SE = .09, p < .0001). Descriptively, theseresults parallel those summarized for vocabulary knowledge. Aspercentage of ELL representation increases, scores decrease. Fur-ther, pre-post scores are related positively. The ICC reduced to.14. Both variables explained 48% of the variation in posttestscores.

Treatment assignment, mean number of strategies and theinteraction between variables were not significantly related tothe outcome (p’s > .19); however, it is important to acknowledgethat treatment assignment was related negatively to scienceknowledge after controlling for percentage of ELLs and pretestscores. Descriptively, this result indicates that comparison class-rooms had greater mean scores than treatment classrooms. How-ever, and while not statistically significant, mean number ofstrategies were positively related to the post science scores. Resultsfor question 1 show that teachers providing instruction in treat-ment classrooms used more of these strategies than teachers rep-resenting comparison classrooms. While we do not have sufficient




sample sizes to specify and test a path-analytic model with directand indirect effects on learning, we attempt to explore statisticallythe relations among treatment assignment and instructional strat-egies in greater detail after we summarize the multilevel modelingresults for the Non-ELL sample.

Non-ELL Sample. For the Non-ELL sample, the ICC for the uncon-ditional model was .30. Only pretest vocabulary scores wererelated significantly to posttest scores, b = .63, SE = .06 (p < .0001).With inclusion of this predictor variable, the ICC reduced to .14.

3.3. Additional descriptive analyses

The summaries for our final analysis are descriptive and focuson the ELLs’ science growth and its association with teachers’ useof instructional strategies with ELLs. We studied correlationsamong teachers’ instructional strategy use and their ELLs’ gainsin science learning. Descriptively, we examined the variation incorrelation coefficient patterns between treatment and compari-son classrooms for ELLs. We used both raw gain scores and unstan-dardized residuals in this analysis. While the gain scores werehighly correlated with the unstandardized residuals at the class-room level (r’s > .70), we included both given limitations notedby research methodologists when using gains as outcome mea-sures (e.g., Kasden, 1977).

Within the treatment group, the use of a higher mean numberof strategies per 10-min observed segment across the three Year2 observations was strongly associated with higher gains for ELLson the science measure (r = .87) as well as with the unstandardizedresiduals (r = .77). In the comparison group, there was only a weakpositive relation between mean number of strategies and gain inscience learning (r = .32) and almost no association with theunstandardized residuals (r = .04). The use of a wider range ofstrategies (i.e., a higher number of unique strategies observedacross the Year 2 observations) was also moderately related to sci-ence learning for the treatment classrooms, r = .64 (for gain scores)and r = .61 (for unstandardized residuals) while there was weakrelation between variables for the comparison classrooms(r’s < �.18).

4. Discussion

The purpose of this research was to examine the hypothesesthat the presence of educative curriculum features focused onstrategies for use with ELLs would increase the number and diver-sity of strategies that teachers used, would lead teachers to addnew strategies to their pedagogical repertoires, and would increasethe quality of the instructional strategies teachers used to supportELLs in science. Moreover, we hypothesized that increased use ofthese instructional strategies would be related to growth in ELLs’science learning.

4.1. Teachers’ use of strategies

Fifteen teachers taught the same curriculum either with orwithout the educative curriculum features. Teachers in bothgroups varied widely in their use of instructional strategies for ELLsin science. Although our small sample size undermined our abilityto achieve statistical significance in the analysis of the teacherenactment and learning variables, we found moderate to largeeffect sizes favoring the treatment group in the mean number ofstrategies for ELLs that teachers were observed enacting, the meannumber of unique strategies that teachers were observed enacting,and the number of unique, new strategies that teachers reportedusing with ELLs in science over the course of the study. That is,treatment teachers were, on average, doing more than control


teachers to modify the curriculum to support the ELLs in theirclassrooms, and they were using a wider range of strategies in thiseffort. In addition, the effect size for comparison of means forteachers’ acquisition of new, unique strategies was medium tolarge in favor of treatment teachers.

4.2. ELL strategies and student learning

In response to the question about the impact of ECMs on stu-dent learning, we examined both the relation of treatment assign-ment to student growth and the association of ELL-focusedstrategy use with student growth within each group. Students’ sci-ence and vocabulary pretest and posttest scores varied consider-ably across classrooms, though every classroom demonstratedpositive and significant growth from pre- to post- for both ELLsand non-ELLs on science and vocabulary assessments. These gainsare unsurprising given that the core curriculum taught by teachersin both treatment groups was designed as inquiry-oriented, lan-guage-rich instruction and was based on a curriculum model thathas been shown to support students’, including ELLs’, science andvocabulary learning in previous studies (e.g., Bravo & Cervetti,2014; Cervetti, Barber, Dorph, Pearson, & Goldschmidt, 2012;Cervetti, Pearson, Bravo, & Barber, 2006). Although students (ELLand non-ELL) in the treatment group did not, on average, makegreater growth than those in the comparison group on either thescience or the vocabulary measure—in fact, the trend for sciencelearning favored the comparison group—we were able to discerndifferent patterns of correlations between ELL’s growth and finalscience knowledge scores as related to teachers’ use of strategiesacross the treatment and comparison groups. The mean numberof strategies used by teachers was more closely associated withELLs’ gains on the science measure in the treatment group thanin the comparison group. Thus, though the availability of the ECFsdid not impact student learning overall, the mean number of strat-egies used by teachers had a strong, positive relationship withELLs’ science learning in the treatment group, but had a very lowto almost no association with student learning in the comparisongroup.

Though not all treatment teachers enacted a large number ofstrategies with their ELL students, some teachers in the treatmentgroup—particularly those with less teaching experience—seemedto be receptive to trying new instructional strategies offered bythe ECF’s, and the strategies used by these high implementers seemto have been supportive of ELLs’ science learning.

5. Conclusions

The findings of this study confirm prior research, which hasdemonstrated that educative curriculum materials can impactteachers’ implementation and their learning about pedagogy(Collopy, 2003; Schneider, Krajcik, & Blumenfeld, 2005). The find-ings also extend this knowledge base. While other studies haveconcentrated efforts on the overall implementation and learningfrom curriculum materials (Bodzin et al., 2012; Schneider et al.,2000), the present study illustrates potential for teacher learningfrom educative curriculum features developed to support particu-lar subgroups of learners—in this case ELLs. The ECF’s examined inthis study provided teachers in the treatment group with instruc-tional supports that more carefully scaffolded ELLs’ experienceswith science instruction. The results of this study suggest that edu-cative curriculum materials may be a viable way to provide profes-sional learning opportunities to teachers that improve their abilityto offer differentiated instruction to ELLs.

With the projected growth of the ELL population, the questionof how to deliver support to teachers that serve ELLs has gained




importance nationwide (e.g., NEA, 2011). It is also clear ELLs arenot performing as well academically as their native English-speak-ing peers, especially in science (Lee, 2005). Examinations of theviability of supporting teachers of ELLs via educative curriculummaterials can inform efforts to support teachers in states likeNebraska and North Carolina where teachers have relatively littleprior experience serving ELLs and where the number of ELLs is ris-ing rapidly.

Given this study’s focus on studying the educative curriculummaterials in an ecologically valid way—situating the study in intactclassrooms and doing little to shape teachers’ use of the materials—it is not surprising that the treatment teachers varied in the degreeof uptake of the instructional strategies offered in the educativefeatures. Previous research on educative curriculum materials hasfound similar variation in teachers’ use of the materials (e.g.,Collopy, 2003). In addition, most models of instruction viewinstruction as emerging from a complex interaction among teach-ers’ beliefs, goals, and knowledge and the curriculum they use(Charalambous & Hill, 2012; Davis, Beyer, Forbes, & Stevens,2011). A number of studies have demonstrated this complexity(Davis et al., 2011; Drake & Sherin, 2006; Remillard & Bryans,2004). For example, in a study of how two primary-level teachersapproached and adapted a reform-oriented mathematics curricu-lum, Drake and Sherin (2006) found that teachers have individualand distinctive patterns of curriculum adaptation that aregrounded in their own experiences as learners and teachers ofmathematics. These experiences led, for example, to differenttreatments of terminology in learning mathematics, and theyshaped the levels of relative emphasis given to big conceptual goalsand the intervening procedural steps. In a separate case studyexamination of two of the treatment teachers who participatedin the current study (Cervetti et al., 2012), we found that the teach-ers’ decisions and whether and how to implement the ELL instruc-tional suggestions were shaped by personal and contextual factors,such as teachers’ feelings of efficacy in teaching ELLs, their percep-tions of the alignment of the strategies with their goals and theirassessments of students’ needs, and administrative support. In par-ticular, teachers focused on the degree to which they believed theirparticular ELL students needed different kinds of instructional sup-ports than the rest of the students in the class.

In terms of future directions, this study suggests that more con-sideration needs to be given to supporting teachers’ engagementwith educative curriculum materials. Although the current studyprovides suggestive evidence that providing a set of optional ECF’scan impact teachers’ practice and knowledge, considering how tobetter contextualize and support teachers’ use of educative curric-ulum materials is an important direction for the future. Treatmentteachers’ use of instructional strategies for ELL was positively asso-ciated with ELL’s growth in science achievement, but some of thetreatment teachers used few strategies, instead opting to offer amore uniform curriculum implementation to ELLs and Non-ELLs.It may be that a stronger orientation toward the educative featuresof the curriculum would have encouraged teachers to engage morefully with these features. Without specific support in understand-ing the goals of educative curriculum materials, the findings of thisstudy may have underestimated the potential impact of educativecurriculum materials.

The intervention in the current study was modest by compari-son to more multi-faceted and lengthy professional developmentprograms that have shown positive impacts on student learning.In a review of the evidence on teacher professional developmentand student achievement, Yoon, Duncan, Lee, Scarloss, andShapley (2007) found that professional development programsshowing positive effects on student learning were intensive (14 hor longer) and that all but one included follow-up support. A sec-ond meta-analysis of mathematics and science professional


development program showed that total time in professionaldevelopment for studies with significant effects on student out-comes was 50 h or more (Blank, de las Alas, & Smith, 2008). As withthe Yoon et al. study, Blank et al. found that many of the effectiveprograms involved coaching and mentoring following the profes-sional development workshop experience. Although educative cur-riculum materials have the potential to approximate a sustainedprofessional development experience through their close link today-to-day instruction, the intensity of that experience is depen-dent on the nature and extent of teachers’ engagement with theeducative features.

It is likely that combining educative curricula with professionaldevelopment opportunities linked to the implementation of thosecurricula would have resulted in higher levels of teacher learningand strategy use. In addition, a combined approach may providea balance between the time- and cost-efficiency of curriculum-based professional learning opportunities and the social supportof face-to-face professional development. Supporting their use ofthe materials with other professional learning opportunities, suchas face-to-face professional development or coaching, may haveincreased the intensity, and thus the impact, of the intervention.Professional development might also provide a helpful bridgebetween the strategies offered in the curriculum and teachers’existing ideas and goals. This connection has been shown to bean important factor in teachers’ use of educative curriculum mate-rials (e.g., Schneider, 2013).

It may also have been helpful to provide additional informationabout each of the strategies offered as part of the ECF’s. The notesfocused on describing the strategies and rationales for the utility ofthe strategies. Treatment teachers may have been more likely touse the strategies if the strategies were more clearly linked to par-ticular challenges and resources that the teachers might haveobserved in their students. This may have been particularly impor-tant given the diversity of the ELL population (e.g., English profi-ciency level, native language proficiency level). Previous researchhas documented the importance of the link between teachers’uptake of professional learning opportunities and their perceptionsof their particular students’ needs (Truscott & Truscott, 2004). Forexample, Davis et al. (2011) found that ECF implementation isinfluenced by what teachers know about their students. Futureresearch might examine approaches that combine educative cur-riculum materials with targeted face-to-fact professional develop-ment designed to heighten teachers’ awareness of the educativefeatures, to help the teachers make decisions about the fit betweenthe particular instructional strategies described in the ECF’s andthe needs of their students, and to help teachers incorporate theinstructional strategies and underlying understandings aboutlearning and development into their general practice.

Consistent with the focus of this special journal issue, this studydemonstrates the practical and methodological complexities asso-ciated with examining complicated interventions implemented byteachers in natural classroom settings. As such, we close with sam-pling and methodological considerations for future research stud-ies based on our results that only represented scores for 15classrooms and 358 students, and for only 147 ELL students forwhom the instructional strategies of the intervention were recom-mended. At both the classroom- and student-levels of analysis oursample sizes are small. However, such small sample sizes are to beappreciated as those which can honestly be attained given a focuson ELLs’ learning in classrooms where the representation of ELLstudents by classroom is currently often relatively small.

The percentage of ELLs represented in any classroom as well asthe multilingual make-up of the classroom are most importantvariables to which analysts must attend. Guglielmi (2012) summa-rizes that by 2030, as many as 40% of students representing school-age populations could be ELLs. It seems certain that quantitative




methodologists must study all classroom and student variablesmost carefully as they assist in planning of future correlationaland/or experimental investigations to study statistically the effectsof both instructional and individual-difference variables thatinform curricular practices to benefit all students. Our currentinvestigation had few classrooms for which we could study thisvariable well, overall and for the various languages spoken by ELLs.Yet, our results seemed clear. Percentage of ELLs representing ourclassrooms significantly explained the variance of scores in sciencelearning that we were able to collect for the current investigation.

6. Limitations

Although the current study has extended our understanding ofthe utility of educative curriculum materials to support teachers’work with ELLs, it has several limitations that bear on the reliabil-ity of the results and subsequent implications.

First the reliability estimates for the student vocabulary and sci-ence measures were low at pretest, introducing some instabilityinto the estimates of growth. Improving the measures might yieldmore reliable results and more precise estimates of the impact ofeducative curriculum materials on student learning.

Second, the small sample size made it difficult to achieve statis-tical significance even in analyses that demonstrated medium tolarge effect sizes. In some cases, a single outlier at the teacher levelhad a meaningful impact on the results. These analyses suggest theimportance of attending to individual differences in investigationssuch as the one we have conducted for all levels of analysis underconsideration in the study of relations among variables.

Finally, record of teachers’ strategy use was based on a rela-tively small number of classroom observations. Recording strate-gies from more classroom observations could have resulted in amore in-depth understanding of the interplay among the types ofstrategies teachers used, the purposes or goals of the lessonstaught, and the specific types of knowledge and skills studentswere learning than what we have been able to summarize forthe current investigation.

Acknowledgments

This article is based upon work partially supported by theNational Science Foundation under Grant Number 0822119. TheFederal Government has certain rights in this material. Any opin-ions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflectthe views of the National Science Foundation.

Appendix A. ELL-focused strategies coded in the classroomobservations

Building or using background knowledge including L1.

� Building background knowledge—e.g., preteaching vocabularyor concepts related to an investigation.� Relating concepts or experiences to the students’ learning from

prior activities or connecting across curriculum areas.� Relating concepts or experiences to the students’ prior

knowledge.� Using cognates to explain words or concepts.� Translating to/from students’ L1’s.� Providing opportunities for students to use L1 in talk, reading,

or writing.� Making connections between science and students’ cultures or

communities.


Scaffolding using images or realia.

� Using prepared visual material, such as picture, diagrams, andgraphic organizers to explain or engage students with conceptsor processes.� Providing written or visual references for instructions.� Creating a written record of students responses or of the discus-

sion or QA.� Using physical objects or kinesthetic activities to explain or

engage students with concepts or processes.� Creating visual representations, such as pictures, diagrams, and

graphic organizers during the lesson.� Using environmental print as reference/resource.

Opportunities for additional practice/time.

� Providing practice with key vocabulary words, such as wordmapping.� Providing additional practice with reading, writing, or talk.� Providing addition time to complete work requiring written

responses.

Modifications to teacher input or interactions.

� Using repetition or restatement in his/her explanations.� Repetition or restatement of student responses.� Providing wait time for responses in his/her talk with students.� Asking leveled questions.� Asking students to repeat back or summarize instructions or

main points.� Using strategies for choosing who talks other than hand-raising.� Using metaphor or simile to explain concepts.

Modifications to arrangements and routines.

� Engaging students in partnered reading or discussion (e.g.,bilingual buddies).� Referring to established routines for classroom activity.� Making language-based grouping choices.

Modifications to modalities.

� Inviting choral or simultaneous group responses (e.g., thumbsup/down, response cards, etc.).� Asking students to use visual representations, including draw-

ing or graphic organizers.� Providing opportunities to use different modalities to respond

or show understanding.

Attention to language development.

� Attending to linguistic ‘‘blindspots’’ for second language learn-ers (e.g., multiple meaning words & figurative language, includ-ing metaphors, clichés, idioms).� Talking about language in science (e.g., differences from lan-

guage in other contexts).� Providing feedback on student miscues (written or oral form).

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