Scaffolding English Language Learners and
Struggling Readers in a Universal Literacy
Environment With Embedded Strategy
Instruction and Vocabulary Support
C. Patrick Proctor, Bridget Dalton, and Dana L. Grisham
National Center on UDL
40 Harvard Mills Square, Suite 3
Wakefield, MA 01880-3233
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781-245-9320
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781-245-5212
Web: www.udlcenter.org
Scaffolding English Language Learners and
Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy
Instruction and Vocabulary Support
C. Patrick Proctor, Bridget Dalton, and Dana L. Grisham
Originally published as:
Proctor, C. P., Dalton, B., & Grisham, D. L. (2007). Scaffolding english language learners and
struggling readers in a universal literacy environment with embedded strategy instruction and
vocabulary support. Journal of Literacy Research, 39(1), 71-93. doi:10.1080/10862960709336758
Table of Contents
Theoretical and Empirical Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
As interest and concern rise in U.S. educational circles around the reading achievement
of English language learners (ELLs) and struggling readers, researchers and practitioners
alike are calling for the increased use of technology as a means to decrease achievement
gaps in reading (Jiménez, 2003; Strangman & Dalton, 2005). In this article, we report results
from a 4-week study of the English reading comprehension of struggling readers, including
Spanish-speaking ELLs. Thirty 4th-grade students read several narrative and informational
hypertexts that provided embedded vocabulary and comprehension strategy supports,
along with text-to-speech read-aloud functionality. Correlation analyses of pre–post
standardized reading vocabulary gain scores revealed that vocabulary gain was associated,
although not significantly, with the frequency of access of hyperlinked glossary items
throughout the intervention, and that lower pretest vocabulary knowledge was associated
with positive vocabulary gains. A similar pattern was detected for comprehension gains,
which were significantly associated with the frequency of access of coaching avatars that
provided support around the productive use of reading comprehension strategies.
The results reported here suggest that struggling readers and Spanish-speaking ELLs
made use of the digitally embedded features in such a way as to promote both learning
novel lexical items and effectively applying reading comprehension strategies. The
results of the 2003 National Assessment of Educational Progress (NAEP) underscore
a well-known and urgent issue for reading achievement in the United States: 37% of
students in Grade 4 and 26% of students in Grade 8 could not read at a basic level
(National Center for Education Statistics, 2003). Of special concern is the continued
gap in achievement for children in different demographic groups, especially given the
increasing diversity of U.S. classrooms. The NAEP fourth-grade results showed 75%
of White students reading at or above a basic level. By contrast, only 44% of Hispanic
students and 40% of African American students performed at this level. Similar gaps
in achievement also persist between students who are eligible for free or reduced
lunch and their more affluent peers. Although reading research has often targeted
understanding how and why children struggle with text comprehension, the vast majority
of this research has been conducted with monolingual English-speaking populations
(see, e.g., Stanovich, 2000, for an impressive overview of the state of reading research,
with little mention of non-English-speaking groups). Considerably more work must
be done with English language learners (ELLs) alongside their English- only (EO)
counterparts to better understand the components and processes of English reading
comprehension and to develop appropriate instructional interventions that target the
persistent gap in reading achievement illuminated in the NAEP report.
The RAND Reading Study Group (2002) indicates a number of gaps in the field of
reading comprehension research. Specifically, readers’ cognitive and metacognitive
strategy development, vocabulary, and linguistic knowledge are variables that exert
considerable influence on reading comprehension processes and outcomes. We know
little about how to enhance these reader attributes or how to individualize text and
instruction to differentially support students’ diverse capabilities and limitations to
optimize learning.
1.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Classroom technology use has the potential to provide struggling readers and ELLs
with access to crucial digital literacies while working to improve vocabulary and reading
comprehension outcomes (Kamil, 2003; Kamil, Intrator, & Kim, 2000; Kim & Kamil,
2003; Laufer & Hill, 2000; Leu, 2000). The most common forms of support provide
access to the content (e.g., a struggling reader may use text-to-speech (TTS) support to
have text read aloud) or additional information needed to comprehend the text (e.g.,
a glossary or background knowledge hyperlink). Of particular promise is the relatively
small body of research on hypertexts designed to support students’ strategic processing
of text (Anderson-Inman & Horney, 1998; Dalton & Strangman, 2006; Reinking, 1988;
Strangman & Dalton, 2005).
Digital reading environments can also be designed and programmed to present
important information in a systematic and consistent fashion, thus ensuring comparable
access for all students. This is particularly promising for speakers of languages other
than English, as supports relative to students’ native language (e.g., translations) may
be provided in their first language (L1), creating a rich linguistic environment in which
to build relevant lexical and metacognitive skills crucial for facile English-language text
comprehension. Programmable digital environments are most certainly not intended to
replace the teacher, but their use creates opportunities to present important information
to students in such a way as to target individual differences in an effort to promote
positive reading and learning experiences that can be supplemented offline through
typical teacher–student interactions.
The study reported here is an initial investigation into the potential effectiveness of a
digital approach to supported reading called a Universal Literacy Environment (ULE). This
approach is an adaptation of a prototype previously developed for struggling readers
(Dalton & Pisha, 2001; Dalton, Pisha, Eagleton, Coyne, & Deysher, 2002) and derived
from classic work on reading comprehension instruction, specifically reciprocal teaching
(Palincsar & Brown, 1984, 1989) and the principles of Universal Design for Learning (UDL;
Rose & Meyer, 2002). UDL advocates that curricular materials be designed with sufficient
flexibility that students of varying levels of aptitude, language proficiency, and cognitive
functioning may access, and learn from, equivalent materials. Using a ULE, students
may access a number of comprehension-scaffolding features, such as (a) pedagogical
coaches who model appropriate responses to comprehension strategy prompts;
(b) hyperlinked vocabulary words for which definitions, translations, example sentences,
and relevant graphics are provided; and (c) TTS read-aloud functionality that reduces
the decoding demands of many challenging texts (Dalton & Strangman, 2006; Rose &
Dalton, 2002). The ULE tested here also draws on existing research on bilingual students’
reading behaviors and was developed under the assumption that children learning
English as a second language may deploy literacy skills in their L1 to enhance second
language (L2) comprehension outcomes, including translations and cognate awareness
(see, e.g., Jiménez, García, & Pearson, 1996; Nagy, 1988; Nagy, García, Durguno!glu, &
Hancin-Bhatt, 1993; Proctor, August, Carlo, & Snow, 2006).
2.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
We worked with 30 fourth-grade students from two classrooms, 16 of whom were
Spanish-speaking ELLs and 14 of whom were native English-speaking monolinguals. This
study was designed to address the following research questions:
RQ1: What is the effect of working in the ULE on students’vocabulary and
comprehension growth? Do reading gain scores differ as a function of language status
(ELL vs. EO)?
RQ2: Is the use of digitally embedded vocabulary acquisition and comprehension
strategy supports over the course of the intervention related to vocabulary and
comprehension gains?
Theoretical and Empirical Issues
A wealth of research evidence over the last 20 years strongly supports the teaching of
reading comprehension strategies (for recent reviews of this literature, see the report
of the National Reading Panel, 2000; Rosenshine & Meister, 1994; Swanson, 1999;
Wong, 1991). Specifically, Palincsar and Brown’s reciprocal teaching approach is a
promising application of multiple strategy instruction based on an apprenticeship model
of learning (Palincsar, 1986, 1998; Palincsar & Brown, 1984). Support for reciprocal
teaching has been demonstrated across grade levels and with diverse learners, including
students with learning disabilities (Swanson, 1999) and ELLs (García, 1991; Klinger &
Vaughn, 1996). Rosenshine and Meister’s (1994) meta-analysis of 16 reciprocal training
studies found an average effect size of .88 for researcher-developed tests and .32 for
standardized tests. The National Reading Panel (2000) found 11 additional studies not
included in the Rosenshine and Meister meta-analysis that also demonstrated positive
results. Unfortunately, there is a wide gap between research and practice, with very little
strategy instruction (vs. comprehension assessment) taking place in many of today’s
classrooms (Pressley, 1998).
Research on monolingual English populations has demonstrated that skilled readers are
aware of their reading processes and know their strengths and weaknesses, suggesting
that active engagement in self-reflection and goal-setting is a powerful means for
enhancing reading comprehension and writing (Englert, Raphael, Anderson, & Stevens,
1991; Paris, Cross, & Lipson, 1984). With support, students can learn to self-assess
and set appropriate goals for themselves as learners (Lipson & Wixson, 1997). Indeed,
similar phenomena have been observed among Spanish-speaking ELLs. Jiménez, García,
and Pearson (1995, 1996) concluded that Spanish-speaking ELLs employed reading
comprehension strategies comparable to their monolingual counterparts in reading
English-language texts. However, native Spanish speakers also drew on bilingual-specific
strategies such as cognate awareness and translation, suggesting that bilinguals have an
extended array of strategies on which they draw to make sense of challenging Englishlanguage texts.
3.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Vocabulary acquisition has also been shown to be of crucial, if not primary, importance
in predicting reading comprehension outcomes among monolingual students (Anderson
& Freebody, 1983), as well as Spanish-speaking bilingual students (Proctor, Carlo,
August, & Snow, 2005). Such findings are bolstered by research on the apparently
causal relations between vocabulary knowledge and reading comprehension noted by
McKeown, Beck, Omanson, and Perfetti (1983, cited in Stanovich, 2000). Other research
has shown that direct instruction of individual words is not an extremely powerful means
of generating high degrees of word knowledge, but rather, continued exposure to text
(Nagy & Herman, 1985) is more likely to result in extended semantic networks that will
account for increases in children’s vocabulary sizes (Landauer, 1998).
With these issues in mind, there is a growing body of research suggesting the potential
for hypertext, hypermedia, and computer-mediated text to support students’ reading
development (Anderson-Inman & Horney, 1998; Cognition and Technology Group and
Vanderbilt Learning Technology Center, 1993; Dalton & Strangman, 2006; Kamil et
al., 2000; Leu, 2000; Reinking, 1988; Strangman & Dalton, 2005). The most common
forms of support provide access to the content (e.g., a struggling reader may use TTS
support to have the text read aloud via synthetic voice or view a multimedia definition)
or additional information needed to comprehend the text (e.g., an ELL may hear a
word pronounced, learn the Spanish translation for that word, and write a personal
association with the word). Strangman and Dalton (2005) noted the particular promise
of the relatively small body of research on hypertexts designed to support students’
strategic processing of text (e.g., a student might type a response to an embedded
prompt to make a prediction). Relatively little is known about how supports such as
these interact with learner characteristics for EO and ELL students, indicating the need
to systematically test features with different groups of learners.
Dalton and colleagues (Dalton et al., 2002) investigated the impact of reading three ageappropriate novels comparing traditional classroom-based strategy instruction with ULE
versions of the texts. In the study, 102 middle school students in both conditions used
the reciprocal teaching strategies of predict, question, clarify, and summarize (Palincsar
& Brown, 1984), as well as visualization (Pressley, 1998). After controlling for gender and
initial reading achievement, students in the ULE condition demonstrated significantly
greater gains on a standardized measure of reading comprehension than did their
peers in the traditional strategy instruction condition. The effect size was moderate,
equating to approximately half a grade level in reading achievement gain. For struggling
readers who read at or below the 25th percentile prior to intervention, however, this
was a meaningful increase. Dalton, Kennedy, Schleper, Lutz, and Strangman (2005)
adapted the ULE instructional design to include American Sign Language video and
signing avatar representations of the embedded strategy and vocabulary supports for
middle school students who were deaf and hard of hearing and reading several grades
below level. Pilot study results were promising, with 69% of the students improving
their instructional reading level between one and two grade levels, as measured on an
informal reading inventory.
4.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
A key issue in designing digital texts with embedded learning supports is learner
control. The amount of support that is “pushed” to the student, ensuring that he or she
is presented the enhancements, versus voluntarily “pulled” by the student is a critical
question, the answer to which hinges on a student’s own judgments about when and
how often to access a particular support. Several studies have found that students often
do not access supports appropriately and that less successful learners have even greater
difficulty using help, often ignoring support that would clearly be beneficial (Horney &
Anderson-Inman, 1999; van Daal & Reitsma, 1993).
In one of the few studies to examine the effects of user control with young students,
Reinking and Schreiner (1985) found that both good and poor fifth-grade readers
learned more when they were required to use comprehension supports. However, a
subsequent study found no difference in outcomes between students who were free to
access supports at will and those who were required to access supports (Reinking, 1988).
In their work with middle school struggling readers, Dalton and Pisha (2001) observed
that students’ use of supports varied. For example, because most of the students were
reading novels that were 3 years beyond their instructional reading level, they relied
heavily on TTS to have the text read aloud. Many students also accessed strategy
coaches who provided think-alouds and model responses during a reading session.
However, it was rare to see students using available multimedia glossary links, even
when subsequent conversations revealed unfamiliarity with the terms.
Although the research base for the use and effectiveness of digital reading environments
with English-speaking students is growing, interventions specifically targeting nonnative English speakers are almost nonexistent. Such an endeavor requires merging
the existing research on technology and literacy with the knowledge base around
bilingualism, biliteracy, and second language acquisition. Indeed, many of the supports
already described, although monolingual in application, are best practice in nature,
and thus have a place in the education of language minority learners. However,
targeting translation of directions and coaching supports as well as the metalinguistic
components of cross-language similarities and differences are bilingual-specific and have
a meaningful place in the development of the ULE in this study.
5.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Method
Participants
The participants were 30 fourth-grade students in two classrooms in a school district
serving 33,000 students in southern California. The students were recruited from two
connected classrooms whose two teachers worked as a team. These teachers selected
the students who participated in the intervention, resulting in a group comprising 16
Spanish-speaking ELLs and 14 EO students. There were 11 boys and 19 girls. The district
in which the school was located was relatively affluent; however, this particular school
was the only school in the district receiving Title 1 funds. The teachers were aware that
the pedagogical goals of the intervention were to improve comprehension of ELLs
and struggling readers. As a result, they were inclined to select all of the ELL students,
as well as the monolinguals they believed were struggling with text comprehension.
The result was a group of struggling readers from English- and non-English-speaking
backgrounds, performing on average at the 23rd percentile in reading vocabulary
and the 31st percentile in reading comprehension on the Gates–MacGinitie Reading
Achievement Test administered at the beginning of the study.
Online Reading Environment
The tested ULE is a multimedia digital reading environment derived from the work of
Dalton and colleagues (Dalton & Pisha, 2001; Dalton et al., 2002) that gives students
the opportunity to read eight hypertexts, four narrative and four informational, with
embedded supports targeting depth and breadth of vocabulary development (Lively,
August, Carlo, & Snow, 2003; Nagy, 1988) and cognitive and metacognitive strategy
development (Palincsar & Brown, 1984). Each text contains prereading, within-reading,
and postreading activities and supports designed to scaffold and assess progress toward
improving English reading comprehension and vocabulary knowledge. To support
students with decoding and fluency problems, the ULE provides TTS with synchronized
highlighting, a tool that students may use to have text read aloud at the word, sentence,
or passage level. Learners may also use TTS to have their own typed responses read
aloud.
The four narrative texts are folktale retellings, authored by members of the research
team, from different regions of the world: Mexico (Aztec folktale entitled Bird Cu), Hawaii
(Polynesian folktale entitled Why the Sun Travels Slowly Across the Sky), West Africa
(Ashanti folktale entitled Hungry Spider and Turtle), and Native America (Klamath folktale
entitled How Coyote Stole Fire). The folktales are paired with an informational text that
has some bearing on its narrative counterpart. For example, the Bird Cu folktale is paired
with an informational text called About the Aztecs. The folktale texts are structured in
a traditional, linear storybook format, and their informational counterparts function in
a fashion akin to a structured Internet Web page. Students are presented with a home
6.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
page that provides five subthemes relevant to the larger topic (e.g., The topic About
the Aztecs has five subthemes: Aztecs, The Story of a Mighty People, Aztec Religion,
Everyday Life in the Aztec Empire, and Lasting Influence). Each subtheme is linked to
a one-page fact sheet with text and relevant images. This format allows the student to
choose his or her path through the text, rather than having it presented in typical linear
format. After reading about each linked subtheme, students are prompted to apply a
relevant reading strategy, a feature common to both the narrative and informational
texts. Table 1 details the readability, word length, and genre of the various texts in the
order in which they were read.
Although the narrative texts (folktales) tend to be somewhat longer than their
informational counterparts, their readability level is lower, ranging from 4.8 for Hungry
Spider and Turtle to 6.0 for Bird Cu (the latter raised partly due to the inclusion of
complex Aztec names). Each folktale is partnered with an informational text (e.g.,
All About Spiders accompanied Hungry Spider and Turtle). The informational texts’
readability ranges from 6.3 to 7.2 and includes many science and social studies terms.
We selected texts that would be somewhat challenging for fourth graders primarily
because we were interested in learning how they would use the digital supports to
assist themselves when they encountered difficulty decoding the text, understanding
the vocabulary, and understanding the content. The nature of the embedded learning
supports is detailed next.
Text
Genre
Word Count
Readibility
Hungry Spider and Turtle
Narrative/Ashanti folktale
1,544
4.8
About Spiders
Informative
1,076
6.3
Bird Cu
Narrative/Aztec folktale
1,311
6.0
About the Aztecs
Informative
1,260
7.1
How Coyote Stole Fire
Narrative/Klamath folktale
1,219
5.4
About Coyotes
Informative
1,123
7.2
Why the Sun Travels Slowly
Across the Sky
Narrative/Polynesian
legend
2,111
5.4
About the Sun
Informative
1,127
6.5
Average narrative texts
1,546.3
5.4
Average informational texts
1,146.5
6.8
Table 1. Titles, Genre, Number of Words, and Flesch-Kincaid Readability Level for Eight ULE Digital Texts
Note: ULE= Universal Literacy Enviroment
7.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Prereading Supports: Power Words
To develop students’ vocabulary and to set the stage for their personal glossary building
that takes place as they read the text, each text begins with the introduction of five
“power words” that are important for fourth graders to know and that are important in
the text. Further, each power word has a true Spanish cognate. Students are presented
the word in English and Spanish, a brief definition, a contextual sentence, one or
two graphics illustrating the word, and an audio pronunciation of the word. Students
are prompted (a) to audio-record themselves pronouncing the word, and (b) to type
a personal association they might have with the word into a text entry box. Their
responses are captured in a work log that can be viewed at any point. Students may
click on a bilingual coaching avatar who offers one of several types of model responses.
Further the bilingual coach avatar also presents a “cognate alert,” explaining how the
target word is related to its Spanish cognate (e.g., “The Spanish word for investigate is
investigar. Do you notice that these two words look similar to each other? That means
they’re cognates: words that look and mean the same in Spanish and English!”). Once
students complete this sequence for the five power words, they begin reading the text.
Within-Reading Supports: Comprehension Strategies
and Vocabulary Development
To develop comprehension, strategy instruction prompts, hints, and models are
embedded in the digital text. At the end of each page of digital text, a student
is prompted to click on “Now would be a good time to stop and think about the
story.” Once this link is clicked, the student is given a particular strategy to apply
(summarization, prediction, clarification, questioning, or visualization) and is prompted
to provide a written or recorded response. For example, a student may be asked to
make a prediction about what will happen next in a story. A text box appears and the
student types a prediction response. If needed, he or she may click on a coach to obtain
expert models, think-alouds, and hints germane to the prompted strategy. The student’s
response is then saved to a personal work log that stores all individual responses for
both student and teacher review. For example, a strategy coach for the prediction
prompt states, “I thought about how cold it gets in the winter when the ice freezes. I
don’t see how you could live without fire, so I predicted that some humans would freeze
and have a hard winter,” followed by an appropriate model of the strategy: “I predict
that some people will freeze and have a very difficult winter.” One of the two coaches
is bilingual, and his suggestions are accessible in both English and Spanish. Figure 1
displays a screen shot of the ULE environment with explanations of available features.
Strategy support is leveled so that students move from high to low support, with the
goal of independent application of strategies. Consider the summary strategy as an
example. A student who is working in the most supported level will choose among three
prewritten summaries, one of which is more appropriate than the other two. The student
8.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
is given three opportunities to select the correct response, with feedback provided on
each selection. At a lower level of support, however, another student is simply prompted
to type his or her own summary. Students and their teachers work together in individual
conferences to review student work log responses, assess strengths and weaknesses
relative to the prompted strategies, and determine when it is appropriate to move on to
a lesser degree of support.
Various vocabulary words within each ULE text are hyperlinked so that the user may
click to learn a word’s definition and its Spanish translation and read the word in a
sentence. Students also have the option of adding any hyperlinked vocabulary word
to My Glossary. When a student selects the Add to My Glossary option after clicking a
linked vocabulary word, he or she is prompted, “Why did you choose this word for your
glossary?” The student then types a response to the question prompt. This feature is
consistent with Laufer’s (2003) work indicating that written interactions with novel words
are associated with long-term retention of word meaning. Indeed, to finish reading a
text, each student must add at least three hyperlinked words to this personal glossary.
Like the comprehension responses, the selected words and student responses are stored
in the My Glossary work log.
Postreading Supports: Retelling Activity
On completing each text, students engaged in a digitally based retelling activity.
Students were presented with eight appropriately sequenced images from the relevant
text and were required to write a description of what was occurring in the text as
represented by the image. Once all eight images had been described, the student
moved to the next screen where all eight descriptions were included in a single text box,
whereupon the student began the process of editing the document for clarity and flow.
Once the process was complete, the students completed a self-check rubric that asked
students if they had included the typical elements of story grammar in their retelling.
These elements included descriptions of the characters, setting, plot, culminating event,
and resolution.
Digital Feature Use Tracking
Laufer and Hill (2000) made the point that digital environments must track students’
online activities, noting, “If a study does not provide log files which record what learners
are doing during the reading task, there is no evidence that they indeed are looking up
unknown words, rather than guessing or ignoring them” (p. 59). Accordingly, students
working in the ULE access the system via the Internet and all student text interactivity,
including vocabulary work, strategy responses, and mouse click selections (e.g.,
selecting Spanish translations, accessing the strategy and vocabulary coach supports,
viewing hyperlinked vocabulary items, and posting vocabulary items to My Glossary) is
routed to a remote server, which saves all work in an event usage log.
9.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Figure 1. Screen capture of Universal Literacy Environment instructional reading environment.
Procedure
The teachers attended two 3.5-hour training sessions the week prior to the intervention’s
start. Training consisted of an overview of reciprocal teaching (Palincsar & Brown, 1984)
and a description of the strategies employed in that approach to teaching reading
comprehension (i.e., questioning, clarifying, predicting, and summarizing). Teachers
also worked with two additional strategies included in the ULE environment: visualizing
and feeling responses. In addition, teachers were introduced to the two work storage
databases, Work Log and My Glossary, and became familiar with the ULE environment
by working with the various texts. In this portion of the training, researchers answered
questions pertinent to working in the ULE environment so that the teachers would be
prepared for similar queries once the students began their work.
Prior to the intervention, students were administered the Gates–MacGinitie Reading
Achievement Test in English to obtain a baseline measure of reading achievement.
Once begun, the students spent 45 minutes, three times per week, for 4 weeks, totaling
12 sessions, in a computer lab where they read and worked with the narrative and
informational texts, one student per computer. During these times, the technology
teacher and one of the two coteachers were present. The adults provided technical
assistance and support when requested by the students. The teachers also consulted
with students on determining areas of strength and needed improvement and when it
was appropriate to move to a less (or more) scaffolded environment.
This was not, however, an active teaching situation. The teachers viewed the program
as a potentially useful reinforcement and practice activity to be carried out in the lab;
feeling the pressures of preparing for the upcoming state assessments and a very
10.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
full curriculum, they were reluctant to spend any time outside of the scheduled lab
sessions on students’ work with these texts. Therefore, whole-class discussion of the
texts was limited; in addition, explicit connections between the strategies being learned
in the ULE and the strategies they were teaching in their reading programs were not
made. The teachers did use their computer time to informally consult with students
to make relatively quick decisions regarding progress and required levels of support.
On completion of the intervention, students were again given the Gates–MacGinitie
Reading Achievement Test in English to obtain postreading scores.
Measures
General vocabulary knowledge.
The Gates–MacGinitie Reading Test,Vocabulary (Forms K and L), a whole-group,
timed, multiple-choice English-language assessment, was administered pre- and post
intervention as a test of the students’ vocabulary knowledge. These assessments each
consisted of 45 short clauses using an underlined target word (e.g., “a quick reply”). The
student was given four items from which a correct synonym was to be chosen. Students
had 20 minutes to complete the assessment. Test–retest reliability for pre–post testing of
the participating students was .88. Raw scores were used for all analyses.
General reading comprehension.
The Gates–MacGinitie Reading Test, Comprehension (Forms K and L), a whole-group,
timed, multiple-choice English- language assessment, was administered pre- and post
intervention as a test of the students’ reading comprehension. The assessment consisted
of 14 passages followed by a series of questions, totaling 48, designed to capture
main ideas and details described in a particular passage. Students had 35 minutes to
complete the assessment. Test–retest reliability for pre–post testing of the participating
students was .88. Raw scores were used for all analyses.
Digital feature use and student strategy and vocabulary work.
The students working with the ULE accessed the texts via the Internet. All of their
responses to the various strategy and vocabulary prompts were stored in individual work
logs. In addition, the event usage tracker logged all student text interactivity, including
vocabulary work, strategy responses, and mouse click selections (i.e., using the strategy
and vocabulary coach supports; accessing hyperlinked vocabulary items; and posting
vocabulary items to My Glossary). Feature use was tracked on a text-by-text basis,
summed across texts for a feature use total, and then divided by the total number of
texts read to establish an average feature use variable.
11.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Results
Table 2 displays the raw score means, standard deviations, and average percentile
ranking for the Gates–MacGinitie Vocabulary and Comprehension pre- and posttests,
both among the group as a whole and disaggregated by language status (ELL or EO).
Repeated measures analysis of variance for pre–post vocabulary revealed that there was
no significant growth from pre- to posttesting (F < 1); however, a significant difference
was detected between ELL and EO students, F(1, 28) = 6.59, p < .05, with no Time ×
ELL interaction (F < 1). A similar trend was revealed for pre–post comprehension scores.
No significant growth was registered from pre- to posttesting, F(1, 28) = 1.29, p = .27,
and EO students significantly outperformed their ELL counterparts on this measure, F(1,
28) = 8.25, p < .01 with no Time × ELL interaction (F < 1).
Preintervention
Raw
M
SD
M
Percentile
Postintervention
Raw
M
SD
M
Percentile
Gain
Raw
M
SD
M
Percentile
Vocabulary
Group
ELLa
27.1
8.0
23.0
27.6
7.8
25.7
0.5
6.0
2.7
23.9
6.7
13.9
24.9
7.3
16.7
1.0
4.1
2.8
EOb
30.7*
8.0
32.7
30.6*
7.5
35.3
-0.1
7.7
2.6
Comprehension
Group
ELLa
28.5
7.8
30.8
29.7
8.5
30.9
1.2
5.6
0.1
28.5
7.2
20.8
26.4
8.3
22.0
1.4
5.2
1.2
EOb
32.4*
6.8
41.5
33.4*
7.4
40.5
1.0
6.2
-1.0
Table 2: Means and Standard Deviations for Gates-MacGinitie Pre, Pos, and Gains for Reading Vocabulary and
Comprehension Assessment
Note: Results are disaggregated by language status (ELL or EO) and presented as percentile rankings.
ELL = English language learner; EO = English only.
an = 16. bn = 14.
*Represents significant differences between ELL and EO groups
The ULE digital architecture in which the texts were developed allowed us to monitor
all student–text interactivity, including the viewing of hyperlinked vocabulary items,
posting vocabulary items to My Glossary, and use of the various coach supports. These
various mouse clicks were routed to a remote server that maintained an event usage log
for each text. The records were summed across texts for a feature use total, which was
then divided by the total texts read by each student to establish a feature use average.
By taking an average feature use, we controlled for students who read more texts than
others, who would thus have been more likely to make greater use of the available
features. Table 3 details the average texts read as well as average use of the three
primary features embedded in the digital environment: strategy coach use, glossary use,
and posts to My Glossary.
12.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Table 3 displays a number of characteristics pertaining to the students’ use of the digital
environment. Students on average read approximately four of the eight available texts,
likely due to the 4-week duration of the intervention. As a group, and disaggregated
by language status, students made strongest use of the glossary feature, with lower
but comparable use of the My Glossary option and the strategy coaches. No significant
differences were found between the ELL and EO students’ use of these features,
although ELL students showed higher average use of all features, especially glossary and
coach access. Table 4 presents the correlations between these variables and sheds light
on differences between ELL and EO students’ use of these features.
Group
ELL
EO
Variable
M
SD
Min- Max
M
SD
Min- Max
M
SD
Min- Max
Texts read
4.2
1.7
1-8
4.2
1.6
2-8
4.4
1.9
1-8
Coach use
4.2
3.1
0-13.7
5.0
2.5
1.7-9.3
3.3
3.6
0-13.7
Glossary use
7.0
3.7
0-18
7.9
3.8
3.3-18
6.1
3.4
0-12.8
Glossary posts
4.3
2.2
1-8.8
4.4
2.1
2.2-8.8
4.2
2.3
0-7.3
Table 3: Average Feature Use Throughout the Intervention
Note: Average feature use was derived by summing total feature use for each student and dividing that figure
by the total amount of texts read by the student. ELL= English Language Learner; EO = English Only
1
2
3
4
5
6
7
1. Gates vocabulary time 1
-
2. Gates comprehension time 1
.69 ***
-
3. Gates vocabulary gain
- .40 *
.03
-
4. Gates comprehension gain
.19
-.23
-.31
-
5. Coach use
-.23
-.46 **
-.19
.41 *
-
6.Glossary use
-.13
-.26
.20
.17
.26
-
7. Glossary posts
-.12
-.16
.13
.25
.11
.56 ***
-
8. ELL (1=yes)
-.44 *
-.46 **
.09
.03
.27
.24
.04
8
-
Table 4: Correlations Between Pretest English Proficiency Indicators (Gates Vocabulary and Comprehension),
Gain Scores, Average Feature Use, and ELL Status
Note: ELL = English language learner.
+p < .10. *p < .05. **p < .01. ***p < .001.
ELLs accessed the available supports, particularly the coaches and the glossary, more
often than their EO counterparts (although not significantly), an encouraging sign given
the focus of the intervention. Also, on average, students who performed less well on
baseline measures of English reading comprehension and vocabulary were more likely to
access important comprehension and vocabulary supports. Although these correlations
were weak (r = –.12 to –.46), all trended inversely such that students who performed
less well on the Gates–MacGinitie reading vocabulary and reading comprehension
were, on average, more likely to access these supports. A second notable trend was
that accessing the embedded supports was positively associated with posttest gain in
13.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
vocabulary and comprehension. Again, thesecorrelations were often weak, and in one
case, negative (r = –.19–.41); however, atrend was clear, despite the small sample (n =
30). Finally, ELL status also showedweak positive correlations with feature use and gain
variables (r = .03–.27).
It is helpful to characterize these correlations through selected examples of the
participating students’ work. Jasmine (pseudonym) was an ELL student who accessed the
hyperlinked glossary items 41 times and posted 35 words to My Glossary throughout the
course of the intervention. Her glossary posts were varied and suggested surface level
(definitional), contextual (personal connections), and metacognitive processes at work.
See Table 5.
Word
Text
Strategy
Student Response
Concentrated
Hungry Spider
and Tutle
“I chose this word because I
didnt know what it ment so
when I see it again I will look it
is in my glossary”
Metacongnitive
Exhausted
Hungry Spider
and Turtle
“when you are exhausted is
Surface level
when you feel tired, weak and
you dont want to do anything”
Flexibility
About the
Aztecs
“I choose this word because
I also have alot of flexibility
because I go to karate”
Contextual
Table 5: Selected Words and Responses From the “My Glossary” of Jasmine, a Spanish Speaking ELL
Note: ELL = English language learner.
On average, then, individual students who posted strong comprehension gains appear
to have accessed the strategy coach with greater frequency than those with weaker
comprehension gains. María (pseudonym) accessed strategy coach support 32 times
throughout the course of the intervention. Her clarification strategy responses seemed
particularly targeted toward trying to make sense of the various texts. She also made use
of sentence starters (e.g., “A confusing part of the passage …”) that were only available
by accessing strategy coaches (see Table 6).
Kathy (pseudonym) was another ELL student whose comprehension gains were
impressive (28th percentile to 48th percentile). Although she accessed the strategy
coaches only 11 times, she was quite active with vocabulary, checking word meanings
25 times and posting 17 words to My Glossary over the course of the intervention.
This combination of reasonable strategy support alongside strong vocabulary access is
readily apparent in her elaborate and varied strategy responses (see Table 7).
14.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
Text
Strategy
Student Response
Hungry Spider and Tutle
Clarifying
“A confusing part of the passage is why
did the spider toke of is coat”
Bird Cu
Clarifying
“A confusing part of this passage is
whydoes the eagle wants bird cu be
the messenger”
About the Aztecs
Clarifying
“A confusing part is why do they make
mask”
Table 5: Selected Words and Responses From the “My Glossary” of Jasmine, a Spanish Speaking ELL
Note: ELL = English language learner.
Text
Strategy
Student Response
Hungry Spider and Tutle
Predicting
“I think the spider will start being selfish.
I think Ashantis trible will find a lots of
food and spider will ask the tribe for
food”
Bird Cu
Feeling
“I feel sad for Bird Cu and owl becaus
eagle had told Bird Cu and owl that
they would become night birds. If
I were them I would feel ashamed
at eagle and the beautiful birds for
sending away Bird Cu and owl”
Bird Cu
Clarifying
“A confusing part of this passage is
how does birdCu loses her feathers. A
confusing word in this passage is the
word reunin”
About the Aztecs
Vizualizing
“When I think of barefoot I think of
a monkey barefooting through the
jungle”
Table 5: Selected Words and Responses From the “My Glossary” of Jasmine, a Spanish Speaking ELL
Note: ELL = English language learner.
Discussion and Conclusion
In recent years, the proportion of immigrant students—particularly Latino students—
in U.S. schools has increased dramatically. In 2001, Hispanics represented 14.9%
of total enrollment in elementary school and 16.7% in kindergarten (Honor, 2001).
Hispanic students are the largest non-English-speaking group in U.S. schools (Tabors,
Páez,&López, 2003) and have the lowest attainment and achievement rates of all ethnic
and racial groups in the United States (NCES, 2003).With the increased literacy demands
being placed on all children, it is profoundly important that new technologies be
focused on reading and writing environments that support children whose needs differ
from average in the population, especially ELLs.
15.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
With this study, we began a line of inquiry into using universally designed digital
narrative and informational texts to support all students, including English learning
students, and their teachers, in using research-based methodologies for enhancing
vocabulary and comprehension outcomes. The ULE environment appears well
suited for both Spanish-speaking ELLs and struggling readers. Correlational analyses
indicated that the use of comprehension-based embedded supports (e.g., the strategy
coaches) was associated with pre–post comprehension gain, and that preintervention
comprehension was negatively associated with strategy coach access, suggesting
that less skilled readers were more likely to access those coaching supports. Indeed,
analyses of individual student responses suggested that participants who made use of
the embedded supports appeared to be interacting meaningfully with the texts. These
qualitative views reveal students responding to the vocabulary and comprehension
activities in a way suggesting the potential of this ULE to affect students’ application of
cognitive strategies to improve word learning and comprehension.
We find it encouraging that the students in this study chose to take advantage of the
vocabulary and strategy supports and in fact accessed supports at a higher level than
previously reported in the literature, especially for struggling learners (Anderson- Inman,
Horney, Chen, & Lewin, 1994; Horney & Anderson-Inman, 1999; van Daal & Reitsma,
1993). We believe a contributing factor was our intentional embedding of a meaningful
purpose for accessing the supports. For example, the requirement to add a minimum of
three words to My Glossary for each text read resulted in frequent clicking on vocabulary
hyperlinks as students considered various words for inclusion. On average, students
added 4.3 words per text, more than was required, despite the fact that adding a word
to their glossary also entailed writing an explanation for why they chose that particular
word. This phenomenon speaks to the issue of “pushing” and “pulling” support to
students in digital environments. Requiring that at least three words per text be added
to My Glossary was an example of “pushing” supports to the students. The fact that the
students, on average, added more than a full word per text than was required is a prime
example of students “pulling” what they apparently perceived to be an important and
interesting feature in the service of their own word learning and text comprehension.
Further, students’ willingness to access the strategy coaches might have been due to
the coach’s presence at the point of use (i.e., students were prompted to construct a
strategy response for each screen). Students were also provided a hint, a think-aloud,
and a model response (at the higher levels of scaffold) to guide them in constructing
their responses. Embedded supports and help features are a characteristic of many
information communication technologies (Reinking, 1988; Strangman & Dalton, 2005);
thus, it will continue to be important to integrate measures of students’use of supports
in studies of student learning in these environments (Laufer, 2003). Such integration
will ensure the design of more effective learning environments and better prepare
students to use thevarious supports available in digital texts strategically and in service
of their own learning goals. We believe that some supports should be “pushed” at
16.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
students, especially during the introductory stage when they are learning how to use the
support system to their best advantage.However, given that choice is key to engaged
learning and the development of strategic learners, we assume that the “pulling” of
supports represents a type of self-scaffolding and is a necessity in customizable, digital
environments.
Some limitations of this study have implications for future research in this area. The
small number of participants, lack of a control group, and relatively short duration of
the intervention were obvious deterrents to being able to draw causal connections
between working in the ULE environment and literacy gains. Future research in this area
would target larger sample sizes with randomized assignment designs and increased
intervention times to verify if the patterns detected here indeed result in increased
achievement for struggling and English learning readers.
Perhaps not surprisingly, implementation was challenging and highlighted the
importance of teacher investment in implementing any curricular intervention. The
intervention teachers’ view of the software as a stand-alone program that would provide
their struggling readers opportunities to read with individualized support meant that
offline instruction was limited. Although understandable, given the teachers’ pressure
to prepare for upcoming state testing, this implementation was likely to curtail the
effectiveness of this type of digital reading environment. In our ongoing research, we
are focusing on how to provide sustained professional development and support for
teachers as they implement technology-based instructional approaches. Additionally,
better measures of student engagement, motivation, and self-efficacy, which are
sensitive to changes over time, are needed in research intervention studies such as
these. Our classroom observations and the feature-use data suggest high levels of
student interest and effort in the ULE environments. However, we need studies that
systematically investigate cognitive and affective processes, with diverse students
reading and learning from a range of digital texts, for a variety of purposes and tasks.
A final limitation was that only English language data were gathered on students’
reading achievement. Future research with larger samples should be careful to gather
bilingual students’ full complement of literacy skills, including L1 proficiency and both
oral as well as reading measures. There is growing evidence that comprehensionrelated skills have a degree of commutability between orthographically comparable
languages, such as Spanish and English (see, e.g., Proctor et al., 2006). Thus, baseline
data collection on bilingual students who participate in interventions such as these will
not only serve further study of cross-linguistic transfer, but also the more ethical ideal
of closing the achievement gap through the promotion of improved outcomes for all
learners.
Some might argue that digital support features, such as animated coaches or dramatic
graphics, could function as seductive details, drawing the learners’ attention away from
the core content, and thereby interfere with productive learning (Garner, 1992). Labbo’s
(1996) analysis of popular interactive storybooks for young readers supports this view;
17.
Scaffolding English Language Learners and Struggling Readers in a Universal Literacy
Enviroment With Embedded Strategy Instruction and Vocabulary Support
including animation and sound effects that did not contribute to understanding the story
line were not facilitative of students’ comprehension, and did draw students’ attention
and time away from productive learning. We need studies that systematically investigate
cognitive and affective processes and outcomes over time, with diverse students reading
and learning from a range of digital texts, for a variety of purposes and tasks.
One final area of future research concerns the distinctive comprehension demands of
reading in informational versus narrative format (Duke, 2004). Studies of digital reading
environments should seek to investigate the similarities and differences between the
appropriateness and application of the various strategies modeled here in these two
very different text genres. This study did not seek to answer this question, but surely
students’ comprehension varied as a function of the different demands of the text genre.
Future research should endeavor to determine whether traditional comprehension
strategies are indeed the most effective way to promote comprehension in Web-based
learning environments.
The ULE environment also has important implications from a new literacies approach
to learning (Leu, Kinzer, Coiro, & Cammack, 2004). A number of researchers have
indicated that technology use is perhaps one of the most important new educational
frontiers for working with struggling readers and ELLs (see, e.g., Alvermann, 2002;
Jiménez, 2003; Rose & Dalton, 2002; Strangman & Dalton, 2005). Giving children
access to the variedways of knowing provided in digital environments may require
higher level information-processing skills, synthesizing in distinct modalities (text,
image, video, etc.) and within nonlinear hypertext structures, and a more fundamental
experience with information presentation (tabular vs. text) and general familiarity with
computer interfaces. Finally, there is the heightened strategic challenge of learning
how to negotiate meaning within digital environments that offer varied types and levels
of support. Guided by a UDL instructional framework (Rose & Meyer, 2002) and our
previous research on universal literacy environments (Dalton et al., 2002; Strangman &
Dalton, 2005), we revised our ULE prototype to more strongly address the vocabulary
needs of ELLs and struggling readers. This study, although limited in scope, suggests the
value of scaffolded digital literacy environments and highlights the need for continued
research and development in the service of improving literacy and learning outcomes for
all students.
Acknowledgments
This study was supported by a grant from the William and Flora Hewlett Foundation. We
thank the school principal, teachers, and students for their participation in the project,
as well as Evangelina Bustamente-Jones for her assistance with data collection, and
Kristin Robinson and Tom Green for their contribution to the development of the ULE
prototype. We also thank advisors María Brisk, Catherine Snow, María Carlo, and Diane
August for their feedback and guidance on developing an effective reading environment
for ELLs.
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Enviroment With Embedded Strategy Instruction and Vocabulary Support
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