Effects of Interactive Vocabulary Instruction on the Vocabulary Learning and Reading Comprehension of Junior-High Learning Disabled Students

Hammill Institute on Disabilities

Effects of Interactive Vocabulary Instruction on the Vocabulary Learning and ReadingComprehension of Junior-High Learning Disabled StudentsAuthor(s): Candace S. Bos and Patricia L. AndersSource: Learning Disability Quarterly, Vol. 13, No. 1 (Winter, 1990), pp. 31-42Published by: Sage Publications, Inc.Stable URL: http://www.jstor.org/stable/1510390 .

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EFFECTS OF INTERACTIVE VOCABULARY INSTRUCTION ON THE VOCABULARY

LEARNING AND READING COMPREHENSION OF JUNIOR-HIGH

LEARNING DISABLED STUDENTS

Candace S. Bos and Patricia L. Anders

Abstract. Drawing upon theory-driven vocabulary instruction and the vocabulary- reading comprehension connection, this study compared the effectiveness of three interactive vocabulary strategies derived from the knowledge hypothesis with definition instruction derived from the access and instrumental hypotheses. Subjects were 61 learning disabled junior-high students. Using content-area texts, students participated in one of three interactive strategies - semantic mapping (SM), semantic feature analysis (SFA), and semantic / syntactic feature analysis (SSFA) - or in definition instruction (DI). Learning was measured both at short and long term by vocabulary and comprehension multiple-choice items and written recalls. Results from the multiple-choice items suggested that students participating in the interactive strategies demonstrated greater comprehension and vocabulary learning than students receiving definition instruction. Results of the written recalls indicated qualitatively and quantitatively greater recalls at long term for students in the SFA and SSFA conditions compared with the DI condition. Implications for research and practice are discussed.

Much current reading research and theory support reading as an interactive process: The reader is characterized as an active participant who inter- acts with the text to construct meaning. From this perspective, the reader uses prior knowledge as a framework to negotiate the meaning of the text (Rumelhart, 1980). One of the most important as- pects of this prior knowledge is the reader's labels for experiences or vocabulary knowledge (John- son & Pearson, 1984). Early factor-analysis (e.g., Davis, 1944, 1972) and correlational studies (e.g., Farr, 1969) highlighted the positive relationship between vocabulary knowledge and reading comprehension. Stahl and Fairbanks (1986) conducted a meta-analysis of studies concerned with the effects of vocabulary instruction on comprehension and found a significant effect size for both comprehension of passages containing the vocabulary

and for global measures of comprehension. Building upon the work of Anderson and Free-

body (1981), Mezynski (1983) suggested four hypotheses that may explain the relationship between vocabulary and reading comprehension. One hypothesis, the aptitude hypothesis (e.g., Hunt, 1978), purports that the relationship between vocabulary and reading comprehension is based on the reader's underlying verbal ability and implies that this aptitude is relatively immutable.

CANDACE S. BOS, Ph.D., is Associate Professor of Special Education, University of Arizona.

PATRICIA L. ANDERS, Ph.D., is Associate Pro- fessor of Language, Reading, and Culture, Univer- sity of Arizona.

Volume 13, Winter 1990 31



A second hypothesis, the instrumental hypothesis, assumes that knowledge of individual word meanings is the major factor related to reading comprehension. Therefore, increasing word knowledge by direct teaching of word meanings (cf. Becker, 1977) would directly increase reading comprehension. According to the third hypothesis, the access hypothesis, vocabulary knowledge is related to the reader's ability to access word meanings and use those meanings in text processing. This hypothesis draws heavily upon notions of automaticity of word knowledge (LaBerge & Samuels, 1974; Lesgold & Perfetti, 1978). Instructional implications of this hypothesis would emphasize automatic decoding and definition generation through systematic practice. The fourth hypothesis, the knowledge hypothesis, assumes that vocabulary terms are surface representations of underlying concepts represented in the reader's knowledge structures or schemata (Anderson & Freebody, 1981). Instruc- tionally, the knowledge hypothesis would imply that to teach vocabulary, one must teach the underlying concepts and their relationships to one another.

An instructional intervention can be generated by combining the instructional implications from the access and instrumental hypotheses whereas a contrasting intervention can be generated from the instructional implications of the knowledge hypothesis. Specifically, an access / instrumental intervention would focus on definition instruction highlighting student learning of the vocabulary and the related definitions to develop easy access, while a knowledge-based intervention would focus on the importance of activating student background knowledge and developing conceptual understanding and semantic relationships among the vocabulary.

The purpose of this investigation was to com- pare the effectiveness of two types of theoretically based vocabulary instruction: (a) interactive vocabulary instruction based on principles of the knowledge hypothesis and (b) definition instruction based on the access/instrumental hypotheses using junior-high students identified as learning disabled studying science text. This population was selected for two reasons.

First, these students have been characterized as not spontaneously generating vocabulary knowledge (Simmons & Kameenui, 1988) and not spontaneously employing comprehension and comprehension-monitoring strategies (Bos & Filip,

1984; Wong, 1980). Second, previous vocabulary research with learning disabled students (Bos, Anders, Filip, & Jaffe, 1989; Pany & Jenkins, 1978; Pany, Jenkins, & Schreck, 1982) has resulted in conflicting findings in terms of the effects of vocabulary instruction on reading comprehension. Bos et al. (1989) compared semantic feature analysis, a knowledge-based instruction, to a dictionary method (Gipe, 1978-79) and found that the interactive instruction resulted in greater reading comprehension and vocabulary learning. In contrast, Pany et al. (1982) compared instrumental hypothesis-based instruction to a no-instruction control condition with learning disabled students. While vocabulary learning was facilitated by the instruction, comprehension, as measured by oral retellings and cloze tests of constructed stories using the vocabulary, was not facilitated. The only comprehension measure that demonstrated instructional effects was one that required students to answer factual questions containing the vocabulary words.

The current study directly compared knowledge-based and instrumental/ access-based vocabulary instruction on learning disabled students' reading comprehension. Specifically, this study compared the effectiveness of three knowledge- based interactive vocabulary strategies - semantic mapping, semantic feature analysis, semantic / syntactic feature analysis --with an access/ instrumental-based instruction (definition instruction) on the vocabulary learning, reading comprehension, and quality of written recalls of junior- high learning disabled students learning from science text.

METHOD Subjects

Subjects were 61 learning disabled (LD) students recruited from middle- and lower-middle class junior-high schools in two school districts in a large, metropolitan area in the Southwest. The 41 males and 20 females had been identified as learning disabled and were receiving services in either resource or self-contained settings. Eligibility criteria included the presence of a severe dis- crepancy between intellectual functioning and one or more academic areas and evidence of one or more deficits in cognitive processing. These learning problems could not be primarily related to ex- clusionary factors. Subjects were further defined by the researchers as having at least normal in-

32 Learning Disability Quarterly



Table 1 Means and Standard Deviations for Student Characteristics (N= 61)

Characteristics Mean Standard Deviation

Age 13.80 .93

Full-Scale IQ 91.97 8.95

Verbal IQ 88.67 10.05

Performance IQ 98.00 10.65

Reading Achievement 81.30 11.20 (Woodcock-Johnson)

Prior Knowledge of Topic 13.31 2.84 (Total Possible = 30)

Prior Interest in Topic 22.90 7.69 (Total Possible =35)

telligence as indicated by either verbal, performance, or full-scale IQ standard scores of at least 85 and reading identified as a remediation focus. Subject characteristics are presented in Table 1.

Students were randomly assigned to one of four intervention conditions and instructed in groups of 6 to 12. Analyses of variance on the student- characteristic data revealed no significant differences among the conditions. Materials

Assessment materials. To measure learning, a 30-item multiple-choice test for the experimental passage and a similar test for the practice passage were developed. Test construction was based on content analyses of the passages (Frayer, Fred- erick, & Klausmeier, 1969), and each test consisted of 15 vocabulary and 15 comprehension items. The vocabulary items measured students' knowledge of the context-related meanings of the vocabulary presented in the passage; the comprehension items, in turn, measured students' understanding of the passage or their ability to apply the concepts presented to novel situations. Each item on the objective test offered five options,

with the correct choices balanced across the test. To determine students' prior knowledge as re-

lated to the experimental passage, a prior-knowledge assessment was constructed using the 30 items from the experimental passage test and 10 items from the practice passage test (serving as dis- tractors). A 7-item topic interest inventory ascer- tained students' prior interest in the topic. Each item represented a superordinate or coordinate concept presented in the experimental passage. Students rated each statement on a 5-point Likert scale measuring their interest in learning about it.

Instructional materials. The instructional reading materials consisted of a practice and an experimental passage. Passages were selected from text and trade books used in junior-high science classes. The experimental passage was a 1,300-word passage on the topic of fossils with an estimated fifth- to sixth-grade readability level (Fry, 1977). The passage's text structure was mixed, beginning with a narrative about a young boy who is interested in fossils and becomes a geologist. Within the narrative, information about fossils is provided. After the narrative introduction, the




structure switches to descriptive expository. The practice passage, on the topic of forming ice, was of similar length and readability utilizing a comparison / contrast text structure.

The concept-related vocabulary from the reading passages served as the instructional focus for the four intervention conditions. The concept-related vocabulary was selected using the same content analysis as for the test construction. Context- grounded definitions were generated and verified by content experts. For the definition instruction condition, the instructional materials consisted of a written list of the vocabulary and definitions. For the semantic mapping condition, instructional materials consisted of a written list of the vocabulary used by the teacher and students to generate a semantic map (Pearson & Johnson, 1978). The map was a visual representation of the vocabulary and the relationships among the different vocabulary. A relationship matrix (Anders & Bos, 1986; Johnson & Pearson, 1984) was constructed for use in the semantic feature analysis condition. To prepare the matrix, vocabulary representing the superordinate concept served as the title, with vocabulary representing the coordinate concepts placed along the top of the matrix, and the vocabulary representing the subordinate concepts along the side. For the semantic-syntactic feature analysis condition, cloze-type sentences were written based on the matrix. Both the relationship matrix and the sentences were used during this instructional condition. Procedures

Five researchers served as teachers. All were trained in the instructional interventions used in the study and randomly assigned to instructional groups with each researcher teaching at least two different conditions and groups.

Intervention consisted of eight 50-minute sessions over a span of approximately seven weeks. First students were given the prior-knowledge test and topic interest inventory. Two weeks later, students and their assigned researcher participated in three 50-minute practice sessions followed approximately two weeks later by the three 50- minute experimental sessions. Finally, four weeks later an additional session was held to collect the follow-up measures.

During the first day of both the practice and the experimental sessions, students were introduced to the study whereupon they completed a pre- reading activity designed around their instructional

intervention. The definition instruction (DI) activity consisted of directly teaching the definitions of the vocabulary terms (Engelmann & Carnine, 1982; Pany et al., 1982). The method emphasizes oral recitation, correct and automatic pronunciation of each vocabulary word or phrase, and memoriza- tion of concise context-related definitions. The vocabulary was learned and reviewed in groups of five with initial intensive practice followed by spaced practice and review. The three interactive conditions employed interactive, discussion-ori- ented strategies (Bos & Anders, in press) designed to assist students in activating prior knowledge, in- stantiating knowledge, and predicting and drawing relationships among the concepts. For the semantic mapping (SM) condition, the researcher and students constructed a hierarchical relationship map from the vocabulary list. In the semantic feature analysis (SFA) and the semantic/syntactic feature analysis (SSFA) conditions, the researcher and students predicted the relationships among concepts using the relationship matrix. The researcher and students in the SSFA condition also predicted the answers for the cloze-type sentences using their matrix as a guide.

During the second day of instruction, the researcher and students set purposes for reading according to their instructional intervention and students then read the passage. After reading, the researcher and students met as a group in a postreading activity and again discussed their matrix and maps or practiced and reviewed the vocabulary and their definitions. During this time, students were encouraged to use the text to confirm definitions and / or relationships.

On the third day of instruction, students were given 10 minutes with their instructional aide (definitions, map, matrix, or matrix and sentences) to study for the posttest. They were then instructed to complete written recalls by writing "all you know about the topic" of the passage including what they read, what they learned during instruction, or other information they knew about the topic. Stu- dents were instructed that they would not be judged for spelling or grammar, but on the content. Twenty minutes were provided for writing, whereupon the multiple-choice test was administered. To measure long-term learning, students again completed written recalls and the objective test four weeks later. Data Scoring

Each objective test item was computer scored as correct or incorrect, and a vocabulary score and




a comprehension score were computed for each student.

The written recalls were scored using a variety of procedures. First, they were analyzed for the vocabulary used in the recall. A list of text-related vocabulary was generated using the list of instructional vocabulary, their corresponding definitions, and the content words from the passage. With this list as a template, each recall was scored for the number of text-related vocabulary. Content words in the student recalls that were not text-related were scored as either student-relevant vocabulary or student-irrelevant vocabulary.

Second, the conceptual units recalled were analyzed and tallied. Conceptual units, adapted from Frederiksen's (1975) propositional analysis, were defined as ideas that convey meaning. For example, in the sentence, "Fossils can be bones from animals who lived long ago," three conceptual units are present (i.e., fossils can be bones; bones are from animals; animals lived long ago). Similar to the vocabulary scoring, each conceptual unit was scored as text-related, student- relevant, student-irrelevant, or student-inaccurate. A conceptual unit was judged as inaccurate if it could be directly disproven by the text or instructional materials.

It was hypothesized that, compared to their peers, students who received interactive instruction would integrate more elaborated prior or scriptal knowledge into their written recalls since these teaching strategies emphasized the activation of prior knowledge (Anders & Bos, 1986). To in- vestigate this hypothesis, the student-relevant conceptual units were analyzed for quality of scriptal knowledge generated. This quality rating was ob- tained by first counting the number of student- relevant conceptual units. To ascertain quality, each unit was categorized as elaborate, specific, or restrictive. This categorization was adapted from Langer (1982): elaborate scriptal knowledge represented creative extensions, linkings, analog- ies, definitions, enriched information, or a predic- tion regarding propositions in the text (e.g., "Fossils are the blueprints of ancient life."); specific scriptal knowledge included attributes, describing characteristics, examples, processes or actions specific to one proposition (e.g., "Fossils are big or small."); and restrictive scriptal knowledge contained very limited information (e.g., "Fossils can be very small"). Based on both the amount and type of scriptal knowledge integrated into the written

recall, an overall quality rating from 0 to 3 was assigned, with 3 representing the richest use of scriptal knowledge. Finally, a holistic rating was generated using a 6-point scale ranging from 0 to 5 (Irwin & Mitchell, 1983).

Written recalls were analyzed and scored by trained scorers knowledgeable in discourse analysis. For each score, the scorers were trained until a .85 reliability level was reached. After initial scoring, a second scorer randomly selected and scored 15% of the scored recalls. Reliabilities for the different scores ranged from .86 to .97. The exception to this scoring scheme was the holistic rating. In this case, holistic scoring procedures were used (Cooper, 1977; Myers, 1980), including selection of anchored recalls, training of raters, and multiple ratings of each recall. Data Analysis

Data were analyzed to determine the short- and long-term learning effects of the four instructional conditions on LD students' learning using a 4 x(2) mixed design (Lindquist, 1953). With the four instructional conditions as the between factor, time of the test (posttest and follow-up) served as the within factor. The score for the experimental passage items on the prior-knowledge assessment, the score for the topic-interest inventory, and the full-scale IQ standard score (see Table 1) served as covariates in the analyses. These three factors were selected due to their theoretical linking to the dependent measures (Anderson, Reynolds, Schal- lert, & Goetz, 1977; Osako & Anders, 1983; Tor- gesen, 1987).

RESULTS Covariates

The role the covariates played in each analysis varied across the reading test and the written recalls. Although prior knowledge served as a significant covariate for both the vocabulary score, F (1, 54) = 20.43, p < .001, and the comprehension score, F(1, 54) = 20.00, p < .001, on the reading test, prior knowledge was not a significant covariate in any of the written-recall analyses. Prior interest in the topic and IQ were not significant covariates in any of the analyses associated with either the reading test or the written recalls. Reading Test

Results from the reading test were analyzed for both the vocabulary and the comprehension score. The adjusted means and standard deviations at posttest and follow-up for both scorers are pre-




sented in Table 2. Vocabulary. For the vocabulary score, results

of the main-effect tests indicated a significant effect for condition, F(3, 54) = 5.37, p < .003, and for time, F(1, 57) = 59.97, p < .001. A significant interaction between condition and time also resulted, F(3, 57) = 5.88, p < .002. Post-hoc analyses using the Tukey method (Glass & Hop- kins, 1984) with a pooled error term (Kirk, 1968) and a critical alpha level of .05 showed that at posttest students participating in the SFA and SM instructional conditions had learned more vocabulary than participants in the DI condition. In terms of long-term learning (follow-up test), students in the three interactive instructional conditions out- performed subjects receiving definition instruction. Neither short- nor long-term learning showed differences among the three interactive instructional conditions.

Comprehension. Results for the comprehension items were similar, with both the main-effect

tests for condition, F(3, 54) = 6.29, p < .001, and time, F(1, 57) = 17.66, p < .001, being significant. Although the interaction followed the pattern of the vocabulary scores, it was not significant, F(3, 57) = 2.69, p < .06. At posttest, post-hoc analyses indicated that students in the interactive conditions scored significantly higher than students in the definition instruction condition. At follow-up, students in the SSFA condition scored significantly higher than those in the DI condition. Neither at posttest nor follow-up were there differences among the three interactive instructional conditions. Written Recalls

Data related to the written recalls were analyzed using the same design as for the reading tests. Ad- justed means and standard deviations for the relevant vocabulary generated and the relevant conceptual units are presented in Table 3; adjusted means and standard deviations for the scriptal- knowledge quality rating and holistic rating are shown in Table 4.

Table 2 Adjusted Means and Standard Deviations for the Reading Test Vocabulary and Comprehension Scores (N = 61)

Definition Semantic Semantic Semantic, Instruction Mapping Feature Syntactic

Analysis Feature

Analysis (n = 11) (n = 19) (n = 17) (n = 14)

Vocabulary

Posttest 8.02 10.58 10.66 9.46 (2.6) (1.5) (2.4) (1.8)

Follow-Up 5.93 8.11 7.72 9.25 (2.8) (1.9) (2.5) (1.9)

Comprehension

Posttest 7.46 9.98 10.60 10.14 (2.2) (1.6) (2.0) (2.2)

Follow-Up 6.92 8.09 8.19 9.79 (2.1) (2.6) (3.2) (1.9)




Table 3 Adjusted Means and Standard Deviations for the Relevant Vocabulary and Relevant Conceptual Units Generated on the Written Recalls (N = 61)

Definition Semantic Semantic Semantic / Instruction Mapping Feature Syntactic

Analysis Feature

Analysis (n = 11) (n = 19) (n = 17) (n = 14)

Relevant Vocabulary

Posttest 22.25

24.82 19.77 22.97

(13.8) (8.6) (6.9) (6.4)

Follow-Up 6.25 11.35 14.30 16.83 (5.0) (5.0) (6.3) (6.2)

Relevant Conceptual Units

Posttest 17.74 19.83 15.27 17.82

(15.7) (8.6) (8.1) (7.1)

Follow-Up 2.56 9.04 9.98 13.46

(2.7) (5.5) (5.4) (6.1)

Vocabulary generated. The recalls were analyzed in terms of the relevant vocabulary generated including the text-related vocabulary and the student-relevant vocabulary. The irrelevant vocabulary was also scored but not analyzed be- cause the instances of irrelevant vocabulary in the written recalls averaged less than one per written recall.

Results of the analysis revealed significant effects for time, F(1, 57) = 108.92, p < .001, and the interaction, F(3, 57) = 6.96, p < .001, between condition and time. Post-hoc analyses on the adjusted means (see Table 3) indicated that although differences were not evident among the four instructional conditions immediately following instruction, a month later students in the DI condition generated significantly less vocabulary than students in either the SSFA or SFA conditions. No statistical differences were evident among the three interactive conditions.

Conceptual units. Recalls were also analyzed

for the relevant, accurate conceptual units generated, including the concepts that were represented in the instructional materials and text and those that were generated by the student. Student-irrelevant conceptual units and student-inaccurate conceptual units were not analyzed, since the number of occurrences per written recall averaged less than one.

The main-effects tests showed a significant dif- ference across posttest and follow-up, F(1, 57) = 63.73, p < .001, as well as a significant interaction, F(3, 57) = 4.61, p < .006. Like the vocabulary generated, post-hoc analyses of the adjusted means (see Table 3) revealed no significant dif- ference among the four instructional conditions at posttest. At follow-up, the findings also paralleled the findings for relevant vocabulary generated. The SSFA and SFA students generated significantly more conceptual units than subjects in the DI condition. No differences were evident among the three interactive conditions.




Scriptal knowledge. Based on the interactive model, it was predicted that the quality of scriptal knowledge would be higher for students participating in the interactive strategies. The quality of scriptal knowledge in the student retellings was as- certained by assigning an overall quality rating based on the amount and type of scriptal knowledge generated: elaborate, specific, or restrictive.

Although a significant effect was not evident for condition, there was a significant effect for time, F(1, 57) = 11.60, p < .001, and for the interaction of condition and time, F(3, 57) = 3.45, p < .05. Post-hoc analyses for the adjusted means (see Table 4) indicate that no differences were evident among the groups on the ratings measuring short-term learning. However, for long-term learning, students in all three interactive conditions generated a higher quality of scriptal knowledge in their recalls than students in the DI condition. No differences emerged among the interactive strategies.

Holistic rating. The same pattern is evident with regard to the traditional holistic rating (see Table 4), with a significant effect for time, F(1, 57) = 65.03, p < .001, and for the interaction, F (3, 57) = 4.34, p < .005. According to post-hoc analyses, no differences were found among the four conditions at posttest. However, at follow-up students participating in the SSFA and SFA conditions generated significantly higher holistic ratings than DI students. No differences were evident among the interactive conditions.

DISCUSSION Previous research with learning disabled

students has resulted in conflicting findings with regard to the vocabulary-comprehension connection. Instrumental/ access-based interventions (Pany et al., 1982) have not demonstrated a clear effect on reading comprehension compared with a no-instruction control condition; however, interactive or knowledge-based interventions (Bos et

Table 4 Adjusted Means and Standard Deviations for the Quality of Scriptal Knowledge and the Holistic Rating of the Written Recalls (N-= 61)

Definition Semantic Semantic Semantic / Instruction Mapping Feature Syntactic

Analysis Feature

Analysis (n = 11) (n = 19) (n= 17) (a = 14)

Quality of Scriptal Knowledge

Posttest 1.78 2.18 1.68 1.75

(1.0) (1.1) (1.2) (1.2)

Follow-Up .33 1.44 1.56 1.61 (.6) (1.0) (1.3) (1.1)

Holistic Rating

Posttest 5.27 6.20 5.17 5.44 (2.9) (1.9) (2.1) (1.9)

Follow-Up 1.73 3.62 4.11 4.09 (1.5) (1.9) (2.2) (1.5)




al., 1989) have led to greater comprehension than a dictionary method of teaching vocabulary. The current study compared an instrumental/ access- based intervention with three knowledge-based interventions.

The results of the reading test and more specifically the comprehension items indicate that students in the interactive interventions scored higher than students engaged in definition learning.' These findings parallel the conclusions drawn by Stahl and Fairbanks (1986) in their meta-analysis of vocabulary instruction. They concluded that the instructional methods producing higher comprehension effects involved students in deeper processing of definition and contextual information and provided students more than one or two ex- posures to the to-be-learned words.

Comparison of the definition instruction and the interactive instruction reveals clear differences among the methods in terms of depth of processing and use of definition and contextual information. Definition instruction focused on correctly pronouncing the vocabulary and accurately mem- orizing content-related definitions of the words, more indicative of surface processing. In this instructional condition students were not encouraged to "think about7 how the vocabulary related to their current understanding or how the concepts might be related one to another. Each vocabulary/ definition was taught as a separate piece of information (except that students were told they all related to the superordinate concept of "fossils"). Students were left to infer the relationships among the vocabulary and their prior knowledge. In contrast, the interactive interventions highlighted the semantic relationships among the vocabulary and encouraged students to "think about" what they already knew about the concept.

Differences are also evident in terms of the type of information highlighted. Definition instruction emphasized relatively context-free definitions. Even though each definition was content-related, it did not provide a rich context for the definitional information. This finding is again consistent with Stahl and Fairbanks' (1986) meta-analysis. These authors noted that methods providing only definitional information did not produce reliable effects on comprehension. In contrast, the interactive strategies highlighted contextual information. Through discussion, students were encouraged to activate, share, and elaborate on their prior knowledge concerning the vocabulary, thereby provid-

ing a context within which to predict definitions and provide definitional information.

Results from the written recalls demonstrated a consistent pattern across the various measures, but this pattern was not congruent with the results of the reading test. For the written recalls, differences among the four instructional conditions were not evident when the students were asked to write on the day following instruction. However, one month later, students in the semantic feature analysis and semantic/syntactic feature analysis conditions performed significantly better than students in the definition instruction condition on vocabulary generated, conceptual units generated, and the holistic rating. For the quality of scriptal knowledge used in the follow-up recall, all three interactive conditions resulted in a higher quality of recall compared to definition instruction.

One explanation for the lack of differences in short-term recall between the access/instrumental-based instruction and the knowledge-based instruction may be the nature of written recalls. Most studies with elementary and middle-school students have employed oral retellings (e.g., Adams, Carnine, & Gersten, 1982; McKeown, Beck, Omanson, & Pople, 1985; Pany et al., 1982), requesting students to retell what they just read. One exception was a study of fifth graders (Wixson, 1986) whose findings were similar to those of the present investigation; differences were evident among the vocabulary-instruction methods for the measure employing comprehension questions but not for the written recalls. The present study not only employed written recalls but also gave students more latitude to utilize a variety of information including "information you have read about, we have talked about, and other information you may know about the topic" Such broad directions may have served as a cueing device for students in the definition-instruction condition, thereby stimulating recalls that mirrored those provided by students in the interactive instructional conditions.

At follow-up, results suggest that the quality of the recalls decreased, but that the decrease dif- fered across the instructional conditions. The recalls reflect a higher quality of long-term learning for students in the instructional conditions that employed a relationship matrix compared to definition instruction. The use of the matrix guided the students and teacher to discuss, predict, and confirm the definition for each vocabulary and the




relationship of each coordinate concept with each subordinate concept. Such systematic discussion utilizing student background knowledge and text information may be particularly fruitful in terms of generating long-term learning.

Instructionally, this study lends support to the notion that rich, elaborated vocabulary instruction based on implications from the knowledge hypothesis can facilitate reading comprehension for learning disabled students. Such findings hold implications for practitioners and researchers alike. From a practitioner orientation, this study and those described in the Stahl and Fairbanks (1986) meta-analysis and the Weisberg (1988) review challenge the use of practices that focus on teaching definitions isolated from content-area context. Learning, especially long-term learning, seems to occur under conditions that provide adequate op- portunities for students to (a) activate and instan- tiate prior knowledge, (b) share that knowledge with each other, (c) make predictions concerning the relationships among concepts, and (d) read to confirm and justify their predictions. If new learning is based on old learning, it is imperative that practitioners consider the curriculum available to students in content areas. A curriculum of ideas based on successive lessons and student experiences is needed to develop sufficient schema for negotiating meanings from content-area text. The results of this study seem to promote the notion of engaging students in ideas, thereby facilitating long-term learning that becomes schema upon which new learning can occur.

For researchers, these findings raise several questions. First, the lack of congruence between the comprehension and composition measures during short-term learning poses a challenging question. To what degree must strategy-based writing instruction (e.g., Englert & Raphael, 1988) be paired with vocabulary instruction to bring the two processes closer together? Observations during instruction and teacher reports made it clear that written recalls did not constitute a frequently used means of measuring content knowledge. Would students' comprehension be quantitatively and /or qualitatively different if composing was a more conventional instructional experience? A second question focuses on the discussions that occur during instruction. What are the characteristics of the discussion during interactive strategies that are distinguishable from discussion when definitions are emphasized ? A third question deals with the

tie between research and practice. Can such interactive techniques be employed by practitioners, and does their use of the strategies lead to similar findings? Research-based strategies that lack ef- ficacy for teachers in their classrooms are of limited use to students, teachers, and intervention researchers.

In the last several years there has been an increasing call for theory-driven intervention research in learning disabilities (e.g., Wong, 1987). The current research provides evidence for interactive practices that are theoretically derived. By more closely examining theory-related practices such as these, researchers and practitioners alike should find cause to increase their confidence in the outcome of instruction and their understanding of the tie between research and practice.

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FOOTNOTES 'The lack of statistical differences between the three interactive strategies may be related to a Type II error due to insufficient power associated with the small number of students in the intervention conditions. This limitation does not allow for discussion related to instruc-

tional differences between the three interactive strategies.

This research was funded through the Interactive

Teaching Project (G008630125) from the Office of Special Education and Rehabilitative Services, U.S. Department of Education.

We wish to thank the special education teachers and their students at Doolen, Flowing Wells, Magee, Secrist, and Utterback Junior High Schools for allowing us to work in their schools. A special thanks to Adela Allen, Judy Mitchell, Grace Duran, Margaret Gallego, Elba Reyes, and Dave Scanlon for their assistance.

Requests for reprints should be addressed to: Candace Bos, Division of Special Education and Rehabilitation, College of Education, University of Arizona, Tucson, AZ 85721.




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Effects of Interactive Vocabulary Instruction on the Vocabulary Learning and Reading Comprehension of Junior-High Learning Disabled Students