Academic Interventions: What School Psychologists Need to Know for Their Assessment and Problem Solving Consultation Roles
Abstract and Keywords
This chapter provides an overview of critical concepts about academic interventions that school psychologists can apply in their assessment (prevention and diagnosis) and problem solving consultation roles. Topics covered include (a) general principles from research on reading, writing, math, and science instruction and learning; (b) home–school relationships; and (c) issues of diversity, motivation, and interpersonal relationships. School psychologists are encouraged to read widely and deeply the research literature on academic instruction and learning, to which many disciplines have contributed. School psychologists are also encouraged to practice and master the artful transformation of that research knowledge to the individual case at hand within a specific social context, including the family, classroom, school, community, and culture.
In an era of accountability in education, with high expectations for student learning outcomes, school psychologists are expected to partner with teachers and other educational professionals to raise academic achievement. In the United States, the federal government has issued a clear mandate that teachers should use evidence-based instructional practices to improve student learning outcomes. In this chapter we discuss other issues that school psychologists need to consider, along with research knowledge of teaching methods, to help students better learn academic skills.
The job responsibility of school psychologists is not to teach students academic skills directly. School psychologists contribute to improved student learning outcomes through indirect services—assessment and problem-solving consultation—which are their job roles (Peverly, 2009). Assessment may include screening for early intervention, progress monitoring to assess response to intervention (RTI), and testing to determine if students qualify for special education (eligibility decisions) or meet criteria for specific learning disabilities that have instructional implications (diagnostic decisions). Problem-solving consultation includes discussions with other professionals about a referred student to identify the student’s problem, plan intervention to modify the program that is not working, monitor the response to the intervention (RTI), and, if the student does not respond to that intervention, design an alternative plan. For both the assessment and consultation roles, knowledge of evidence-based academic interventions is highly relevant for generating academic intervention plans based on the assessment information, and increasing the probability that students will respond to the intervention. See Berninger (2007) for further discussion of these issues with applications to practice.
However, the amount and nature of preservice preparation school psychologists receive regarding academic interventions vary greatly. Some programs, especially those with an exclusively behavioral or special education orientation, may not cover the comprehensive body of research generated since the mid-twentieth century in fields ranging from mainstream reading, writing, math, and science (p. 554) research to linguistics, cognitive psychology, developmental psychology, and cognitive neuroscience. Moreover, inservice school psychologists may not have the time to keep up with, and become knowledgeable consumers of, an ever growing and evolving body of research relevant to academic learning. Consequently, they tend to rely on some of the following sources to obtain their information about evidence-based academic intervention practices: professional development presentations that offer continuing education credits, chapters in books that review the research, results of meta-analyses of multiple research studies, and testimony of publishers that a product is evidence-based.
Moreover, the emphasis in these secondary sources is often on what the teacher should do and what works for students, without sufficient attention to individual differences or systems variables (family and home–school relationships, interpersonal relationships in classrooms, school, community, and cultural issues, etc). Although knowledge of evidence-based practices based on research samples is necessary and desirable, such knowledge may not be sufficient; considerable clinical expertise is required for effectively translating that knowledge into educational practice (see Rosenfield & Berninger, 2009). Because school psychologists are the individual-differences specialists in schools, they are in an ideal position to help educators custom tailor academic instructional programs to the needs of individual learners.
The main goals of this chapter are, therefore, to provide for school psychologists (a) references to access recent reviews, syntheses, and meta-analyses of research findings about effective instruction in reading, writing, math, and science; (b) offer general principles based on the accumulating research evidence from many relevant research traditions that provide a conceptual framework for transforming research knowledge about academic learning into educational practice (planning, implementing, and evaluating academic interventions); and (c) discuss other important issues beyond instruction per se, for which research also exists, such as learning processes from the perspective of the student who is expected to respond to the instruction. To address these issues beyond teaching behaviors, we adopt a systems approach and apply it to (a) the individual learner’s response to instruction across the domains of academic learning—reading, writing, math, and science; and (b) the social context in which learning occurs at school and home across cultures.
A theme that has been supported by meta-analyses of research across these academic domains is that children respond best to explicit instruction. However, what counts as evidence-based, explicit instruction is far ranging and includes (a) instructional activities to develop conscious awareness of the relevant aspects of domain-specific learning; (b) teacher modeling of procedural knowledge for how to perform specific academic skills; (c) teacher-guided lessons that lead students to articulate conclusions, generate summaries, and/or answer questions that require inferential thinking; (d) direct explanations; and (e) strategy instruction for self-regulated learning (see Berninger, 2007; Cartwright, 2008; Graham, Harris, & Zito, 2005; Mayer & Wittrock, 2004; Rosenfield & Berninger, 2009, Part I; Swanson & Deschler, 2003).
Accessing Research on Effective Reading Instruction
Many reviews and meta-analyses of effective reading instruction have been conducted in the recent past (for an overview of these, see McCardle & Miller, 2009). In this chapter we focus on instructional and learning issues, for which evidence exists, but that were not covered in the influential National Reading Panel Report (NICHD, 2000), which has had major impact on instructional practices in the United States. The instructional components recommended by the National Reading Panel included phonological awareness, phonological decoding (alphabetic principle), fluency, vocabulary, and reading comprehension. To illustrate that research-generated knowledge is ever expanding, we propose that four additional kinds of evidence-based instruction should also be recommended for best practices: linguistic awareness that includes orthographic and morphological awareness as well as phonological awareness; teaching predictable decoding for written English words that draws on multiple knowledge sources including the three kinds of linguistic awareness; teaching oral language to facilitate learning of written language; and integrating writing and reading. Then, we discuss, from a systems perspective, the complexities of the skills that the learner must orchestrate in responding to reading instruction.
The ability to store words in working memory and reflect upon their constituent parts is critical to the acquisition of written language (Mattingly, 1972). (p. 555) However, three kinds of linguistic awareness play a role, but only the first kind was reviewed by the National Reading Panel: (1) phonological awareness of the sounds in spoken words; (2) orthographic awareness of letters and multi-letter units in written words; and (3) morphological awareness of the base word, plus or minus affixes in both spoken and written words that underlie the formation of longer, complex words, refine meaning and, in the case of suffixes, mark grammatical information linking words to higher levels of language. For evidence supporting orthographic awareness1, see Berninger (1987), Caravolas, Kessler, Hulme, and Snowling, (2005), Cassar and Trieman (1997), Olson, Forsberg, and Wise (1994), Seymour (1997), Pacton, Perruchet, Fayol, and Cleeremans (2001), Pacton, Fayol, and Perruchet (2005), and Varnhagen et al. (1999). For evidence supporting morphological awareness1, see Bourassa, Treiman, and Kessler (2006), Carlisle and Nomanbhoy (1993), Fayol, Totereau, and Barrouillet (2006), Leong, (2000), Nagy, Berninger, and Abbott (2006), Nunes and Bryant (2006), Pacton et al. (2005), and Pacton and Deacon (2008).
All three kinds of linguistic awareness, especially the interrelationships among phonological, orthographic, and morphological awareness, predict reading (and writing) outcomes of typically developing children and children with dyslexia (Berninger et al., 2008). See Henry (2003) for evidence-based approaches to teaching the phonology, orthography, and morphology of English words of Anglo-Saxon, Romance (French and Latin), and Greek origin, all of which are needed for reading achievement, from the beginning but especially after the first three grades. After the third-to-fourth-grade transition from oral to silent reading, the silent orthography and silent morphology of written words (which do not always correspond to phonological units of the same size), become increasingly important in languages with deep morphologies that code not only letter-sound correspondence, but also spelling-morphology correspondences (Jaffré & Fayol, 2006).
Teaching Regularities for Decoding in Morphophonemic Orthographies
English has a deep morphophonemic orthography, which means that even though it is not perfectly regular in pronunciation in terms of a single letter and a single phoneme, it is predictable when all three knowledge sources (orthography, morphology, and phonology) are taken into account (Venezky, 1970, 1999). For example, in English, the predictable correspondences in alphabetic principle tend to be between 2-letter (and not just-1-letter) spelling units and one phoneme, or a small set of phonemes called alternations, which can be applied strategically to decoding words until a match with a meaningful word in the mental dictionary is made. Moreover, alphabetic principle is not the only knowledge source that is relevant to decoding words in English, because pronunciation can also be based on multi-letter units corresponding to a rime unit (the part of a syllable left when the onset phoneme or blend is deleted), which often contains multiple phonemes; these correspondences are referred to by teachers as a word family (e.g., ould in could and would). Multi-letter units may also correspond to morphemes units with predictable spelling and pronunciation (see Nunes & Bryant, 2006). For example, tion and sion, which both contain the -ion morpheme, but the former has ti and the latter has si to stand for the alternate spellings of /sh/ in words of Latinate origin and in both cases the whole unit is pronounced /shun/ despite the unaccented /o/ vowel that does not have regular grapheme-phoneme correspondence.
Thus, teachers (or psychologists) should never tell children who are learning to read English that they should sound out unfamiliar words letter by letter, or that English is hopelessly irregular. Instead, an evidence-based approach teaches children the multiple ways units of written language (not just single letters) are related to units of spoken language within the word parts that mark meaning and grammar, so that the relationships among spelling, pronunciation, and meaning are evident. No words are completely irregular when the multiple connections underlying written and spoken language are taught explicitly to children. In addition, synthetic phonics alone, as recommended by the National Reading Panel, may not be effective if children cannot apply phonics rules learned as declarative knowledge (rules) to the decoding process. It may be necessary to teach alphabetic principle and other strategies for translating units of written language into units of spoken language as procedural knowledge; that is, how to produce the corresponding unit of language during the actual reading process. For school psychologists not familiar with the research from linguistic science, cognitive science, and instructional science that has provided the evidence supporting these general principles of reading instruction, which were not covered in the National Reading Panel Report, see the Table of Contents in Berninger (2007), with instructional resources from (p. 556) interdisciplinary research on word decoding along with explanations of the rationale underlying these word learning concepts. Berninger and Wolf (2009-a, 2009-b) also illustrate with practical examples how these general principles can be implemented in instruction.
Role of Oral Language in Learning Written Language
Many mistakenly believe that children have already learned oral language skills prior to school entry, and that the sole purpose of elementary education is to teach written language skills (reading and writing), that is, literacy. Mainstream educational research has long recognized that oral language is an important part of the instructional program for learning to read and write; many research studies have pointed to the conclusion that reading instruction benefits from oral discussion before and after reading text (e.g., Reznitskaya, Anderson, McNurlen, Nguyen-Jahiel, Archodidou, & Kim, 2001). However, children show considerable intra-individual differences in their oral language (listening and speaking) and written language (reading and writing) skills (Berninger et al., 2006), and some may have instructional needs in oral language if they are to learn written language.
Just as importantly, children have to learn from teacher talk (instructional language), which has two unique characteristics. First, although oral language in conversation typically has considerable contextual support from the conversational partner to support the conversation (Garvey & Berninger, 1980), children listening to instructional language must extract the message from longer stretches of talk without such frequent support from interacting with the speaker. Second, even though instructional language is typically oral, it often uses vocabulary and grammar that characterize the academic register rather than the oral register, and children need to learn to understand the unique patterns of language use in the academic register (see Silliman & Scott, 2009). Moreover, children who have language learning disabilities originating in the preschool years that interfere with development of syntactic awareness and inferential thinking about text may have extreme difficulty in learning to process the language teachers use (Silliman & Scott). Also, children who are dialect users and do not speak mainstream English (Washington and Thomas-Tate, 2009), or for whom English is not the first language, may also have difficulty in learning to understand instructional language and participate in oral language discussions. The importance of teaching oral language along with written language skills was not adequately addressed by the National Reading Panel, but see Berninger and Wolf (2009-a) for practical suggestions about how to do so.
Integrating Reading and Writing
To be successful in the reading program, children have to be able to write. They write to show that they understand what they read, for example, answering questions on independent seatwork, writing summaries, or composing book reports. As they get older, they are increasingly expected to read source material, take notes, and convert those notes into written reports in the content areas. These activities require executive functions (Altemeier, Abbott, & Berninger, 2008) to integrate reading and writing so that children become writing-readers (Altemeier, Jones, Abbott, & Berninger, 2006). The National Reading Panel did not examine the relationship of writing to development of reading skills. See Rieben, Ntamakiliro, Gonthier, and Fayol, (2005) for a review of research showing that including writing instruction in the kindergarten reading program can benefit reading development, for example, through opportunity to invent spellings that represent speech sounds and also receive feedback about conventional spellings.
Teaching does not cause learning apart from the mind of the learner, which mediates response to intervention (Berninger & Richards, 2009). For example, the learner must plan (set goals for reading based on the purpose—to skim for an answer to a specific question, or to read carefully for the main idea and supporting details), translate (turn the written squiggles on the page into identified words, syntactic structures, and discourse structures drawing on both what is stated in the text, and what must be inferred based on activated background knowledge about the topic/s and metaknowledge about language), and review (self-monitor) and revise (reread if translation does not make sense). All this mental activity that supports the reading comprehension process takes place in working memory, which has limited capacity and resources to support the processing and complex temporal coordination required to orchestrate all the component processes involved in reading (cf., Fayol, 1999; Bourdin & Fayol, 1994, 1996). Comprehensive assessment of response to instruction should take into account all these components of the functional system that (p. 557) support reading—not just the automatic ones, but also the controlled, strategic ones (also see Cartwright, 2008).
If the teacher is guiding the reading process, explicit cues from the teacher help the student to regulate (manage) the complex process. If the child is reading independently, the reading success may depend on the individual’s executive functions (mental self-government) for self-regulating the complex process involving all the components, from planning to translating to reviewing and revising, which collectively serve as the higher order executive functions that guide the cognitive processes in processing and producing written language (cf., Fayol, 1999; Hayes & Flower, 1980). When a student fails to respond to reading instruction, school psychologists should help the teacher figure out where in the complex system of many components the difficulty is, and then devise modified instructional approaches to overcome this difficulty in group instruction and/or independent work settings, as needed.
Accessing Research on Effective Writing Instruction
For a meta-analysis of effective writing instruction in students in fourth grade and above, see Graham and Perin (2007a, 2007b). For a review of evidence-based writing instruction, with focus on early and middle childhood, see Berninger (2008) and Hooper, Knuth, Yerby, Anderson, and Moore (2009). For an overview of evidence-based instructional practices for struggling writers in general, see Troia (2009), and for writers in general, including general and special education, see Graham, MacArthur, and Fitzgerald (2007).
Writing Components from an Instructional Perspective
Much instructional research on writing has focused on specific skills taught in the curriculum; for example, handwriting, spelling, and composing. Although earlier in the history of education in the United States, handwriting and spelling were often overemphasized and not taught in relationship to composing, currently relatively more emphasis is placed on composing (for a review of changes in instructional practices and overview of current approaches to writing instruction, see Wong & Berninger, 2004). Recent surveys of teacher practices in handwriting (Graham, Harris, Mason, Fink-Chorzempa, Moran, & Saddler, 2008a) and spelling (Graham et al., 2008b) document variability among teachers in what and how they are teaching these skills. School psychologists in schools that have not adopted systematic, explicit programs of handwriting and spelling instruction might, in their consultation role, volunteer for participation on the district curriculum committee to help adopt such a program, given clear research evidence for the importance of explicit, systematic instruction in these skills (Berninger, 2008; Graham & Perin, 2007a, 2007b; Hooper et al., in press).
Phonological, orthographic, and morphological awareness, which contributes to learning to read words, as discussed in an earlier section, also contributes to learning to spell words. However, they are interrelated in different directions for spelling (spoken to written words) and for reading (written to spoken words). In addition to these three kinds of linguistic awareness, other knowledge sources have been identified that contribute to spelling (and contribute to word reading, too): phonotactic (knowledge of permissible sound sequences and positions; e.g., Bernstein & Treiman, 2001; Kessler, & Treiman, 1997), orthotactic (knowledge of permissible letter sequences and positions; e.g., Apel, Wolter, & Masterson, 2006; Pacton et al., 2001, 2005), vocabulary meaning (e.g., Stahl & Nagy, 2005), and spelling rules (e.g., Chliounaki & Bryant, 2007). See Berninger and Fayol (2008) for instructional methods for teaching spelling that draw on these seven knowledge sources that contribute to spelling. In addition, grammatical knowledge (e.g., the possessive, contractions, inflectional suffixes that mark tense and number, derivational suffixes that mark part of speech, function words for prepositions, conjunctions, pronouns, and articles, and compounding of base words) contribute to spelling (e.g., Bryant, Nunes, & Bindman, 1997, 2000; Fayol et al., 2006; Kemp & Bryant, 2003; Nagy et al., 2006) and may facilitate the application of spelling knowledge during composing text (e.g., Carlisle, 1994).
Writing Components from an Individual Differences Perspective
Multivariate cross-sectional and longitudinal research have identified skills that are not writing per se, but contribute uniquely to specific writing skills within the same grade level or across adjacent grade levels (e.g., see Berninger, 2007; Hooper et al., 2009). In this chapter we focus on one writing-related skill that contributes unique variance in predicting writing achievement; namely, working memory (e.g., Swanson & Berninger, 1996), which (p. 558) supports the written language production system discussed next.
Writing Components from an On-Line Processing Perspective
In other programmatic research on writing, experiments have been conducted to study the on-line processing of the writer during the writing production process. According to Fayol (1999), who has been a leader in this line of research, most language production models include three components, which are orchestrated in working memory, for (a) conceptual planning to generate and organize ideas for a particular topic, writing goal, and audience; (b) translation of the ideas into units of language—words, syntax, and discourse; and (c) production of the language via speech or transcription (letter writing and word spelling by hand or keyboard). Two features of the production system, and the working memory system that supports it, influence how efficiently its components are orchestrated: (a) its limited capacity and resources; and (b) its temporal coordination, that is, executive management of the component processes. Because of the capacity limitation feature, the more resources any one component needs, the fewer resources are available for the other components. To the degree that any component is automatic2—that is, it can be performed quickly and effortlessly outside conscious awareness—the fewer resources it will use, and the more resources will be available for the other components. However, resources are still needed for the executive management of the system that orchestrates the component parts. The executive management requires controlled, strategic processing for smooth coordination; that is, fluency,2 and is resource-draining. If the sum of the resources needed for each component and for the executive management of the system exceeds the available resources, the system is said to be on overload.
On-line experiments have investigated the executive management of the component writing processes. Initially, writing processes are orchestrated serially—one process at a time—because parallel execution of multiple processes exceeds capacity limitations. For example, the number of ideas that can be generated and coherence of text are greater for oral production, which does not require handwriting, than for written production, which does (Bourdin & Fayol, 1994, 1996). Before handwriting is automatic in beginning writers, the amount that can be copied within a constant time limit is reduced (Bourdin & Fayol, 2000) compared to adults who have automatized their handwriting (Bourdin & Fayol, 2002).
On-line experiments have also shown that when writers experience difficulty in integrating component writing skills in real time, they adjust their writing speed or increase pause duration. For example, Chanquoy, Foulin, and Fayol (1990) found that adults, but not eight-year-olds, modified their pause durations between clauses. Beginning writers are unable to modify their handwriting speed, as skilled writers are, in response to changing conceptual or linguistic requirements of the writing task, probably because their handwriting is not yet automatic (Bourdin & Fayol, 1994, 1996). Recent studies (in preparation) extend this work by showing that skilled writers can carry out two writing-related tasks at a time in parallel—for example, planning the next clause while still writing the current clause—but beginning writers carry out these same two writing tasks serially, and complete the transcription of one clause before planning the next clause.
Many times when students do not start or finish writing assignments it is not because they are unmotivated, lazy, or have emotional problems; rather, their written language system may be on overload. Two ways to overcome overload are to (a) automatize transcription skills, and (b) combine tasks (Fayol, 1999). Not only does automating transcription free up resources for other writing components, but also automating one component makes it possible for other components to be executed in parallel; for example, choosing words and spelling words simultaneously, rather than serially (Fayol, Hupert, & Largy, 1999). Sentence combining, which has been shown to be an effective method of writing instruction (Graham & Perin, 2007a, 2007b), may be so because combining the two sentences teaches students more efficient executive management. Another way to overcome overload is to increase knowledge related to the writing topic (Bourdin & Fayol, 2002).
Instructional methods that have been validated in the University of Washington writing instruction studies for overcoming capacity limitations and facilitating executive management systems during writing include the following: (a) teach a plan for automatic writing of letters, and practice each of the alphabet letters once during a warm-up at the beginning of a lesson; (b) teach automatic phoneme–spelling correspondence and reflective coordination of phonological, orthographic, and morphologic awareness for word spelling; (c) teach for transfer (p. 559) of transcription skills to independent, self-regulated, authentic composing; (d) teach to all levels of language (subword, word, and text) close in time, so that they are coordinated in time for executive management; and (e) use a variety of brief instructional activities to avoid habituation by prolonged practice in any one skill—less is more! (See Berninger, 2007, Table of Contents, Instructional Resources; Berninger & Wolf, 2009-a, 2009-b).
Accessing Research on Effective Math Instruction
For meta-analyses on effective math instruction, see Swanson (2009) and Swanson and Jerman (2006). Also, see the conclusions and recommendations of the recently issued National Math Report (United States Department of Education, 2008). This report, which recommended that students should master Algebra II for high school graduation in the United States, concluded that the evidence does not support the use of handheld calculators as a substitute for explicit instruction and practice in math fact retrieval and computation.
Evidence-Based Instructional Approach
Overall, Mayer’s (2004) review of the history of math instruction in the United States supported guided discovery in math learning, with explicit instructional guidance, rather than pure discovery, with unstructured exploration as advocated by the constructivist philosophy of instruction, which has dominated teacher education for over a decade. The meta-analyses of Swanson and colleagues (e.g. Swanson, 2009; Swanson & Jerman, 2006) also found that explicit strategy instruction was the most effective for math learning. However, as discussed in the introduction, explicit instruction can provide a balance between automating skills and guiding students in reflective activities.
Children with math disabilities (MD) may have problems in math fact retrieval, computation, or visual spatial representation (Geary, 2003), or math fact retrieval, computation, and problem solving (Andersson, 2008).
Math Fact Retrieval and Computational Operations
Experimental studies have shown that early in schooling, children apply counting or other algorithms to find the answers to addition and subtraction problems, but later in schooling, when math fact retrieval is automated, use direct retrieval of math facts for addition and subtraction (Barrouillet & Fayol, 1998). That is why children who do not have automatic math fact retrieval may benefit from counting forwards and backwards by variable increments along a number line taped to their desk in learning their basic additional and subtraction number facts (Berninger, 2007). In contrast, problems in learning math facts for multiplication were related to inefficiencies in inhibiting incorrect responses, rather than in direct memory retrieval (Barrouillet, Fayol, & Lathulière, 1997). Perhaps activities in which children are timed for choosing the correct products among foils will help them become more efficient in inhibiting incorrect responses.
Children benefit from explicit instruction in schema for math word problems (Fuchs & Fuchs, 2003). Mayer (2004) contrasted these well-defined, routine math problems and the ill-defined problems, which are more likely to characterize math problems in the real world. His review of the research identified four cognitive processes that contribute to math problem solving, including representations (nature of the problem to be solved and strategies for doing so), planning/monitoring (executive management), executing, and self-regulation. He also identified seven effective instructional methods for problem solving including load-reducing, structure-based, schema-activation, generative, guided discovery, modeling, and teaching thinking.
As for reading and writing, multi-component production systems underlie math problem solving. Children make plans (represent the problem and construct or choose strategies for solving the problem), translate underlying number concepts into written numerals, number facts, or written computations (sequential steps of arithmetic algorithms for addition, subtraction, multiplication, and division), and review and, when errors are detected, revise. Although much arithmetic instruction teaches math fact retrieval, computation, and problem solving as separate processes, real-world math often requires the integration of these three processes. Executive functions are needed for integration of components in math problem solving, and monitoring (self-checking) and revising.
Children who do not have automatic math retrieval may benefit from multimodal practice (listen–say, (p. 560) listen–write, look–say, look–write) rather than look–say drill alone. Computation can break down because of problems in representing numerals in visual spatial arrays, in applying the sequential steps of calculation algorithms, in retrieval of math facts during calculation, misunderstanding the place value concept underlying the problem representation itself during the steps of the calculation or in expressing an answer, or momentary breakdowns in any step of the process, and failure to monitor and self-correct the errors that result. Children with problems in learning fractions or telling time benefit from explicit instruction in part–whole relationships. As with reading and writing, limited working memory resources and timing constraints can interfere with efficient math problem solving; however, including mental math activities at the beginning of each math lesson may improve the efficiency of working memory during math problem solving. For further discussion of all these issues, see Berninger (2007).
Although relatively little research exists on effective instruction for science, what does exist supports the same conclusion Mayer reached for more general problem solving: guided inquiry, including some direct explanation, is superior to unstructured discovery learning (Klahr & Nigram, 2004; Li & Klahr, 2006). Case studies have shown that teacher-guided inquiry is also effective with students with learning disabilities (Palincsar, Collins, Marano, & Magnusson, 2000). Progress is being made in improving teaching of vocabulary in the science content domain for students with a variety of language learning needs (see Silliman & Scott, 2009). Science can be a motivating part of writer or writing-readers workshops for struggling readers and writers (Berninger, 2009-b).
Literacy knowledge construction takes place both at home and at school (Purcell-Gates, 1996). Most children become acquainted with written language well before entering formal schooling, through observing and participating in literacy activities in their homes (van Steensel, 2006), both informal and formal (Senechal, LeFevre, Thomas, and Daley, 1998). Informal home literacy practices, which include interactions with print, such as storybook reading for the purpose of learning the message contained in print, are related to the development of language skills (Senechal & LeFevre, 2002). Formal home literacy practices, which include interactions focused on the print itself, for example, using an alphabet book to talk about letters and letter sounds (Senechal et al., 1998), are related to emergent literacy skills (Senechal & LeFevre, 2002; Evans et al., 2000). Senechal and colleagues found that all parents in their samples reported using informal home literacy activities, whereas only some reported formal ones. Not surprisingly, parents had differing ideas about the appropriate means for teaching their students early literacy skills (Fitzgerald, Spiegal, & Cunningham, 1991; Senechal et al.; Stipek, Milburn, Clements, & Daniels, 1992).
Parental Contribution to Academic Learning
Parental involvement enhances academic development (Leslie & Allen, 1999; Lonigan & Whitehurst, 1998; McWayne, Hampton, Fantuzzo, Cohen, & Sekino, 2004) through home literacy practices (Boudreau, 2005; Evans, Shaw, & Bell, 2000). Early home and childcare experiences were indirectly related to reading achievement through their influence on language development, and language and phonological knowledge were both directly related to acquisition of reading skills (Poe, Birchinal, & Roberts, 2004). The way in which parents view themselves within the framework of children’s academic success has been positively linked to indicators of student achievement, including student grades, achievement test scores, and teacher ratings of student competence (Hoover-Dempsey, et al., 2005).
A variety of parental beliefs and behaviors influence children’s academic socialization and school-related development (Taylor, Clayton, & Rowley, 2004). Rashid, Morris, and Sevcik (2005) found that, after maternal education level and children’s IQ were accounted for, parental indicators such as obtaining a library card for their child accounted for a significant amount of the variance in children’s reading comprehension and spelling performance. In contrast, direct measures of children’s literacy activities did not. Parental expectations for their children’s educational attainment and socialization practices, while not classified as a literacy activity, have also influenced children’s academic achievement (Lee & Bowen, 2006). Socialization practices can include both home literacy and other activities such as monitoring and structuring children’s time, discussing school and education, and holding educational expectations (Suizzo & Soon, 2006). (p. 561) However, most of the research on parent involvement in academic learning has focused on reading rather than writing, math, or science.
Children benefit from positive collaboration between schools and families (Patrikakou, Weissberg, Redding, & Walberg, 2005). Hoover-Dempsey et al. (2005) frames the construct of parental involvement in terms of parental role construction and parental sense of self-efficacy. Parental role construction, which is how parents view what they are supposed to do in relation to their children’s education, and the patterns of behavior that follow those beliefs, is important because it establishes a basic range of activities that parents will construe as important, necessary, and permissible for their own actions with and on behalf of their children (Hoover-Dempsey & Sandler, 1997). Parental self-efficacy, which is the belief that what one does makes a difference, requires experiences of success in helping the child learn, opportunities to observe other parents successfully helping their children with academic tasks, encouragement from important others (e.g., teachers), and support for positive feelings gained from success, or encouragement when doubts emerge (Hoover-Dempsey et al., 2005). If parents feel that their actions matter, they will become involved, but if they think their efforts are useless, they will avoid involvement for fear of confronting their perceived inadequacies (Hoover-Dempsey & Sandler, 1997).
Diversity Issues Related to Home Variables
Family, Race, Socioeconomic, Culture
Children’s early experiences within their family, and aspects of family structure, are consistently strong predictors of emergent literacy skills and later academic achievement (Downer & Pianta, 2006). The quality and quantity of those experiences are often mediated through the demographic factors of race, ethnicity, and socioeconomic status. Lack of material resources often place ethnic minority families at a disadvantage in terms of the home literacy environments they create for their children, and their relationships with the schools that educate them.
Parent academic involvement has been found to function differently across ethnicity and SES. In their study on the demographic characteristics of parenting, Hill et al. (2004) found several differences related to parental involvement. These included the finding that African Americans had higher levels of involvement in educational activities at home, whereas European Americans were more likely to be involved at school. Hill and Craft (2003) found differential pathways for African American and European American parents with regard to behavioral control and child outcomes. Jeynes (2003) found that parental involvement in school was more influential for African American and Latino students than for Asian American students.
Parents’ efficacy levels have been associated with their levels of education, which are often included as a measurement of socioeconomic status (Kohl, Lengua, & McMahon, 2000), with parents who have lower educational attainment tending to have lower efficacy than parents with higher levels of education (Hoover-Dempsey & Sandler, 1997). Higher parental education has been associated with more stimulating learning environments (Parcel & Menaghan, as cited in Manguson & Duncan, 2002). Alternatively, parents with lower levels of education may be less involved with school because they feel less comfortable communicating with school personnel, as a result of the differences in education (Lee & Bowen, 2006). Kohl et al. (2000) found that parental education level was related to the quality and amount of parent–teacher contact, parental involvement in school and at home, and teacher’s perceptions of the parent’s valuing of education. These findings held true across ethnic lines. Burchinal et al. (2002) found that maternal education and parent’s practices and attitudes were strong predictors of child outcomes. Hoover–Dempsey and Sandler (1997) cited research that parents with less education expressed doubts about their abilities to help their children in school, and their hope that teachers would assume responsibility for teaching needed skills.
The role of parents’ beliefs about parenting practices and sense of efficacy in terms of their involvement with their children’s development varies according to social class and ethnic background, but each of these constructs has been linked to achievement outcomes (Burchinal, Peisner-Feinberg, Pianta, & Howes, 2002). Lee and Bowen (2006) framed the relationship among race, SES, and parental education in terms of cultural or social capital, which has been defined as (a) features of a social organization that facilitate cooperation for mutual benefit, and include mechanisms such as mutual trust among individuals, and community participation (Garcia Coll & Pachter, 2002), and (b) personal dispositions, attitudes and knowledge gained from experience, connections to education related objects (i.e., books, academic credentials, technology), and (p. 562) connections to education-related institutions (Lee and Bowen, 2006). According to Lee and Bowen, the greater an individual’s cultural capital, the more likely the individual is to obtain benefits for themselves and their families. The less cultural capital available, the more constrained and restricted the family becomes with regard to resources (2006). For example, European American and middle class parents are more likely to share the school culture and feel comfortable with the school, whereas African American, Latino, and low-income parents usually do not share cultural backgrounds with the school and may be more reluctant to initiate contact (Desimone, 1999).
Parents from higher SES backgrounds are more likely to see themselves as in partnership with schools, and tend to presume they are more entitled to be involved in their child’s education (Hill et al., 2004). The results of shared culture for European American and middle income families is that there is congruence between home and school culture, which has been found to be advantageous to student outcomes (Lee & Bowen, 2006). Alternatively, parents with lower cultural capital are less likely to have access to information about school systems which could inform their practices at home, which, in turn, could relate to their children’s academic outcomes.
Biologically Based Learning Disabilities
Another source of diversity that cuts across socioeconomic and racial groups is genetic and neurological (Berninger et al., 2008). Because other family members in the current or past generations are likely to be affected when a learning disability has a genetic basis, school psychologists are encouraged to reach out proactively to parents of children with developmental and learning problems, who may fear their children will experience the same school struggles they did. See Berninger (2007) for practical ways to do so early in schooling.
Interpersonal Relationships, Multicultural Factors, and Systems Variables
Interpersonal relationships between teachers and students, and among peers in the same classrooms, can influence academic learning and response to instruction as much as cognitive variables can (Pianta, 1999). Multicultural factors can influence how the child responds to instruction at school, or the kind of home–school relationships that are established. See Jones (2009) for an overview of multicultural research that is relevant to school psychology practice. Motivation variables such as creating interest, hope, and self-efficacy, setting goals, and graphing progress toward meeting goals, also contribute to learning and affect response to instruction (Berninger & Hidi, 2006). Other systems variables in the classroom, school, family and community may also influence a child’s learning at school.
Knowledge of what research has found about effective instruction is valuable for the school psychologist who assesses children and consults with teachers and parents on behalf of children. However, equally important for improving a student’s academic learning is broader knowledge of the cognitive and motivational processes in learning, individual differences among students due to language, cultural, socioeconomic, or biological diversity, knowledge of the student’s interpersonal relationships within the classroom and relevant family issues, and the school psychologist’s relationship with other professionals in the school and the family. Compassionativity (caring about the student who struggles with academic learning, see Berninger & Richards, 2002) can be just as important as research knowledge in helping students respond to instruction and improve their learning outcomes, behavior, and mental health.
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(1.) Because of space limitations, these are examples of research articles with evidence rather than exhaustive review of the literature.
(2.) Please note that automaticity is not the same as fluency. When cognitive processes become automatic, the previously controlled, strategic processing, which requires relatively more working memory resources, is transformed to rely on direct retrieval of a single item, which requires fewer working memory resources. In contrast, fluency refers to the executive coordination of serial items over time that is controlled and strategic, but after practice becomes fast, coordinated, and smooth, and thus requires fewer working memory resources than it did when it was first being learned. Fluency may also be enhanced by flexibility, and not only automaticity (Cartwright, 2008).