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Learning Styles Research

Research by Barbara Prashnig For more information, contact: Technology Based Solutions 504 Floral Vale Blvd. Yardley, PA 19067 888.783.2283 www.asktbs.com

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Table of Contents
Achievement Gains Through Learning Styles Matching ......................................... 3 A Summary of Learning Style Preferences at Various Grade Levels...................... 5 Classroom Discipline............................................................................................... 5 Cognitive Style ........................................................................................................ 6 Counselling ............................................................................................................. 7 Cultural Comparisons.............................................................................................. 8 Emotional Elements and Achievement.................................................................. 11 Formal/Informal Preferences and Achievement .................................................... 11 Gifted/Non-Gifted Students ................................................................................... 11 Intake, Sound and Achievement ........................................................................... 13 Learning Disabilities .............................................................................................. 13 Learning Styles/Teaching Styles........................................................................... 16 Maths Test Scores and Attitudes ..........................................................................16 Mathematics, Reading, and Time Preferences ..................................................... 17 Musical Talent....................................................................................................... 17 Physiological Elements and Achievement............................................................. 18 Reading and Sound .............................................................................................. 19 Reading and Light ................................................................................................. 19 Reading Comprehension and Design (Study Area) .............................................. 20 Rural/Inner City Student Background....................................................................20 Science Achievement with Computer-Assisted Instruction ................................... 21 Social Studies ....................................................................................................... 21 Sociological Elements and Achievement .............................................................. 22 Time of Day Preferences and Achievement.......................................................... 23 Vocational Education/Industrial Arts ..................................................................... 25 Word-Pair Recognition and Mobility ...................................................................... 26 Word Recognition and Temperature ..................................................................... 26

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Research concerned with identifying the relationship(s) between academic achievement and individual learning style has provided consistent support for the following: a) students do learn differently from each other; b) student performance in different subject areas is related to how individuals do, in fact, learn; c) when students are taught with approaches and resources that complement their unique learning styles, their achievement is significantly increased (DeBello, 1985; Dunn, DellaValle, Dunn, Geisert, Sinatra, & Zenhausern, 1986; Dunn, Dunn, Primavera, Sinatra, & Virostko, 1987; Dunn, Krimsky, Murray and Quinn, 1985; Dunn, Cavanaugh, and Zenhausern, 1982; Giannitti, 1988; Hill, 1987; White, 1981; Hodges, 1985; Jarsonbeck, 1984; Kroon, 19 85; Lemmon, 1985; Lynch, 1981;, MacMurren, 1985; Martini, 1986; Miles, 1987; Murrain, 1983; Pizzo, 1981; Shea, 1983; and Spires, 1983). In addition to the research documentation substantiating the positive effects that occur when students are taught in ways that are responsive to how they each learn, widespread practitioner corroboration has been published based on classroom or schoolwide experiences (Ballinger & Ballinger, 1982; Carruthers & Young, 1980; Cavanaugh, 1981; Dunn, 1981; Fiske, 1981; Dunn & Griggs, 1987, 1989a, 1989b; Gardiner, 1983; Hodges, 1982, 1983; Jenkins, 1982, 1986; Lemmon, 1982, 1985; Pizzo, 1982; Vigna & Martin, 1982; and Wheeler, 1980). This section provides an overview of selected correlational and experimental studies concerned with the identification of students' learning style characteristics with the Learning Style Inventory (LSI).

Achievement Gains Through Learning Styles Matching
A doctoral investigation conducted by Spires (1983) revealed that implementation of a learning styles program resulted in significant gains in reading and mathematics achievement on standardized achievement tests. The Learning Style Inventory (Dunn, Dunn, & Price, 1978) was administered to students in grades 3 through 6, and the Learning Style Inventory Primary Version (Perrin, 1982) to grades K through 2. Analyses of the data indicated that teaching students through their individual learning styles resulted in significantly higher reading and mathematics achievement, particularly on those subtests requiring higher level cognitive abilities, such as reading concepts. A study was conducted to (a) identify how the Dunn, Dunn and Price Learning Style Model had been implemented in seven diverse regions of the United States and (b) develop guidelines for providing instruction for students with learning styles not currently accommodated in conventional classrooms (Klavas, Dunn, Griggs , Geisert, Gemake, & Zenhausern, 1994). Many practitioners had reported that such students often were classified as poor achievers, learning disabled, discipline problems, or dropouts; but that academic reversals had occurred when instruction was redesigned to respond to their particular learning-style preferences as revealed by Dunn, Dunn, & Price's (1989) LSI (Andrews, 1990; Brunner & Majewski, 1990; Elliot, 1991, Klavas, 1993, Perrin, 1990; Stone, 1992). Braio (1995) analyzed the effects of gradually implementing learning-style strategies on reading achievement and attitude toward instruction with 81 special education and 35 low-achieving general education-urban students in grades four, five, and six. Pre-and post-tests concerned with structural analysis instructional units were administered in each of five phases, of two weeks each, to determine reading achievement gains. Significant gains in reading achievement for both groups were revealed when students were taught using gradually-increasing, learning style approaches that included responsiveness to students' varied Sound, Light, Temperature, Seating, Mobility, and Perceptual preferences. Removal of learning-style approaches evidenced decreased achievement. Statistical significance for attitude was achieved by the general education students, but not those in special education, perhaps because these students' classroom environment often reflects a relaxed traditional ambiance. Marino, 1993 argues that students will accept and even learn from homework provided that its design takes into consideration students' learning styles and study skills. He describes an effort at an all-boys

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high school in Brooklyn, New York, to tai lor class instruction and homework to results obtained from a Learning Styles Inventory. Klavas, 1994 describes how a North Carolina elementary school altered teaching methods to suit varied learning styles of the students based on the results of a Learning Styles Inventory. She discusses changes made based on students' perceptual preferences, time of day preferences, environmental preferences, and sociological preferences. Discipline problems dropped dramatically and test scores rose precipitously. This investigation (Braio, 1995) analyzed the effects of incremental implementation of learning-style strategies on reading achievement and attitude toward instruction via structural analysis with special education and low-achieving general education students in grades four, five and six. To identify individual preferences, the Learning-Styles Inventory (Dunn, Dunn, & Price, 1990) was administered to students who attended an urban intermediate school. Two categories were targeted: 81 special education students and 35 low-achieving general education students. Both categories were divided into two sub-groups: group one was incrementally matched according to learning-style preferences for sound, light, temperature, design, mobility, tactual, kinesthetic, auditory and visual elements; group two consisted of unmatched and/or no preferences. Instructional units were divided into five phases of two weeks each. Structural analysis units and varied learning-style preferences gradually were introduced during these instructional phases: (phase 1) compound words using traditional teaching methods; (phase 2) plurals accommodating for sound, light, temperature, design and/or mobility elements; (phase 3) prefixes accommodating for sound, light, temperature, design and/or mobility elements and/or tactual and kinesthetic modalities; (phase 4) suffixes accommodating for sound, light, temperature, design and/or mobility elements and/or tactual, kinesthetic, auditory and/or visual modalities; and (phase 5) contractions using traditional teaching methods. Pre- and post-tests were administered in each of the five phases to determine reading achievement gains. Significant gains in reading achievement for both special education and general education students were found when students were taught using incremental learning styles strategies. To determine attitudinal changes toward reading, the Semantic Differential Scale (Pizzo, 1981) was administered four times throughout this study: before phase 1 (a baseline measure); after phase 1 (traditional teaching); before phase 5 (learning-styles intervention); and after phase 5 (with the return to traditional teaching and the removal of learning styles). Statistical significance for attitude was not achieved for the special education students. However, the general education students' attitudes toward reading became increasingly favourable after learning-style instruction and a decrement occurred after learning-style methods were removed. These data confirmed the importance of matching learning-styles preferences with complementary instructional strategies and environments. Experimental studies (Dunn, Griggs, Olson, & Beasly, (1995) based on the Dunn, Dunn and Price Learning Style Model and conducted between 1980-1990 were identified to determine the value of teaching students through their learning-style preferences. Thirty six studies provided a database of 3,181 participants. Results were synthesized through meta-analysis and the standard normal curve suggests that students whose learning styles are accommodated would be expected to achieve 75% of a standard deviation higher than students who have not had their learning styles accommodated. This finding indicates that matching students' learning-style preferences with educational interventions compatible with those preferences is beneficial to their academic achievement. Through the use of greater tactual, kinesthetic, and global methodology during reading instruction, the fifteen students enrolled in the program experienced an average increase of 73.33 percent in selfconcept, according to the Primary Self-Concept Inventory. These same students experienced an average gain of 7.25 months in reading achievement, as measured by the Iowa Test of Basic Skills, during five months of instruction (Settle, 1989). After a brief review of the literature on sound, a study by J. Pizzo (1981) is described involving learning style preferences of 64 6th graders. Results of exposure to either noise or sound revealed that Ss' who preferred quiet performed best in a quiet acoustic environment (AE). Ss' who preferred sound performed best in a noisy AE. Ss' in an environment that complemented their learning style

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preference also had statistically higher attitudinal scores than their mismatched peers, and a mismatched environment affected Ss' reading achievement and attitudes toward intellectual ability and other strengths.

A Summary of Learning Style Preferences at Various Grade Levels
An examination of the ways in which learning style characteristics appeared to change as students advanced from grade to grade was conducted by Price (1980). It was revealed that selected environmental, emotional, sociological, and physical traits appe ared to be stable over time, whereas others tended to parallel the growth curve. A total of 3,972 subjects in grades 3 through 12 completed the LSI during the 1979-1980 school year. Some of the statistically significant findings revealed were: * The higher the grade level, the more Sound and Light were preferred. * The higher the grade level, the less preference was indicated for Formal Design (wooden, plastic, or steel chairs when studying). * Self Motivation decreased during grades 7 and 8, but then a gradual increase was evidenced in each of the grades thereafter. * The higher the grade level, the less Teacher-Motivated students became. * The higher the grade level, the less Motivated in general, students were. The biggest shift was between grades 7 and 8, with grade 11 having the highest peak for being Unmotivated. * An overall decrease in the need for Structure was evidenced the higher the grade. * Although the junior high school years are considered strong periods for Peer influence, there was a greater need to learn/study alone in grades 9, 10, 11, and 12 than during any other interval. * The highest need to learn with Peers occurred in grades 6 through 8; the lowest need was in grade 12, followed by grade 9, with a slight increase in grades 10 and 11. * The younger the student, the more tactual and kinesthetic he/she was. Those modalities were followed by the development of visual strengths and, beginning with grades 5 and 6, the development of auditory strengths. Price (1980) revealed how learning-style changed as students moved from elementary school into adolescence and young adulthood. Others found that learning styles are also different by achievement level, gender, and age (Dunn & Griggs, 1995). Thus g eneral changes in style can be anticipated as students develop.

Classroom Discipline
A survey (Campbell, 1990) of teachers in an elementary school building and a literature review indicated that the causes of the lack of individualizing student learning were related to class size, poor leadership, teacher training, and poorly developed learning style instruments. A practicum was designed for classroom teachers to recognize differential learning styles and incorporate them into their repertoire of teaching. This practicum involved 31 sixth grade students and included five behavioural objectives: (1) improved study habits, attitudes, and behaviour; (2) employment of four distinct teaching methods; (3) administration of the Dunn, Dunn, and Price Learning Style Inventory self-reporting instrument to 27 elementary teachers; (4) in-service on learning styles for all elementary teachers; and (5) parental review of child's learning style inventory results. Outcomes of the practicum showed improved work habits in 27 students, improved classroom attitudes in 26 students, and improved classroom behaviour in 10 students. The students and their classroom teacher found the four group teaching methods that were introduced and demonstrated to them to be an excellent experience.

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Cognitive Style
Go into any classroom, at any level, in any school, and select a textbook in any subject. Chances are excellent that the textbook is not presented compatibly with how more than half the students in that classroom learn best. How is that possible? A large majority of educators are analytic processors whereas many students at any level are global processors. Neither method is better than the other and both types can learn the same information; they just do it differently. Analytics respond best w hen ideas are presented sequentially with new information building upon past knowledge leading up to eventual understanding of entire concepts. Globals/Holistics, on the other hand, need to "see the whole picture" first. They respond best when a teacher begins with a short story that explains why learning this information is important. Globals must be able to relate new information to what they already know. For a greater understanding of the differences between global and analytic processors, we turn to the research. Kaley (1977) investigated field dependence versus field independence and how it affected sixth-grade readers. She found that of the good readers, half were analytic and half were global. Of the poor readers, 85% were global. She concluded that good readers were field independent (analytic) because they could see each letter, sound it out individually, and piece it together with others to form words. Two years later, Trautman (1979) explored the relationship between selected instructional techniques and cognitive style. He used Contract Activity Packets (CAP' s) with junior-high school social studies classes. Half the objectives were written analytically and half were written globally. Each student completed all the objectives. Trautman's findings indicated that the groups matched with their processing styles achieved statistically higher gains on those objectives than on the objectives written in the unmatched style. Further support for matching instructional techniques to cognitive style was provided by Tanenbaum (1982) who studied high school students enrolled in nutrition classes. Trautman's, Douglas', and Tanenbaum's students all produced significant gains when instructional techniques matched their cognitive styles. At about the same time, Dunn, Cavanaugh, Eberle, and Zenhausern (1982) found that right/left brain dominance was linked with certain learning-style elements. Using a scale for brain dominance developed by Zenhausern, the researchers identified high school students as being either right-brain dominant or left-brain dominant. Their findings revealed that students who were strongly left-brain dominant needed quiet, bright light, formal design, were persistent, and required no intake while studying. Conversely, right-dominant students needed sound, preferred low lighting and informal seating, were not persistent, and often required intake while learning. The findings of Dunn, Cavanaugh, Eberle, and Zenhausern constituted a significant breakthrough in our understanding of the importance of cognitive processing. For the first time, specific conditions under which analytics and globals learn were identified. One of the first correlational studies that revealed a relationship between IQ and cognitive processing was conducted by Cody (1983). She examined the learning styles of highly gifted, average, and underachieving students. Among her findings were that: (a) of the students with an IQ of 145 or higher, 9 of 10 were global: (b) of the students with an IQ of 135 or higher, 8 of 10 were global: (c) of the students with an IQ of 125 or higher, 8 of 10 were analytic: and (d) analytics performed better than globals in school. Furthermore, Cody noted that the learning styles of gifted, average, and underachievers were very different from each other. The most crucial point that teachers need to know is how to teach both analytically and globally. Analytics learn best when information is presented in a step-by-step sequence, whereas globals need to understand the whole concept first; they then focus on the details. To engage a global learner, a

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teacher should introduce a new lesson with a humorous story and use diagrams, illustrations, and pictures to represent key ideas. It is important to note that many globals prefer to work with peers rather than alone or with a teacher, and they often like to structure their own tasks. Globals appear to concentrate best with Sound, Soft or Low Lighting, an Informal seating arrangement, and some form of Intake. Also, they take frequent breaks while studying and often work on several tasks simultaneously. Analytics, on the other hand, prefer to work on one assignment at a time before proceeding to the next. They prefer a quiet, well illuminated environment and formal seating. Most analytics do not require Intake to concentrate (Dunn, Cavanaugh, Eberle, & Zenhausern, 1982). Many highly gifted students and most underachievers are global. The difference between the two groups is that underachievers tend to become unmotivated and are essentially Tactile/Kinesthetic learners. Globals appear to concentrate best with Sound, Soft or Low Light. It would be wise to vary tasks to increase students' motivation and persistence and to encourage active, hands-on participation while learning. It is interesting to note that the majority of elementary school-age children are global. However, as children develop and progress through the grades, many become increasingly analytic (Dunn, Dunn, 1992, 1993; Dunn, Dunn, & Perrin, 1994).

Counselling
Griggs, Price, Kopal, and Swaine (1984) tested 165 sixth-grade, suburban students for their styles with the Learning Style Inventory (Dunn, Dunn, and Price, 1978). The 19 who revealed either Low Motivation and a High Need for Structure or High Motivation and a Low Need for Structure were randomly assigned to one of three groups: (1) High Structure & Counselling: Compatible: Low Motivation, High Structure (three students); Incompatible: High Motivation, Low Structure (two students); (2) Low Structured Counselling: Compatible: High Motivation, Low Structure (four students); Incompatible: Low Motivation, High Structure (three students); (3) Control Group: (seven students). All groups met for eight sessions conducted weekly during a two-month period. The treatment objectives, to explore the world of work, were identical, but their strategies differed. A one-way analysis of covariance was used to analyze the data. The independent variable had three levels: Compatible, Incompatible, and Control; the covariate was pre-test scores, and the dependent variable was post-test score on the Occupational List Recall Test (OLRT). The comparison of groups for the adjusted OLRT post-test score was significant (p