Research has indicated that on average, employees with a bachelor’s degree earn $21,545 more than workers with no college credits. Consequently, many incoming freshmen enroll in community colleges with a strong desire to improve their standard of living. However, less than 63 % of these students return for a second year. To understand this problem, the learning-styles of two distinct community college populations, education majors and remedial students, were examined. Although the two groups evidenced no significant differences in their perceptual strengths and hemispheric processing styles, comparative analyses revealed significant differences for specific learning-style elements depending on the participants’ gender and level of achievement. In addition, these two groups of learners also exhibited significantly different correlations.
Although more high school graduates are prepared for college today, as a whole in the United States, few gains have been made in college completion over the last decade, and substantial racial, ethnic, income, and geographical disparities have been disguised by these improvements. In fact, the gap in college participation between high- and low-income students has widened in many states. Additionally, only a slightly higher percentage of college students complete two-and four-year degrees ( National Center for Public Policy and Higher Education, 2004). Conversely, many of our nation’s global competitors have surpassed the United States in providing access to higher education and baccalaureate degree attainment at a time when economic and demographic changes demand training beyond high school ( National Center for Public Policy and Higher Education, 2004).
According to Carnevale and Desrochers (2003), when employers recruit new personnel, they prefer to hire the applicants with post-secondary education, and they reward them with higher wages than candidates who have only completed high school. An associate degree typically provides a wage increase of approximately 20 to 30 % over a high school diploma, and the returns for women are even higher (Carnevale & Desrochers, 2003). Moreover, potential employees who don’t have an associate degree, but have earned at least one year of college credits can access wages that are 5 to 11 % greater than the salaries offered to high school graduates (Grubb, 1999; Kane and Rouse, 1995; Pascarella, 1999). On the contrary, workers with the least education encounter the most obstacles when attempting to increase their earnings because they are less likely to receive training and have access to technology, which both lead to higher incomes (Carnevale & Desrochers, 2003). In fact, the average household income increases by $10,656 for workers with some college credit and by $21,545 if they received a Bachelor’s degree (U.S. Census Bureau, 2000).
The need for a more educated workforce stems from the reality that employers cannot compete successfully unless their workers possess solid academic skills. For instance, because of the rapid advances and the complexity of modern technology, computer systems and sophisticated machinery must be operated by personnel with highly developed skills that include reading, critical thinking, and problem solving. In addition, employees must be able to interact effectively with customers, prepare and present documentation, convey new ideas, and resolve problems. All of these tasks require advanced communication skills, which include effective listening, speaking, reading,and writing. As a result of these demands, American employers use education as the most reliable standard to assess the preparedness of job applicants (Carnevale & Desrochers, 2003).
Despite the need for educated and trained professionals, educational attainment has leveled off during the last several years (Carnevale & Desrochers, 2003). Enrollment of low-income students has decreased from 24 % to 21 %, and less than 63 % of community college freshmen return to college for a second year ( National Center for Public Policy and Higher Education, 2004). In the past decade, retention rates have decreased almost 2% for the community colleges, while the four-year colleges have seen a modest increase of 2.6% ( National Center for Higher Education Management Systems, 2002). This problem not only undermines our nation’s performance in a highly competitive global economy, but also inhibits economic, academic,and personal growth among the poorest members of our society who have the least opportunities to achieve success. Therefore, many community college administrators and faculty have begun to investigate new innovative approaches to enhance student performance, retention,and graduation rates because these institutions are typically the ones that encounter the students with the lowest incomes, the weakest skills, and the greatest risk of academic failure.
Traditional Methods versus Learning Styles
To support underachieving students who are in jeopardy of failing out of college, administrators, faculty, and counselors at community colleges have instituted a wide variety of programs that range from tutoring centers, study skill preparation classes, learning communities, cooperative learning, workshops, and academic probation. However, according to Biggs (1978), Derry and Murphy (1986) and Ford (1981), these approaches have been ineffective for large numbers of students. In contrast, Mangino and Griggs (2003) examined experimental research conducted in various undergraduate courses, and discovered that when instruction was congruent with college students’ learning-style preferences, they achieved significantly higher scores than when mismatched. Rochford (2004c) replicated these findings when she confirmed that preparing under-achieving remedial writing students at an urban community college with learning-style responsive materials resulted in significantly higher achievement and levels of curiosity than the use of a traditional classroom chalk and talk method.
These results occur because learning-style traits vary according to academic achievement (Clark-Thayer, 1987; Eitington, 1989; Giordano & Rochford, 2005; Hickerson-Roberts, 1983; Jenkins, 1991; Ranne, 1996), gender (Bovell, 2000; Lam-Phoon, 1986; Li, 1989; Giordano & Rochford, 2005), culture (Franchi, 2002; Ponce-Meza, 1997; Wittenberg, 1984), age (Bovell, 2000; Galvin, 1992; Giordano & Rochford, 2005; Katzowitz, 2002; Kizilay, 1991; Montgomery, 1993), and processing style (Dunn, Bruno, Sklar & Beaudry, 1990; Ritchey, 1994; Siebenman, 1984; Wittenberg, 1984). In fact, research has demonstrated that the less academically successful college students are, the more important it is to accommodate their learning-style preferences (Dunn, 2003) because these underachieving learners often enroll in community colleges and are unable to negotiate successfully into college-credit courses (Ingham, 2003; Nelson, Dunn, Griggs, Primavera, Fitzpatrick, Bacillious, & Miller, 1993; Rochford, 2003, 2004a, 2004b, 2004c). In fact, Claxton and Murrell (1987) and Garcia-Otero and Teddlie (1992) reported that students’ mere knowledge of learning styles increased academic success in college courses. Additionally, when researchers experimented with instructional treatments to increase college students’ achievement based on their learning-style preferences, each reported significantly higher achievement when study strategies were congruent, rather than incongruent, with students’ learning styles across subject matter (Clark-Thayer, 1987; Dunn, Deckinger, Withers, & Katzenstein, 1990; Ingham, 2003; Lenehan, Dunn, Ingham, Murray, & Signer, 1994; Miller, 1998). Of greater consequence, Nelson et al. (1993), Ingham (2003) and Rochford (2004c) demonstrated that not only did knowledge of learning-style preferences increase community college students’ achievement, but it also improved their rate of retention.
To support underachieving students who are in jeopardy of failing out of college, administrators, faculty, and counselors at community colleges have instituted a wide variety of programs that range from tutoring centers, study skill preparation classes, learning communities, cooperative learning, workshops, and academic probation. However, according to Biggs (1978), Derry and Murphy (1986) and Ford (1981), these approaches have been ineffective for large numbers of students. In contrast, Mangino and Griggs (2003) examined experimental research conducted in various undergraduate courses, and discovered that when instruction was congruent with college students’ learning-style preferences, they achieved significantly higher scores than when mismatched. Rochford (2004c) replicated these findings when she confirmed that preparing under-achieving remedial writing students at an urban community college with learning-style responsive materials resulted in significantly higher achievement and levels of curiosity than the use of a traditional classroom chalk and talk method.
These results occur because learning-style traits vary according to academic achievement (Clark-Thayer, 1987; Eitington, 1989; Giordano & Rochford, 2005; Hickerson-Roberts, 1983; Jenkins, 1991; Ranne, 1996), gender (Bovell, 2000; Lam-Phoon, 1986; Li, 1989; Giordano & Rochford, 2005), culture (Franchi, 2002; Ponce-Meza, 1997; Wittenberg, 1984), age (Bovell, 2000; Galvin, 1992; Giordano & Rochford, 2005; Katzowitz, 2002; Kizilay, 1991; Montgomery, 1993), and processing style (Dunn, Bruno, Sklar & Beaudry, 1990; Ritchey, 1994; Siebenman, 1984; Wittenberg, 1984). In fact, research has demonstrated that the less academically successful college students are, the more important it is to accommodate their learning-style preferences (Dunn, 2003) because these underachieving learners often enroll in community colleges and are unable to negotiate successfully into college-credit courses (Ingham, 2003; Nelson, Dunn, Griggs, Primavera, Fitzpatrick, Bacillious, & Miller, 1993; Rochford, 2003, 2004a, 2004b, 2004c). In fact, Claxton and Murrell (1987) and Garcia-Otero and Teddlie (1992) reported that students’ mere knowledge of learning styles increased academic success in college courses. Additionally, when researchers experimented with instructional treatments to increase college students’ achievement based on their learning-style preferences, each reported significantly higher achievement when study strategies were congruent, rather than incongruent, with students’ learning styles across subject matter (Clark-Thayer, 1987; Dunn, Deckinger, Withers, & Katzenstein, 1990; Ingham, 2003; Lenehan, Dunn, Ingham, Murray, & Signer, 1994; Miller, 1998). Of greater consequence, Nelson et al. (1993), Ingham (2003) and Rochford (2004c) demonstrated that not only did knowledge of learning-style preferences increase community college students’ achievement, but it also improved their rate of retention.
Learning style is the way students begin to concentrate on, process, internalize, and remember new and difficult information (Dunn & Dunn, 1993). Each individual’s preferences differ significantly, and the stronger the preference, the more important it is to provide compatible instructional strategies (Braio, Dunn, Beasley, Quinn, & Buchanan, 1997). Most instructors are not cognizant of the fact that less than a third of their pupils can recall what they hear or see during a classroom lecture (Dunn, 2003). However, many of these same learners remember well when they learn tactually by using their hands, or kinesthetically through whole body movement. Nonetheless, many tactual and kinesthetic students cannot achieve success in college because they are expected to sit and listen passively in class when they, instead, crave active engagement to learn effectively.
The Dunn and Dunn learning-style model is divided into five strands called stimuli. The first stimulus strand consists of biologically-imposed environmental elements (Thies, 1979, 1999-2000). These include preferences to learn with (a) sound or silence, (b) dim or bright light, (c) warm or cool temperatures, and (d) formal or informal seating. The combination of light and seating design affect approximately 70 % of adults (Dunn & Dunn, 1998). Although room temperature and sound impact only a small percentage of learners, for those who have a strong need for silence or sound and/or a specific room temperature, these elements are critical for functioning effectively because if the temperature or acoustics do not match their biological preferences, they become distracted and are unable to concentrate (Dunn, Thies, & Honigsfeld, 2001).
The model’s second stimulus strand includes the emotional elements of motivation, persistence, responsibility, and structure. Although the element of persistence is innate, the others are developmental (Thies, 1979, 1999-2000). Persistence refers to the desire either to complete a task before taking a break or to take many breathers while working on an activity. Motivation is concerned with whether or not a person is internally or externally motivated, whereas responsibility is denoted by whether a person is conforming or nonconforming. Finally, structure involves an individual’s desire for internal versus external direction.
The third stimulus consists of sociological elements that specify whether a person wants to work alone, in pairs, with peers, in a team, or with an adult who is either authoritative or collegial. This stimulus also indicates if a student learns best by working in a variety of ways or with a set routine (Thies, 1979, 1999-2000).
The physiological strand includes perceptual preferences, intake, time of day, and mobility. The four perceptual strengths are: (a) auditory, which refers to remembering what is heard; (b) visual, which is the ability to recall what is read or seen; (c) tactual, the capability to recollect what is written or manipulated; and (d) kinesthetic, which is learning what is physically experienced. The next element of the physiological strand is time of day, which specifies at what time an individual learns best. The last two elements are intake, which indicates whether a person needs to snack while learning, and mobility, which identifies a learner’s need to be pacing, rocking, or changing seating positions at frequent intervals while learning. It should be noted that perceptual strengths and time of day preferences each impact approximately 70 % of all people.
The fifth stimulus strand incorporates the psychological elements of (a) global versus analytic processing, (b) hemisphericity, and (c) impulsive versus reflective behaviors. The elements of hemisphericity and global/analytic processing essentially appear to be parallel (Dunn, Beaudry, & Klavas, 1989). Both refer to a preference for either simultaneous or sequential mental processing. This suggests that global pupils learn most readily when they understand the concept being taught first and then concentrate on details, whereas analytic learners prefer to start with details, so they learn step-by-step in a sequential manner that gradually builds toward a broad conceptual understanding (Dunn, Cavanaugh, Eberle, & Zenhausern, 1982).
Global and analytic learners also have different environmental needs (Dunn, Bruno, et al., 1990). Many analytics are task persistent and prefer to learn steadily and consistently without any breaks or intake, in a traditional classroom setting that is quiet, well illuminated and formal. Conversely, global pupils prefer to work with sound, such as music or background conversation, dim lighting, informal seating arrangements, some form of intake or food and frequent breaks. Many globals also wish to learn with peers rather than alone or with teachers. Both analytic and global learners can master the same material, if they are taught with an instructional method that complements their learning style (Dunn, Bruno, et al., 1990). These preferences can be determined for college students by administering the Building Excellence (BE) survey ( Rundle & Dunn, 1996-2000) or the Productivity Environmental Preference Survey (PEPS) (Dunn, Dunn, & Price, 1979, 1980, 1990, 1996).
Learning-Style Differences and College Students’ Majors
Recent research among college students has demonstrated that students who select certain majors may have distinctly different learning-style preferences from those who major in other fields of study (Loo, 2002; Giordano & Rochford, 2005). In fact, in a meta-analytic examination of Kolb’s learning-style preferences among business majors, Loo (2002) revealed that a high proportion of college business students were assimilators or analytic learners who craved structure. In contrast, he discovered a lower proportion were global thinkers or accommodators than would have been anticipated if the learning styles were distributed equally.
In 2005, Giordano and Rochford revealed that most business majors at an urban community college were analytical learners, who exhibited a strong preference for bright light, a quiet learning environment, and single-task persistence. However, these same students also displayed a strong preference for the two global elements of informal seating and intake.
In view of these findings, two researchers conducted a pilot comparative analysis between two groups of urban community college students who were education majors and developmental/remedial reading and writing students at the City University of New York (CUNY). The purpose of this study was to ascertain if these two groups of students exhibited significantly different learning-style preferences that could have the potential to inhibit or enhance their performance.
The Population
The 176 participants for this research were drawn from two different urban community colleges. The first group consisted of education majors registered in three-credit, college level courses, and the second group was composed of remedial reading and writing students. Since students volunteered to participate, a non-probability (Dictionary of Psychology, 2001) or convenience sample (Wilkinson, 1999) was employed.
Instrumentation
The PEPS (Dunn, Dunn, & Price, 1979, 1980, 1990, 1996) was administered to identify each student’s learning-style preferences. This instrument established good reliability and predictive validity through research studies conducted at the college level in the domains of engineering, law, nursing, and allied health (Boyle & Dolle, 2002; Boyle & Dunn, 1998; Ingham, Ponce Meza, & Price, 1998; LaMothe, Billings, Belcher, Cobb, Nice, & Richardson, 1991; Lefkowitz, 2001; O’Hare, 2002).
In addition to assessing the subjects’ learning styles, students’ grade-point-averages (GPAs), age, and scores on the ACT Compass Reading and the ACT Writing Sample Assessment exams were collected for this analysis. The ACT Writing Sample Assessment and the ACT Compass Reading were designed to measure the fundamental reading and writing ability of students when they enter two-year colleges (CUNY/ACT Test Administration Manual for the Asset Writing Skills and Reading Skills Assessments and ACT Writing Sample Assessment, 2000). The primary goal of this assessment process was to gather information efficiently for each student to develop and implement a sound program of study in preparation for college-level courses. Upon entrance into CUNY, students who received a score less than 7 on the ACT Writing Sample Assessment and/or a score below 65 on the ACT Compass Reading were placed in remedial courses to prepare them for college-level course work.
Research Hypotheses
1 There will be a significant difference in the learning styles of remedial students and education majors (Giordano & Rochford, 2005).
2. There will be no significant differences in the perceptual preferences of the education majors and the remedial students.
3. There will be no significant difference in hemispheric processing style of the education majors and the remedial students.
4. There will be significant differences in the learning styles of the remedial students and education majors based on their achievement levels (Dunn, Griggs, Olson, Gorman, & Beasley, 1995; Giordano & Rochford, 2005).
5. There will be significant differences in the learning styles of the remedial students and education majors based on gender (Dunn, Griggs, Olson, Gorman, & Beasley, 1995; Giordano & Rochford, 2005).
6. No significantly different correlations will be exhibited between the remedial students and the education majors.
A t-test of independent means demonstrated significant differences between the education majors and remedial students: (a) for the learning-style elements of noise, motivation, intake, time of day, tactual learning, and kinesthetic activities; and (b) for GPAs, age, ACT Compass Reading scores, and ACT Writing Sample Assessment scores (see Table 1). These findings suggest that the remedial learners desired a quieter learning environment and late afternoon or evening learning. In contrast, the education majors revealed a need to snack and preferred activities that involve the manipulation of materials and whole body movement.
Table 1
Although the ACT Compass Reading and ACT Writing Sample Assessment scores were significantly higher for the remedial students, the education majors demonstrated significantly higher GPAs. The higher ACT scores among the remedial students may have resulted because of specific in-class preparation they were receiving during the semester this analysis was conducted, and the higher GPAs among the education majors may have emerged because of their significantly higher motivation and age (see Table 1).
These results suggest that community college faculty and educators should offer additional late afternoon or early evening remedial courses, and provide education majors with a variety of tactual and kinesthetic learning activities to prevent passive learning. In addition, counselors should advise remedial students to register for courses at their preferred time of day so that students can maximize their learning potential.
In view of the significant findings, research hypothesis one, which stated there will be a significant difference in the learning styles of remedial students and education majors, was accepted.
A Pearson Chi Square exhibited no significant differences in the perceptual preferences of the education majors and the remedial students, confirming research hypothesis two, which stated there will be no significant differences in the perceptual preferences of the education majors and the remedial students. Approximately 40 % of education majors and 37 % of the remedial students demonstrated a need for auditory learning, whereas approximately 37 % of the education majors and 43 % of the remedial students indicated that their learning was contingent upon their level of motivation (see Table 2). This suggests that instructors in education and remedial courses must be aware that a large percentage of their students prefer to listen and hear information when they learn. Therefore, to accommodate auditory students, teachers should provide activities such as videos, lectures, and discussions
At the same time, professors need to be cognizant that the remaining 60% of the students will not retain three quarters of what they hear in a 45-50 minute period. Thus, instruction should not be solely for the auditory students. In fact, this analysis indicated that another large group of learners required motivation before they engaged in the learning process. This can be accomplished by demonstrating the value of a lesson or the relevance of a topic to their lives at school or work. In addition, teachers can provide incentives for participation and achievement in classroom activities or competitions so that students become actively involved with the course content.
Table 2
Perceptual Preferences by Group
Global versus Analytic Processors
Although a Pearson Chi Square indicated no significant differences in analytic or global processing styles, approximately 11 % of the remedial students exhibited the traits of analytic processors, in contrast to 2.9 % of the education majors . In addition, approximately 21 % of the education majors and remedial students exhibited global traits. Finally, more than 75 % of the education majors and almost 68 % of the remedial students indicated that their processing style was integrated and that they could shift from one style to another depending on their level of motivation (see Table 3).
These findings suggest that most of the education majors and remedial students benefit from being motivated before they engage in the learning process. If they are not, they may not focus, but instead tune out. Thus, it is beneficial to arouse their interest so that they are incited to learn. This could be accomplished by offering a variety of choices for homework, projects or presentations, and by permitting students the option to work alone, in groups or pairs in environments that address their desired level of light, noise, temperature, and room design. These alternatives will remove the burden of students’ feeling coerced into participating in activities that inhibit their learning potential.
Table 3
Processing Style by Group
Thus, the third hypothesis, which suggested there would be no significant difference in the hemispheric processing style of the education majors and the remedial students, was accepted inasmuch as both groups revealed that the majority of the participants had an integrated processing style.
Achievement Levels
To determine the relationship between achievement and learning-style preferences among the participants, a One-Way Analysis of Variance (ANOVA) was performed based on achievement levels of (a) low for GPAs below 2.2, (b) medium for GPAs between 2.2 and 3.5, and (c) high for GPAs greater than 3.5. Among the education majors, a significant difference was exhibited for the learning-style element of temperature (p <.01). After a Tukey HSD procedure was performed, it was determined that the education majors who were high and medium achievers preferred warmer temperatures than low achievers (see Table 4). These findings contrasted with those of Giordano and Rochford (2005) who ascertained that high and medium achieving community college business students preferred cooler temperatures. It should be noted, however, that since the PEPS (Dunn, Dunn, & Price, 1979, 1980, 1990, 1996) element for temperature did not quantify temperature ranges for warm or cool, individual students’ interpretations of these conditions may vary based on their background and culture. To address the students’ need for a particular temperature, professors can encourage students who require warmth to wear layers of clothing or to sit near a heating vent or radiator, whereas students who desire a cool environment should wear lighter clothing and sit near an open window or air conditioner.
This study also revealed that remedial students’ age varied according to their level of achievement. High achievers had a mean age of 24.75, whereas low achievers’ mean age was 20.75 (see Table 4). It could be theorized from these findings that the more mature remedial students are more motivated and have acquired life experiences and skills that enable them to perform better in college, whereas the younger students may have entered college because of the expectations of their parents or society.However, it is recommended that this outcome be replicated with a larger population to verify its accuracy.
Table 4
Tukey HSD Results for Achievement Levels
Thus, hypothesis four, which stated t here will be significant differences in the learning styles of the remedial students and education majors based on achievement levels, was accepted because significant differences were evidenced in temperature preferences.
Learning Styles and Gender
A t-test of independent means indicated that the male education majors were less conforming than females (p <.05), and these results corroborated the findings of Giordano and Rochford (2005). It is essential to identify and effectively deal with non-conformists because they frequently declare the opposite of what an instructor states (Dunn & Dunn, 1999) and create discord in the classroom. Sometimes their behavior appears to be irresponsible, but it typically results when they believe regulations or assignments are arbitrary or capricious. Therefore, non-conformists need to understand why a task is important, and respond well when offered choices as to whom they will work with and with which resources they will learn. In addition, they prefer collegial interactions with instructors. Therefore, if professors employ a highly authoritarian approach, it may result in unnecessary classroom disruptions and lower performance among this population. In contrast, these suggestions can maximize learning and create a positive classroom environment for all students.
In the remedial students’ group, the females exhibited a significantly greater desire to participate in varied learning experiences than their male counter-parts (p <.05). This implies that remedial female students find a daily classroom routine monotonous and tedious. Consequently, they become distracted or anxious, and cannot learn effectively. However, when the same students are offered a variety of learning activities, they become stimulated to learn. This need can be addressed by providing an assortment of tasks that range from occasional teacher-centered lectures, small group work, individual assignments and projects, and/or instructional presentations that employ multi-media.
In summary, research hypothesis five was accepted inasmuch as significant differences in learning-style preferences by gender were exhibited for the education majors and the remedial students.
Correlational Analyses
For the education majors, a Pearson’s correlational analysis revealed significantly moderate correlations for the learning-style elements of persistence, motivation, authority, design, mobility, conformity/responsibility, global/analytic, and motivation (see Table 5). The moderate correlations between persistence and motivation (.403) and persistence and conformity (.506) suggest that as the education majors’ level of persistence increased, so did their motivation and need for conformity. These results imply that when education majors are highly task persistent and conforming, they also have a strong desire to learn and perform well. Therefore, when instructors identify these qualities in a student, if possible, it is wise to provide such students the opportunity to complete new topics, assignments, or projects all at once because this is how these future teachers become stimulated and maximize their learning. In contrast, if these learners are expected to divide their assignments into separate activities to be completed at different times, they may become frustrated and discouraged.
Another moderate correlation (.491) was discovered between the learning-style elements of authority and alone/peers. This relationship implies that the more these learners desire to have an authority figure present, the more they also want to work with peers. Thus, although these students may enjoy group work, they desire the guidance of their professors during activities.
Table 5
Pearson Correlational Analyses for Education Majors
A negative correlation between room design and global/analytic traits (-.405) suggests that the more global a student is, the less he/she desires a formal classroom design. An instructor can address this need by permitting global learners to work in small groups or set up informal work stations inside or outside the classroom where they can complete group work or in-class assignments.
Finally, another moderate correlation was demonstrated between mobility and intake (.400). This association suggests that learners who require frequent movement also need to snack. This necessity can be accommodated by permitting students to stand up and move during class as long as they don’t disturb others and by permitting them to eat neatly in the classroom while they learn.
In contrast to the education majors, a Pearson’s correlational analysis revealed distinctly different correlations for remedial students. Data analyses indicated that as students’ scores for auditory learning increased, so did their need for the learning-style elements of (a) motivation, (b) persistence, (c) structure, (d) tactual learning, (e) kinesthetic activities, and (f) intake (see Table 6). Although traditional college classes are conducted in a persistent, structured, lecture format, these correlations imply that remedial students with high auditory scores may require more than just a sage on stage lecture experience. That is some of these learners might desire snacks, tactual lessons, and/or kinesthetic activities such as academic competitions or computerized tasks because these activities will enhance their ability to learn.
Next, moderate correlations were demonstrated among visual learners for the elements of (a) noise, (b) persistence, (c) structure, (d) tactual tasks, (e) kinesthetic activities, (f) late morning classes, and (g) mobility (see Table 6). These associations suggest that the more visual a student is, the more likely he/she is to benefit from structured, persistent learning, background noise, the manipulation of objects, and/or movement during class. These requirements could be met by permitting remedial students to (a) listen to instrumental music with headphones while they work, (b) create or participate in computerized activities and lessons, and (c) perform activities that permit students to change positions during class such as group work or academic games.
Table 6
Pearson Correlational Analyses for Remedial Students
Moderate correlations for (a) noise, (b) motivation, (c) persistence, (d) structure, (e) kinesthetic learning, (f) intake, and (g) mobility were exhibited for tactual students (see Table 6). These relationships suggest that many tactual remedial students are non-traditional learners who require intake, mobility, and high levels of background sound. However, they are quite motivated and persistent, and may require sequential step-by-step learning that doesn’t include breaks.
Finally, kinesthetic learning correlated positively with the elements of (a) noise, (b) intake, (c) mobility, (d) tactual learning, (e) structure, (f) persistence, (g) motivation, and (h) late morning or afternoon classes (see Table 6). Although these learners are also non-traditional because of their strong desire for background noise, snacks, movement, and the manipulation of objects, many are motivated and crave a structured, persistent learning environment. Therefore, it is important for the professor to provide an orderly well-defined classroom atmosphere that permits students to move, eat, and listen to music with headphones, while they simultaneously provide lessons such as large puzzle boards or floor games that permit students to engage in whole body movement and the use of their hands.
These analyses have revealed that education majors and remedial students possess significantly different correlations among the learning-style elements. Therefore, research hypothesis six, which indicated that there would be no significantly different correlations between the education majors and remedial students, was rejected.
Infusing Learning Styles in College Learning
Since many college-level courses have a required curriculum, professors are sometimes unable to alter the traditional lecture method of instruction, inasmuch as they are expected to cover specific course content. Despite this reality, minor modifications can be incorporated into classes, and students can be taught how to learn and study in ways that are congruent with their learning styles. The first step is to test students for their learning styles, and this can be accomplished by administering the PEPS (Dunn, Dunn, & Price, 1979, 1980, 1990, 1996) or the BE ( Rundle & Dunn, 1996-2000). Next, professors should have their learning styles assessed because self-knowledge is an essential part of developing flexible, varied approaches to learning, inasmuch as teaching strictly in a style compatible with the instructor’s preferences can obstruct learning (Terregrossa & Englander, 2000).
Next, students should be provided interpretations of their learning styles or homework prescriptions that explain the ways in which they learn best, so that they study with methods compatible with their learning-style preferences. For instance, a tactual learner who enjoys working with peers might benefit from re-writing class notes on a computer and then discussing or sharing the files with other students. This study method would permit a non-auditory student to obtain a complete set of notes that he/she will recall easily because of the social interaction and the tactual act of typing them. Kinesthetic learners could occasionally present new material in the form of a videotape or a simulation, so that they become engaged in the act of autonomous self-teaching, instead of sitting passively. Also, they could study while on a treadmill or by reading notes they’ve hung around their home. Visual learners might enjoy reading about a new topic or watching a video to develop schema before they hear a lecture, and some benefit from drawing pictures or symbols in their notebooks. What is most important about each of these recommendations is that it places the burden of responsibility on the students because they begin to understand how they can learn and study effectively, despite a lecture-style class format.
To address the students’ environmental needs, professors could experiment by only turning on lights in certain sections of the classroom to accommodate students who need dim lighting. In addition, learners who require warmth should be encouraged to wear layers of clothing or to sit near heating vents, while those who desire cool temperatures will prefer to be near an open window or an air conditioning unit. During exams, students can use headphones to listen to music to block out sound that might interrupt their thoughts.
Some learners also desire intake and mobility during class. If possible, instructors should allow these individuals to snack neatly, or move around their work area, as long as others are not disturbed. In addition, people who require mobility are ideal participants for teacher student demonstrations, blackboard work, and role plays.
It is also important for instructors to realize that although certain learners crave social interaction, others dislike it. Thus, students should have the option to work alone, in a pair, or in a team. Moreover, even though many students enjoy the presence of an authority figure or an expert when they learn, other pupils demure when the professor joins their group or speaks to them individually. Therefore, certain learners prefer to work with their peers or with a tutor when they are confused or require individualized attention.
To address the needs of reflective learners, some professors permit students to write down their thoughts before a class discussion. This technique also allows the impulsive students to organize their ideas so that they express their thoughts more clearly.
To deal with non-conformists, instructors can offer choices in assignments or classroom activities so that students have the opportunity to select tasks that suit their needs. In addition, when students crave structure, they should receive rubrics and detailed syllabi with grading criteria, so that they understand how their work will be graded.
Since people are alert and ready to learn at different times of the day, counselors and academic advisors might recommend students register for difficult courses during their preferred time-of-day. Whenever possible, advisors should also steer analytic students into difficult classes with professors who are very structured and sequential, while global students should seek instructors who take a more holistic approach to teaching.
According to the Illinois Community College Board (2005), community colleges enroll the highest proportion of (a) low-income urban youths, (b) immigrants, and (c) minority groups. Therefore, these institutions are at the forefront of a national effort to decrease poverty, improve living standards, and compete globally, by preparing and retraining the students with the least opportunities to meet the demands of an ever-growing technological worldwide market. However, the fact remains that less than 63 % of community college freshmen return for a second year (National Center for Public Policy and Higher Education, 2004), and this statistic suggests that traditional pedagogical methods used in college courses are not effective in addressing the needs of this new, more diverse population.
Despite prior research that has demonstrated improvements in academic achievement and retention when college students are taught with methods that address their individual learning styles (Clark-Thayer, 1987; Dunn, Deckinger, Withers, & Katzenstein, 1990; Ingham, 2003; Lenehan, Dunn, Ingham, Murray, & Signer, 1994; Miller, 1998; Nelson et al., 1993; Ingham, 2003; Rochford, 2004c), many college educators continue to rely on traditional methods because they believe it produces achievement as long as the students are motivated and apply themselves. However, research on learning styles has revealed there is no one, single correct teaching method. In fact, an approach that is highly effective for one person may be completely inappropriate for another. Therefore, it is important that community college educators understand the diverse ways in which their students learn and adjust their pedagogy so that every student can maximize his/her learning potential.
Clearly, the present trends in college degree attainment in this country are a concern. Although this topic has been greatly debated and a variety of traditional programs have been tested, few have had consistent success, except for learning styles. Therefore, it is time to reevaluate the methods used to instruct college students because too many freshmen fail to return to college after their first year since they don’t understand the ways in which they learn best and their professors don’t know how to accommodate their diverse learning styles.
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