Knowledge management and learning styles: prescriptions for future teachers

Knowledge management and learning styles: prescriptions for future teachers

Joseph Stevenson

This manuscript presents a framework for teaching diverse college students who are studying to become teachers. On the basis of learning-style preference, the authors identify a model in which one of either of the two prototype reliable and valid instruments could be designed for multicultural students at the pre-collegiate and post-secondary levels. Based on earlier research cited by the authors, the essay reports the results of experimental studies as a potential model, in which undergraduates were randomly selected from a total population of first-time, full-time freshmen and transfer students. Many of these students could be “knowledge management oriented” teachers for the nation’s growing multicultural schools.

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Chancellor Joe Wyatt of Vanderbilt University recently remarked, “our nation’s future depends on a high-quality public education system and a superior force of educators”. There is no more important work (Darling-Hammond). Three compelling demographic shifts in the American college classroom provide the genesis for this essay. First, the nation’s public schools, particularly those in urban venues, have become profoundly multicultural. Second, there has been a steadfast emerging need to staff the nation’s teaching force. And third, colleges and schools of education are challenged with replacing a retiring teacher education labor force with new professors who must be capable of responding to the first two demographic shifts. In Miami, Florida International University provides 30% of the teachers for the local school systems in a state that, coincidently, has a 30% illiteracy rate. Miami, like most modern urban venues, is a multicultural metropolis with rich diversity among students enrolled in public and private schools at all levels. Perhaps recognizing this and other socio-economic implications, the Florida Assembly passed legislation requiring schools to examine learning styles. This essay suggests that teaching college students who currently, or might, major in teacher education to learn about their own diverse learning styles is a prudent way to empower these future teachers with knowledge about multicultural learning styles among the children and youth enrolled in our increasingly challenging public schools. Not only is this knowledge transfer and relationship pedagogically sound, it could no doubt manifest into a relationship to sustain learning improvement and academic achievement. In this context, teachers can become both effective and efficient managers of their knowledge about multicultural learning. In an informal survey completed by one of the authors in a graduate level class for two dozen teachers who were earning a masters degree in urban education, most of the teachers, who were either Black (African descent) or Hispanic (Latin descent) American, felt they were unaware of their learning styles in elementary or secondary levels, but knew of their learning styles in college. Most of these teachers also indicated that they had either Black- or Hispanic. American students in their classrooms, which were predominately at the elementary and middle school levels. These authors hypothesized that our nation’s aspiring multicultural teachers and their multicultural students would become better managers of the information they gained from the transfer of explicit knowledge (lesson plans and other instructional materials) and tacit knowledge (in the heads of teachers), if they both could have a fundamental understanding of each other’s learning style. The term “knowledge management” is commonly used in the corporate sector for explaining organizational learning and investing in intellectual capital. It has direct applicability to the educational setting. Teachers could, indeed, develop prescription-based lesson plans through an analysis and the results from this “knowledge transfer” and relationship-building process. In academic terms, this is the locus of control or the unit of analysis. Where students and teachers share ethnic and cultural commonalities, there could be a profound effect on the relationship. Where there are no apparent similarities, this exercise would be an excellent opportunity for teachers to explore the plethora of research, theories and developments in multicultural diversity and classroom dynamics. This is particularly important to note as many of the nation’s future teachers will be ethnic minorities. Minority freshmen often are somewhat deficient in the English language and appear to be less prepared academically than majority students on American campuses (Mentzer, 1993). American colleges and universities also have been enrolling increased numbers of foreign students and mid-life adults who currently are attending college to move into new careers (Dunn, Ingham, & Deckinger, 1995). The differences in age, experience, culture, and language skills among traditional high school graduates, minority and foreign students, and career-changing adults in their 40s and 50s suggest a diversity that is unlikely to find any single teaching style effective. And, although teaching styles may differ, many professors tend to teach in one unique pattern with only infrequent variations (Frazier, Primavera, & Dunn, 1995). Although many K-12 teachers and college professors “teach like they have been taught”, our current times call for new pedagogy and instructional delivery systems. When our clients change, we must change with them so that heuristic goals can be met. College and university; professors have experimented with instructional approaches, such as case studies, cooperative learning, group processes, independent studies, role playing, and simulations to enable students to improve academically (Clay, 1984; Katz & Henry, 1988; Roach, 1994). These practices, for the most part, have proven ineffective with at-risk students (Clark-Thayer, 1987; Cook, 1989; Dunn, Bruno, Sklar, Zenhausern, & Beaudry, 1990; Mickler & Zippert, 1987). Thus, this manuscript will synthesize the effects of learning-style-based instruction and technologically-generated study prescriptions on students’ achievement and retention. This is important as colleges and universities strive to develop creative means and methods to recruit students in teaching and retain them throughout their undergraduate and graduate experiences. In fact, college students should become more excited about learning by embracing a learning style that will not only help them in their teacher education and training programs, but in the cognitive development of their critical thinking skills for other academic areas as well. Retention is a critical problem for many institutions of higher education (Smith, 1989) and because these individualized approaches are easy to implement (Dunn, Deckinger, Withers, & Katzenstein, 1990), they may be of interest to other college teachers. Given the demography of the nation’s educational system, many of these at risk students range in diversity relative to race, class, ethnicity, and gender.

What Is Learning Styles

According to Dunn and Dunn (1993), learning style is the way each individual begins to concentrate on, process, internalize, and remember new and difficult academic information or skills. Students at the collegiate and pre-collegiate levels are in a better position to manage the knowledge they gain by developing a prescription for learning. Although many students can master easy information in the “wrong” style for them, they do so more efficiently and rapidly when they capitalize on their learning-style strengths.

Learning styles vary with (a) age (Price, 1980), (b) achievement level (Milgram, Dunn, & Price, 1993), (c) culture (Dunn & Griggs, 1995; Milgram, Dunn, & Price, 1993), and (d) global versus analytic processing (Dunn, Bruno, Sklar, & Beaudry, 1990; Dunn, Cavanaugh, Eberle, & Zenhausern, 1982). Regardless of these variables, in every family, mothers and fathers tend to have almost opposite styles. First-born children reveal characteristics of one of their parents; second-born children evidence characteristics of the other parent. The third child in each family has a style very different from both older siblings, and it is very likely that all three learn differently from each other.

Dunn and Stevenson (1995) earlier referred to learning style in terms of each person’s ability to master new and difficult knowledge

1. environmentally (with either sound versus quiet; soft versus bright light; warm versus cool temperatures; or formal versus informal seating),

2. emotionally (through consistent versus inconsistent motivation, persistence, conformity or non-conformity, and with either internally or externally imposed structure),

3. sociologically (alone, with peers, with either a collegial or authoritative teacher, and/or with varied approaches as opposed to in patterns or routines),

4. physiologically (auditorially, visually, tactually, and/or kinesthetically; with identifiable time-of-day energy highs and lows; with or without intake; and by sitting for long periods of time versus by frequently moving from one location to another), and

5. globally versus analytically as determined through correlations among sound, light, design, persistence, sociological preference, and intake (Dunn, et al., 1982; Dunn, et al., 1990) (see Figure 1).

[FIGURE 1 OMITTED]

Research on Learning-Style Approaches for College Students

When researchers first experimented with learning-style prescriptions for teaching college students, significantly higher achievement resulted. Those gains were evidenced in anatomy (Cook, 1989; Lenehan, Dunn, Ingham, Murray, & Singer, 1994), bacteriology (Lenehan, et al., 1994), marketing (Dunn, Deckinger, Withers, & Katzenstein, 1990), mathematics (Dunn, Bruno, Sklar, & Beaudry, 1990), physiology (Lenehan, et al., 1994), across subjects (Clark-Thayer, 1987, 1988; Mickler & Zippert, 1987), and for overall grade-point averages (Nelson, Dunn, Griggs, Primavera, Fitzpatrick, & Miller, 1993).

For example, Clark-Thayer (1987) identified underachieving, college freshmen’s learning styles with the Productivity Environmental Preference Survey (PEPS) (Dunn, Dunn, & Price, 1982). Trained tutors were assigned to teach freshmen to study with strategies that complemented their learning-style preferences. In a subsequent study, Clark-Thayer (1988) described students’ significantly higher achievement and attitude scores toward course content after they had studied with congruent, rather than incongruent study strategies.

Later, Dunn et al. (1990) identified the processing styles of 1,000 minority college students in remedial mathematics classes with the PEPS. Most of these developmental minority students were global processors. The textbook assigned to the class was written in a step-by-step analytic style in which procedures were itemized but no direct applications were provided. The researchers re-wrote alternate textbook chapters in a global processing style and kept the alternate analytic chapters intact. Students were required to study all the revised global chapters and all the existing analytic chapters by themselves-with no direct teacher instruction. Requiring the students to teach themselves (a) eliminated the possible intervention of different teacher’s teaching styles and (b) resulted in significantly higher test scores (p<.001) on each of the chapters that matched, rather than mismatched, individuals' global learning styles.

Nelson, et al. (1993) identified individual freshmen’s overall learning styles with the PEPS and provided directions for studying with complementary strategies. The matched prescriptions impacted significantly on student achievement (p>.01) and retention (p>/01) to the point where the college’s annual dropout rate was reduced from 39 percent to 20 percent. Those results were particularly meaningful in light of Demitroff’s (1974) and Trent and Rhyle’s (1965) earlier findings that poor study habits resulted in inadequate student scholastic performance and led to either voluntary or involuntary withdrawal for college.

Instrumentation

Both the Learning Style Inventory (LSI) (Dunn, Dunn, & Price, 1975, 1979, 1985, 1989, 1991) for non-traditional college: students and the Productivity Environmental Preference Survey (PEPS) (Dunn, Dunn, & Price, 1982, 1989) for traditional college students, consist of 100 statements that elicit self-diagnostic responses on a five-point Likert scale in approximately 25 minutes. Data collected from those assessments yield a computerized profile of each student’s preferred learning style based on the elements itemized above. As early as 1979, Kirby reported that the LSI and the PEPS had “established impressive reliability and face and construct validity” (p. 72). Since then, both have evidenced predictive validity (Dunn, et al., 1990; Dunn, DellaValle, Gelsert, Sinatra, & Zenhausern, 1986; Lenehan, et al., 1994; Nelson, et al., 19930. More recently, a meta-analytic study of 42 experimental studies with the Dunn and Dunn Model conducted between 1980-1990 by 13 different institutions of higher education, revealed that students whose characteristics were accommodated by educational interventions responsive to their learning styles could be expected to achieve 75% of a standard deviation higher than students whose styles were not accommodated (Dunn, Griggs, Olson, Gorman, & Beasley, 1995).

Both instruments are easy to administer and interpret and have been used in research by almost 120 institutions of higher education (Research on the Dunn and Dunn Model, 2001). For each element for males and females, the mean, standard deviation, reliability and standard error was calculated. The Hoyt (1941) analysis of variance procedure was used to estimate reliability for each subscale and was deemed equivalent to the Kuder and Richardson (1937) formula (2) procedure. Hoyt reliability coefficients for the elements fall into the .75 to .88 range (Price, Dunn, & Dunn, 1991). The elements with the highest reliabilities included noise level, light, temperature, design, motivation, persistence, responsibility, structure, learning alone/peer-oriented, authority figures present, wanting variety versus wanting routines and patterns, perceptual preferences, requiring intake evening/morning/ afternoon chronobiology, needing mobility, and parent and/or teacher motivation.

Translating Individuals’ Learning Style Traits Into Prescription for Studying

Dunn, Klavas, and Ingham (1990) developed a software package to analyze each individual’s preferred learning style based on the Dunn, Dunn, and Price LSI computerized profile. First, student’s learning styles are identified with either the LSI or PEPS. Then each students’ style is analyzed for “strengths” and converted by software package into a series of directions for studying and doing homework based on each individual’s “strong preferences” (scores of between 20-29 or 70-80 on LSI) and “preferences” (scores of between 30-40 or 60-69 on the LSI). Each person’s set of directions is called his/her “Homework Prescription.” Nelson, et al., (1983) reported increased achievement for community college students who studied with prescriptions based on their learning-style strong preferences. Lenehan et al., (1994) revealed that using the Dunn, Klavas, and Ingham learning-style homework prescriptions (a) increased achievement and curiosity and/or (b) reduced anxiety and anger when learning science.

Recommendations

Non-traditional and poorly-achieving students are particularly vulnerable to academic failure despite the availability of conventional college tutoring and advisement. Adults returning to college after many years away from traditional learning may also have adjustment problems. These diverse students may have an additional hurdle to handle when their professors try to teach an entire class of very different-from-each-other learners identically. By identifying students’ learning styles and providing each with a structured outline for studying based on their personal characteristics, it may be possible to either avoid-or reverse-academic failure for many.

Therefore, college faculty and PreK-12 teachers should consider the following alternatives.

1. Identify your learning style and the learning-styles of all students in one course with the LSI (for non-traditional students) or the PEPS (for all other post-high school adults). Explore differences and similarities.

2. Provide students with a Homework Prescription, encourage them to follow it, and request an honest report concerning whether individuals did, or did not.

3. Examine the effect(s) of following Homework Prescription on students’ grades, attitudes, and attendance.

4. Identify your own teaching style and determine the relationship between students’ grades and the match or mismatch of students’ learning and the professor’s teaching style.

References

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Dunn, R., DellaValle, J., Dunn, K., Geisert, G., Sinatra, R., & Zenhausern, R. (1986). The effects of matching and mismatching students’ mobility preferences on recognition and memory tasks. Journal of Educational Research, 79(5), 267-272.

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Milgram, R.M., Dunn, R., & Price, G.E. (Eds.). (1993). Teaching and counseling gifted and talented adolescents: An international learning-style perspective. CT: Praeger.

Nelson, B., Dunn, R., Griggs, S.A., Primavera, L, Fitzpatrick, M., & Miller, R. (1993, September). Effects of learning-style intervention on college students’ retention and achievement. Journal of College Student Development, 34(5), 364-369.

Price, G.E., (1980). Which learning-style elements are stable and which tend to change over time? Learning Styles Network Newsletter, 1(3), 1.

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Author’s Notes

Joseph Stevenson is a professor at Florida International University and Rita Dunn is a professor at St. John’s University, New York 11439. For information: Contact Dr. Rita Dunn (718) 990-6335/6.

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