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Technology instruction to target women and minorities Julio Garcia & Patricia Backer Department of Aviation and Technology San Jose State University Goals Summarize key research on learning styles with women and minority students
Julio Garcia & Patricia Backer
Department of Aviation and Technology
San Jose State University
Kolb describes learning style within a two-factor model. The perceiving factor, which Kolb defines as how one takes in or processes experience, ranges from Concrete Experience (CE) to Abstract Conceptualization (AC). The second factor is how one processes information; this ranges from Active Experimentation (AE) to Reflective Observation (RO). A combination of scores on the CE-AC and AE-RO scales classifies the learner into one of four learning styles.
active/reflective--An active learner learns by trying things out and enjoys working in groups while a reflective learner learns by thinking things through and prefers to work alone or with a single individual.
sensing/intuitive--A sensing person is a concrete thinker, is practical, and oriented towards facts and procedures; and an intuitive person is an abstract thinker, innovative, and oriented toward theories and underlying meanings.
visual/verbal--A visual learner prefers visual representations such as diagrams, pictures and flow charts and a verbal learner prefers written and spoken explanations.
sequential/global--A sequential learner uses a linear thinking process and learns in small incremental steps while a global learner uses a holistic thinking process and learns in large leaps.
Felder and Spurlin (2005) summarized the data from ten student populations at six institutions (three at Ryerson, two at Tulane, and one each at Kingston, Iowa State, Limerick, Michigan, and Michigan Tech).
“Undergraduate engineering students at a variety of institutions are therefore more consistently more active than reflective and more sensing than intuitive, much more visual than verbal, and more sequential than global” (p. 109)
Despite the many, sometimes contradictory types of learning styles model available, there are some general conclusions that appear to be true (O’Connor, 1997).
There were two research questions in this study:
This research was focused on surveying students who had taken most if not all of their BSIT classes. All seniors in the Industrial Technology program at San Jose State University were surveyed in Spring 2002 using the Kolb Learning Style Inventory.
A total of 52 students returned the survey; this represents a 34% return rate.
Hlawaty (2002, p. 8) also found gender differences in learning styles among 869 German adolescents. German women preferred to learn with more variety than did men, “they need more options regarding educational scenarios, including working independently, in pairs, with peers, in larger groups, and with teachers.”
In an international study of learning styles and gender, Honigsfeld and Dunn (2003) investigated gender differences of 1,637 adolescents from five countries (New Zealand, Sweden, Bermuda, Brunei, and Hungary). Although there were different gender differences found by country, three elements (self-motivation, persistence, and responsibility) were common to all countries.
McShannon and Derlin (2000) analyzed the learning styles of 515 undergraduate engineering students in three universities in New Mexico to see if there were any differences in how students perceive they learn best. In their research, they focus on students’ interaction styles rather than their learning styles.
McShannon and Derlin (2000) found that interactive learning styles differed among ethnic and gender subgroups. Student who traditionally are most successful in undergraduate engineering classes (white students and senior students), use the interactive learning style. That is, they most often learn by themselves. In contrast, “learning with other students contributed most highly to minority student success…”
Behm et al (1996), through the NSF-funded Pac-TECH project, conducted research with teachers from elementary to university level to analyze why “some students are uncomfortable with science, mathematics, engineering, and technology.” The researchers focused on four underrepresented groups in these fields: African Americans, Hispanics, Native Americans, and women.
The researchers proposed criteria or specifications that could be used in classrooms and gave examples of how teachers can apply these criteria to their classrooms.