Summer 1993 // Volume 31 // Number 2 // Research in Brief // 2RIB1
Agents' Learning Preferences
Abstract
Our study examined Extension staff members' learning style preferences and how they vary across primary assignment areas as a basis for designing inservice training and professional development activities.
In the process of thinking, responding to stimuli, and using a variety of resources and methods while learning, people develop personal tendencies and preferences, or learning styles. Learning styles are characteristic ways of processing information, feeling, and behaving in learning situations. Our study examined Extension staff members' learning style preferences and how they vary across primary assignment areas as a basis for designing in- service training and professional development activities.
Methodology
All 299 Pennsylvania Cooperative Extension county staff members received a letter explaining the study, a brief questionnaire relating to their professional position, and the Kolb Learning Style Inventory (LSI). The results apply to the 211 (71%) people providing usable responses after one mailing (no follow-up).
The LSI is founded on Kolb's experiential learning theory that includes the concepts of learning and individual development.1 An individual's results on the LSI determine his or her classification as a converger, diverger, assimilator, or accomodator. Convergers prefer dealing with technical tasks and problems and doing things rather than dealing with social and interpersonal issues. Divergers are feeling-oriented, interested in people, and emphasize concrete experiences and reflective observations. An assimilator uses inductive reasoning, is less focused on people, and more concerned with judging ideas by theoretical precision rather than by practical value. Accomodators prefer concrete experiences, doing things, completing tasks, and being involved in new experiences.
Six of every 10 staff members participating in the study were male (57%), and the majority of these males (81%) had primary program assignments in agriculture. County directors were primarily males (70%), as were 4-H/youth development agents (59%); 93% of the family living agents were female. Agents in each of the three program areas averaged 14 years service and county directors averaged 21 years of Extension experience.
Learning Style Preference Results
Family living agents had the smallest percentage of staff members (16%) identified as having a converger learning style preference. Forty-four percent of family living agents had an accomodator learning style, about twice as many as in any of the other learning style categories. Agricultural agents were identified most frequently as having the assimilator (31%) or converger (32%) learning styles. County directors were almost evenly split between converger (32%), accomodator (27%), and assimilator (24%) learning styles, with the diverger (19%) learning style occurring the least. The 4-H/youth development agents came closest to mirroring the collective group of staff members in terms of percentages of agents across the four learning styles (see Table 1). More than half (55%) of the agents in all groups were either convergers (26%) or accomodators (29%) who prefer a learning situation where the teacher is a role model showing them how to do things.
Table 1. Extension personnel by area of assignment1 and learning style. | ||||
---|---|---|---|---|
Area of assignment | Learning style | |||
Accomodator | Assimilator | Converger | Diverger | |
Agriculture (n=75) | 20% | 31% | 32% | 17% |
4-H/youth (n=46) | 30 | 28 | 24 | 18 |
Family living (n=45) | 44 | 20 | 16 | 20 |
County director (n=33) | 27 | 24 | 30 | 19 |
All agents (n=199) | 29% | 27% | 26% | 18% |
1. Area of assignment was determined by having a majority of their total time assigned to the respective area. Twelve agents didn't have one major program area commitment. |
Implications
Knowing agents' learning preferences can be useful in deciding how to use instructional technology for inservice training. For example, agents who are convergers or accomodators generally prefer to have a person delivering the inservice training rather than learning the information through the use of computer-assisted instruction. Where computer-assisted instruction is used with these agents, it needs to be interactive, allowing them to practice and receive feedback. Such an approach focuses on their preferences for active involvement, learning by doing, solving problems, and making decisions. For these agents, computer-assisted instruction works best if several agents can work as a team, interacting with the instructional package and discussing the solutions to problems posed. Agents with assimilator learning preferences are adept at working individually in an interactive, computer-assisted instruction mode. Both the assimilator and diverger would use inductive reasoning in developing solutions to the "big picture" presented in the computer-assisted instruction mode.
From a management perspective, having a sense of agents' learning preferences is especially useful in forming work teams and communicating with individuals on those teams. For example, agents serving on an Extension strategic planning team who have preferences as assimilators may contribute to a team by "seeing the big picture" and bringing together smaller components into a cohesive whole. Agents who are convergers or divergers are especially valuable in helping the group generate new ideas and helping the team look at programming from different perspectives. Divergers are concerned with how people are affected by the strategic plan and how that's communicated to the people. Accomodators on the strategic planning team help put the plan into action and bring to the team an emphasis on getting things done and moving ideas into practice.
One goal for using information from this study was to enhance state Extension staff members' knowledge about learning preferences of the agents with whom they interact. Learning preference information about agents helps state staff in Pennsylvania organize educational experiences for agents which increases the organizational capacity for delivering Extension programming.
Footnote
1. David A. Kolb, Learning Style Inventory (Boston, Massachusetts: McBer and Company, 1985).