"Forms of Communication and Individuals that Influenced Freshmen"
280 Factors Influencing Career Choices of Urban Agricultural Education Students Discussant Remarks: William G. Camp Cornell University The researchers conducted a follow-up study of the graduates of an urban high school agricultural education program approximately ten years after they completed the program. To attempt a follow-up of high school graduates is always a difficult task, but to attempt a follow-up on a population that has been out of school for a decade is a most intimidating task. The researchers should be commended for their willingness to undertake this study. The research sought to determine the factors that affected the subsequent educational and career choices of graduates of the program. In particular the study was intended to determine the factors that influenced the graduates to choose or not to choose a career in the field of agriculture. A census of the graduating classes over a three-year period was attempted using a mailed survey, with a 24% response rate. Early-late comparisons were made in lieu of a follow-up of non- respondents. The researchers used discriminant analysis to try to determine if career choice could be explained by the factors under study. The rationale for the study is well conceived. The design and research methods are appropriate. The theoretical framework is appropriate and ties in very nicely with the study but let me suggest that you also examine Donald Super’s Career Development Theory from the 1950s, 60s, and 70s. Although that work is very old, I believe that you will find his theory explains the outcomes of your study almost perfectly. The paper is well written and the conclusions and recommendations flow logically from the findings. The topic of the study is an important one and the researchers should be commended for studying an area that has not been adequately examined in our profession in the past. The use of discriminant analysis was ingenious but the failure to find meaningful predictability was unsurprising, given the near-randomness of career choice for so many young people. Some points to consider: 1. Early-late comparisons can be useful in controlling for non-response error in many studies, but I suspect that this is a special case. You should be able to secure limited demographic data from school records. If race and gender are available, a simple comparison might tell us whether the respondents and non-respondents are really alike. If the self-reported grade point averages are accurate, you received completed surveys from a very selective subset of the population. 2. Surveys are a convenient way to get input from large numbers of people and to provide clean descriptions. On the other hand, surveys are notorious for being simplistic and for failing to get at the underlying reasons for complex behaviors. What might we find by tracking down even a limited number of the non-responders and conducting in-depth interviews? 3. Many factors affect career choice, including random chance. a. Did the school provide career placement services? If so, what effect did that service have on career choice? b. Many young people choose to remain near home when seeking employment. What was the geographic distribution of your respondents? What effect has geographic dispersion had on your ability to contact graduates? How did that dispersion affect career choice? c. The availability of jobs may be the most important single factor in career choice for most youngsters. To what extent were agriculture-related occupations even an option for the average graduate from the school ten years ago? 281 Forms of Communication and Individuals that Influenced Freshmen Students When Selecting an Agricultural Education Major and a College of Agriculture Discussant Remarks: William G. Camp Cornell University The authors developed a survey to measure the impact of various forms of communication and individuals on student decisions to major in agricultural education or to attend a college of agriculture. The survey represented a modification of similar instruments used in previous studies and was appropriately validated for this study. The population for the study was limited to the University of Minnesota and was further limited to incoming freshmen who attended the summer freshman orientation in 2002. The survey was administered during orientation so the data collection was a census with an apparent 100% response rate. The analysis was descriptive in nature and included appropriate measures of frequency, means, and standard deviations. The rationale for the study is well conceived. The theoretical framework is based on Chapman’s (1981) model of student college choice and considers a number of related studies conducted in agricultural education in recent years. The design and research methods are appropriate. I could not determine if the instrument was field tested before the data collection. The paper is well written and, the conclusions and recommendations flow logically from the findings. The topic of the study is an important one and the researchers conducted an applied study that can have direct and immediate application in their university. Some questions to consider: 1. In my experience, not all students who eventually matriculate actually attend the freshman orientation and not all potential students who attend orientation actually enter the freshman class. Would we find differences between the students attending freshman orientation and those who actually begin study as freshmen? Would transfer students be different than incoming freshmen? 2. A large proportion of applicants are offered admission to a particular program and college but, for any number of reasons, never matriculate as freshmen. How might we expect their perceptions to differ from those who do matriculate? More importantly what could members of agricultural education programs and colleges of agriculture do to increase the effective “yield” from those students who apply and receive offers of admission? 3. The purpose of this study was to determine why incoming freshmen chose agricultural education and the college of agriculture. Do we also need to know why transfer students choose agricultural education and the college of agriculture at a later point? 4. This survey was based on pre-determined lists of communication forms and individuals and the lists were certainly appropriate. Nevertheless, in administering survey instruments we find it very difficult to get at the underlying reasons that such factors are perceived to be important. If the researchers conducted focus groups or individual interviews with those 2002 freshmen who are still at the University, would it be possible to get a fuller understanding of the meaning underlying the statistics? For instance, I would be interested in “how” the agricultural education teachers had such a great influence on incoming freshmen in agricultural education. Chapman, D. W. (1981). A model of student college choice. Journal of Higher Education, 52(5), 409-505. 282 Factors Influencing College-Choice of High School and Community College Matriculants Into a College of Agriculture Discussant Remarks: William G. Camp Cornell University The researchers sought to compare freshman entrants and transfer students to determine if the members of the two groups differed in terms of the factors that influenced their decisions to attend the College of Agriculture and Life Sciences (CALS). The researchers conducted a census study of all students enrolled in CALS during fall semester, 2003. The theoretical basis for the study was Chapman’s (1981) model of student college choice. Beginning with an instrument used in a similar study elsewhere, the researchers developed a survey instrument to measure perceptions of students on the degree of influence of various program and institutional characteristics and selected individuals in their decisions to attend the College. In addition demographic data from college records were accessed and analyzed. The survey was administered online with e-mail being used instead of traditional surface mailings. The study was a population census with a 38% response rate. Early-late comparisons were made to control for non- response error. The rationale for the study is well conceived. The design and research methods are appropriate. The theoretical framework is appropriate and ties in very nicely with the study. The paper is well written and the conclusions and recommendations flow logically from the findings. The topic of the study is an important one and the researchers should be commended for studying an area that has potential impact on the recruiting practices of colleges of agriculture. The comparison of freshman and transfer matriculants was particularly informative. Some questions to consider: 1. We have a tendency to survey our students to find out why they elected to major in agricultural education or to attend a college of agriculture. What might we find if we identified potential students who chose a different route to find out why they chose not to study agricultural education or some other agriculture major? 2. This is the first study I have seen that found websites to be this important to students as they make their college decisions. To what can we attribute this change? Does that mean we should be putting more emphasis on the quality of our websites now and putting less emphasis on printer matter? 3. You showed the most popular majors for high school matriculants, but clearly the transfer students did not select the same majors. What majors were most popular with transfer students? To what do you attribute the difference in academic interests between high school matriculants and transfer matriculants? 4. Surveys tend to produce simplistic answers because they inherently lack the ability to get at the nuances among respondents and because they tend not to deal effectively with “why” questions. If you were to organize two focus groups to represent the two groups of students in this study, what questions could you ask that are difficult to assess on a survey? Chapman, D. W. (1981). A model of student college choice. Journal of Higher Education, 52(5), 409-505.