Eleven questions concerning the possible origins of self-directed readiness as defined by scores on the Guglielmino (1977) Self-Directed Learning Readiness Scale (SDLRS) are addressed by this research. This chapter presents findings concerning the association of individual SDLRS scores and age, educational level, being an amateur radio operator, class of amateur radio operator license held, self-assessment of whether the respondent is a self-directed learner, number of amateur radio operators in a family, number of hobbies, and occupation. Chapter V will present additional qualitative findings based on structured interviews of selected respondents.
The findings in this chapter are reported in three sections. First, the descriptive data for the total sample are presented, Second, findings concerning the eleven research questions are reported. Third, a discussion of the findings concludes the chapter.
General Descriptive Statistics
The research design, as described in Chapter III, was based on a multi-step process. First, the eleven research questions were addressed through the collection of demographic information and the completion of the Guglielmino (1977) Self-Directed Learning Readiness Scale. Second, additional qualitative information associated with the phenomenon was collected through interviews. Respondents who scored below the first quartile and beyond the third quartile, were selected for the interviews. The analyses of the interviews are reported in Chapter VI.
Descriptive statistics were used to organize, and aid in the analysis of the data collected. Where helpful, the results of descriptive statistics are displayed in graphical form. Correlations were used to analyze the association between individual SDLRS scores and other demographic and self-reported data. Computer software (B/STAT, Motorola 68000) was used for computation.
The following general descriptive data providing an overall view of the sample are displayed in Tables 4.1 and 4.2.
All 13 variables are included in Table 4.1. Two variables, age and SDLRS are continuous. Other variables, such as educational level, class of license, and other hobbies, are identified in ranges. Still other variables, study habits, whether self-reported as self or other-directed, level of family support, station location, and occupation, are more subjective and categorical in nature.
Figure 4 is a histogram of the national population of US amateur radio operators with a normal distribution curve overlaid. The histogram provides a graphical portrayal of the distribution of amateur radio operators by age. The base year is 1997. Given a total population of nearly 500,000, one would expect the distribution to be normal. The growth in the population appears depressed during the period 1925 through 1940, however. If amateur radio operators are high in SDLR, then any variance in the distribution of amateur radio operators may be an indication of a variance in the general distribution of individuals high in SDLR or may be explained by other unidentified variables such as costs associated with the hobby and income levels.
Figure 5 is a graphic that shows the percentage of live births that are amateur radio operators in the current population. The graphic indicates that the variance in the number of hams by birth year corresponds to some degree with the number of live births.
Descriptive Data for the Total Sample of 262 Amateur Radio Operators by Demographic
Variables as a Function of Standard Deviation.
|Sex||261||26 (F)||236 (M)|
Race 256 5 (O)* 251 (W)
License class 260 4.5 1.40 1 7
Study habit 220 1 2
Self-directed 213 1 2
Descriptive Data for the Total Sample of 262 Amateur Radio Operators by Demographic
Variables as a Function of Frequency of Response.
Variable Frequency Percentage
Male 236 89.0
Female 26 11.0
Novice 8 3.1
No-Code Technician 5 1.9
Technician Plus 66 25.8
General 29 11.2
Advanced 66 25.4
Extra 80 30.8
No response 41 15.7
Individual 203 77.8
Group 17 6.5
No response 48 18.5
Self 196 75.3
Other 16 6.2
American Indian 2 0.8
Black 1 0.4
Variable Frequency Percentage
Pacific Islander 2 0.8
White 251 98.0
Number of family members licensed
1 151 58.8
2 68 26.5
3 27 10.5
4 or more 11 4.3
Why amateur radio operator
No response 16 6.2
Compelled by other 4 1.5
For other 32 12.4
Goal/to be able to 174 67.2
Fun/challenge 30 11.6
To know/fascination 2 0.8
Love of learning 1 0.4
Level of family support
Against 0 0.0
Not supportive 16 6.3
Somewhat 52 20.6
Supportive 93 36.8
Very 92 36.4
No Answer 14 5.4
Separate 15 5.8
Garage 13 5.0
Variable Frequency Percentage
Spare Room 166 63.4
Family Area 52 20.0
No response 7 2.7
None 1 0.4
One 73 27.9
Two 70 26.7
Three 64 24.4
Four 30 11.5
Five or more 17 6.5
No response 13 5.0
Laborer 23 8.8
Non-professional 43 16.4
Semi-professional 111 42.4
Professional 70 26.7
Researcher 2 0.8
The mean age of the respondents was 48.9; the range of ages was from 11 to 85 and falls within the age ranges of previous studies of SDLRS (McCune and Garcia, 1989). The mean educational level was 15.1 years; the range was 5 to 19+ years of education. The respondents were predominantly male; 240 of 261, and white; 251 of 256.
The SDLRS scores ranged from 166 to 285 with a mean of 238.0 and a standard deviation of 24.51.
A series of questions designed to gather information about the respondents' interest in amateur radio were presented. The range of license class is from Novice to Extra. The majority of respondents were General class or higher; 175 of 262 (see table 4.2). Table 4.3 indicates the type of effort required to acquire each level of amateur radio license.
Each written examination must be taken in sequence. That is to say, one must pass the Novice written exam before attempting the Technician written exam. The same is not true for the demonstrating Morse Code proficiency. One could attempt the 13 words per minute Morse Code test first. Learning Morse Code is considered a difficult barrier to overcome in order to become an amateur radio operator, even at the 5 words per minute entry level. It is interesting to note that the distribution of No-code Technician licensees within this self-selected sample, only 2% (Table 4.2), is markedly different from the national distribution of 33% (NACB, 1997).
Class of Amateur Radio License and Difficulty
Class of license
Number of questions
Theory and examined
Basic theory and regulations
|Technician -||20||not required||Basic theory and regulations plus additional theory and regulations|
|Technician +||20||5 wpm||Additional theory and regulations|
|General||20||13 wpm||Detailed theory and regulations|
|Advanced||45||13 wpm||Advanced theory and regulations|
|Extra||50||20 wpm||Additional theory and regulations|
Findings Concerning Research Questions
The responses from the subjects were treated statistically to identify associations with SDLRS scores. In each case the correlation coefficient between the two variables and the probability that the actual correlation is zero is presented.
What kind of an association exists between SDLRS and being an amateur radio operator? The mean SDLRS score for the sample is 238 with an SD of 24.41. Guglielmino reports, in the instructions for interpreting SDLRS scores, that the average score for adults is 214 and the SD 25.59. Comparison of the population means relative to the population standard deviation provides a useful frame of reference for claiming there is a difference between populations (Minium and Clark, 1982). If there is an association between being an amateur radio operator and SDLRS we would expect the effect size to indicate a difference between the average SDLRS for adults and the mean of our sample. An effect sizes larger than .33 should be considered to have practical significance (Borg & Gall, 1989). The effect size is 0.94 indicating there is a significant difference between Guglielmino's mean of 214 and the mean SDLRS score of 238 for the amateur radio operators included in this study.
What kind of an association exists between SDLR and sex? The point biserial correlation is a special case of Pearson product-moment correlation. It is designed for the situation where one variable is continuous and the other dichotomous (Wilson, 1992). It shows the extent of a relationship exists (Hay, 1988). The test value is 0.0952, with 258 degrees of freedom, and a two tail probability of more extreme value of 12.6%. This probability of more extreme values exceeds an exploratory alpha level of .1. Therefore, the notion that there is an association between SDLRS and sex is rejected.
What kind of an association exists between SDLRS and age? The test value is 0.0064, and a two tail probability of more extreme value of 91.82%. Therefore, there is no apparent association between SDLRS and age.
What kind of an association exists between SDLRS and educational level? The test value is 0.2276, and a two tail probability of more extreme value of 0.02%. Therefore, there is a positive association between SDLRS and educational level in the amateur radio operator sample.
What kind of an association exists between SDLRS and class of amateur radio license? The response was scored with a zero for no license to a seven for an Extra class license. The test value is 0.0761, and a two tail probability of more extreme value of 22.5%. Therefore, there is no apparent association between SDLRS and class of amateur radio license.
What kind of an association exists between SDLRS and one's self-assessment of whether one prefers to study alone or in a group? The responses were coded either 0 for alone, or 1 for group. The test value is -0.2561, with 218 degrees of freedom, and a two tail probability of more extreme value of 0.01%. Therefore, there is a negative association between SDLRS and whether an amateur radio operator prefers to study alone or in a group. In other words, those that prefer to study in a group tend to have lower SDLRS scores.
What kind of an association exists between SDLRS and one's self-assessment of whether one is a self-directed learner? The responses were coded either 0 for self-directed, or 1 for other-directed. The test value is -0.1124, with 211 degrees of freedom, and a two tail probability of more extreme value of 10.19%. Therefore, the notion that there is an association between SDLRS and an amateur radio operator's self-assessment of being a self-directed learner is rejected.
What kind of an association exists between SDLRS and the number of amateur radio operators in a family? The test value is 0.0578, and a two tail probability of more extreme value of 35.20%. Therefore, there does not appear to be an association between SDLRS and the number of amateur radio operators in a family.
What kind of an association exists between SDLRS and number of hobbies? The test value is 0.2083, and a two tail probability of more extreme value of 0.09%. Therefore, there is a positive association between SDLRS and number of hobbies.
What kind of an association exists between SDLRS and the occupation? The test value is 0.3246, and a two tail probability of more extreme value of 0.00%. Therefore, there is a positive association between SDLRS and the occupation of amateur radio operators.
What kind of an association exists between historical events and the development of SDLR? The amateur radio operator population by birth year, Figure 4, is not normally distributed. Since amateur radio operators are high in self-directed learning, it is questioned whether the variance in the amateur radio population indicates a similar variance in the population of high SDLR individuals. However, the quantitative data analyzed in this chapter did not inform the researcher concerning this question. Therefore, the kind of an association that exists, if any, between historical events and the development of SDLR remains to be answered. This question will be explored more fully in Chapter V..
The findings noted in the previous pages are similar to those reported in the literature. First, some professional groups such as nurses (Long & Barnes, 1995; Middlemiss, 1987; Russell, 1990) have reported Mean SDLRS scores higher than the Mean reported by Guglielmino (1977).
Guglielmino's corpus also included SDLRS scores of children who frequently score less than her Mean of 214. Therefore, even though the SDLRS scores for the amateur radio operator sample used in this study exceed the general Mean reported by Guglielmino, the subsequent significance of the difference may be less than the statistical significance. Furthermore, the self selective process leading to inclusion in the data pool is a source for further caution about the findings. Given the above warning, it is useful to note that amateur radio operators generally characterize the kinds of activities that may be identified with self-directed learners.
SDLRS scores for the amateur radio operators in this study are positively associated with educational level, self-identification with a preference for solitary learning, self-perception as being self-directed, number of hobbies, and professional or white collar employment. In turn female amateur radio operators in the sample had higher SDLRS scores than males in the study. Unfortunately the SDL research literature is equivocal concerning elements in the above profile. The difference between the sexes on the SDLRS scores of males and females are inconsistently reported. Nevertheless, there is evidence that high SDLRS scores are associated with occupations that require high cognitive function.
Finally, the question of the relationship between historical events and individual SDLRS scores remains problematic. Figure 4 reveals that when a normal curve is imposed over the number of licensed amateur radio operators by age there is a close correspondence between the two. The distribution has several possible explanations. First, it may be implied that the distribution is in some way associated with social-cultural phenomena connected to birth year and early childhood development. This position suggests that where the numbers rise above the curve and when the numbers fail to reach the curve it is an effect of major events such as the Great Depression, major conflicts such as World War I and World War II, etc., and/or associated political/technological developments. Second, it can be argued that the number of individuals licensed and who continue to hold amateur radio licenses, is independent of the above and can be explained by some other phenomena such as SDLR. Third, to the degree that demography is independent of the social cultural phenomena noted above, the distribution may be answered by the number of people in the population. Some demographers, such as Easterlin (1980), have theorized that many social behaviors, such as competitiveness, are a function of birth cohorts. Small birth cohorts are, therefore, less competitive than larger ones. Therefore, if SDLR is associated with competitiveness, a link between birth cohort and SDLRS scores might be established. This research does not satisfactorily achieve that result, however. Therefore, Figure 4 does not definitively support, nor invalidate the association of macro developments with SDLR.
On the other hand, some specific conclusions, based on the research hypotheses, are defensible. They are identified below.
This chapter reports the findings concerning 11 research questions examined by quantitative analysis. Five of the hypotheses were not supported by the findings while five were. One hypothesis was not definitely supported, nor rejected. Based on these findings the following conclusions concerning this sample were obtained.
1. There is an association between SDLRS scores and being an amateur radio operator.
2. There is no association between SDLRS scores and sex.
3. There is no association between SDLRS scores and age.
4. There is an association between SDLRS scores and educational level.
5. There is no association between SDLRS scores and class of amateur radio license.
6. There is an association between SDLRS scores and one's self-assessment of whether one prefers to study alone or in a group.
7. There is no association between SDLRS scores and one's self-assessment of whether they are self-directed learners.
8. There is no association between SDLRS scores and the number of amateur radio operators in a family.
9. There is an association between SDLRS scores and number of hobbies.
10. There is an association between SDLRS scores and occupation.
11. Limited support was found for the conclusion that there may be an association between historical events and the development of SDLR.
Additional insight concerning these conclusions is provided by the qualitative analysis of the interviews reported in Chapter V.