Browsing by Subject "Self-Directed Learning"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Developing a decision model to describe levels of self-directedness based upon the key assumptions of andragogy(Texas A&M University, 2005-11-01) Richards, Lance JonathanAs workplace demands change, a need has developed for alternatives to traditional education. With advancements in electronic telecommunication technologies, distance education has become a viable alternative to traditional classrooms for working professionals. Efficiency and cost effectiveness are driving many programs to place oncampus students and distance students in the same courses at the same time. This phenomenon has resulted in the placement of students with vastly different backgrounds, levels of expertise, and levels of motivation in the same classrooms. Often a professor will teach to one learning style, leaving some students in the dust, never to get on track. Without face-to-face contact with an instructor, this can leave distance education students feeling isolated and alone. There is a continuing need for the development of alternative instruments to assess self-directed learning (Brockett & Himestra, 1991). We must develop a means of determining an individual??s readiness for self-directed learning, as well as a device for measuring the efficiency of programs designed to foster the attitudes and skills which are involved in increased self-directedness in learning (Guglielmino, 1977). Self-directed learning readiness is important to a learner??s success in distance education programs. Inorder for an educator to tailor instruction to the unique attributes of each student, there is a need for an instrument that will identify the learner??s stage of self-directedness or degree of dependency and for an instrument that will determine the educator??s default teaching style at the beginning of a course. Such an instrument will help instructors increase their learners?? level of self-direction and will improve the overall quality, student satisfaction, and student retention in distance learning courses. The purpose of this study is to develop and pilot test two instruments based upon the Staged Self Directed Learning Model (Grow, 1991) and the key assumptions of andragogy: one measuring the self-directed learning readiness of a student in the context of an individual course and the other measuring the teaching style of the instructor in the context of the same course. The data will be analyzed and given to the instructor to give him/her an idea of the self-directed learning readiness level of students enrolled in the course. A report will be generated to show matches and mismatches between the instructor??s teaching style and the self-directed learning readiness level of the students. A decision model will be developed to suggest teaching strategies that minimize mismatches and facilitate the growth of students from dependent to self-directed through the course.Item Readiness for self-directed learning and the cultural values of individualism/collectivism among American and South Korean college students seeking teacher certification in agriculture(Texas A&M University, 2006-04-12) Lee, In HeokThe purpose of this study is to examine the relationship between self-directed learning readiness and the cultural values of individualism/collectivism in two sample groups drawn from different cultures. The research design used for this study was descriptive and correlational in nature. The target population for this study consisted of two sample groups: Korean and American college students who seek teacher certification in the field of agriculture. Data were collected using a web-formatted questionnaire. Results were computed statistically, including the means, standard deviations, effect size, independent sample t-test, one-way ANOVA, bivariate correlations, and multiple regression. Findings indicated that in a hierarchical multiple regression analysis, scores for the Self-Directed Learning Readiness Scale (SDLRS) (R2 = .03, adjusted R2 = .01, p = .30) in Step 1 was not statistically significantly related by gender, student classification, and GPA. Gender, student classification, and GPA accounted for only 3% of the variance and the three beta weights for the gender, student classification, and GPA variables were not statistically significantly related to the SDLRS. However, scores for SDLRS (R2= .34, adjusted R2 = .30, ??R2 = .31, p =.00) in Step 2 was statistically significantly related by gender, student classification, GPA, nationality, vertical individualism (VI), horizontal individualism (HI), vertical collectivism(VC), and horizontal collectivism(HC). This model accounted for 34 % of the variance in the SDLRS (R2 change = .31). It appears that nationality, VI, HI, VC, and HC accounted for a further 31% of the variance. However, in Step 1, the gender, student classification, and GPA variables did not account for a significant amount of variance in Step 2. The beta weight for nationality and VI variables were not statistically significantly related to the SDLRS (E = -0.15, t = -1.67, p = .10; E = 0.01, t = 0.10, p = .92, respectively). However, the beta for the HI variable was statistically significant and positive (E = 0.40, t = 4.31, p = .00). The beta for the VC variable also was statistically significant and positive (E = 0.20, t = 2.12, p = .04). The beta for the HC variable also was statistically significant and positive (E = 0.21, t = 2.19, p = .03). These findings indicated that if HI, VC, and HC attitudes are high, the SDLRS scores tend to be high. That is, differences in the students?? SDLRS can be best explained through HI, VC, and HC among the cultural values of individualism/collectivism.