Developing of the Measurement Model of Self-Directed Learning Characteristics

Abstract

Problem statement: Self-directed learning is a factor essential for learners. But, factors both differ and overlap. The structures of various factors are not consistent. Research Questions: The model of self-directed learning characteristics of technical college students was developed valid or not? Purpose of the Study: This research aims to develop a model of self-directed learning characteristics of technical college students by factor analysis and multidimensional item response analysis, and to validate the self-directed learning model. Research Methods: Samples were two groups. The first sample was used to analysis the model factors (230 students) and the second sample, used to validate the model (1,563 students). The instruments were 44 items (four choices). Data were analyzed through the methods of means, standard deviation, confirmatory factor analysis, and multidimensional item response analysis. Findings: First, results of analyzing item of the model are as follows. Factor analysis: items were suitable for the self-directed learning model (93.18%). Multidimensional item response analysis: all questions were suitable for the model (100.00%). The selected model had eight factors (32 items). Second, the model had validity. Conclusions: The model developed from the Guglielmino’s theory and the self-directed learning model was consistent with empirical data. The standard of the self-directed learning model was interpreted on four levels: awareness, interest, attempts at learning, and actual practice.

Keywords: Self-directed learningvalidation

Introduction

At present, advanced sciences and technologies, and the easy access to information, are inevitably

affecting how people live their lives and make decisions, causing social, economic and cultural

changes. It is, therefore, important to stay abreast of information. One of the key factors of human

development is education. The National Education Plan, Revised Edition (2009-2016) mentioned

educational development with the following qualitative aims: 1) making Thai people moral, efficient,

happy, knowledgeable, professional, ethical, eager to learn and for knowledge; and 2) turning Thai society into a society of integrity, wisdom and education by creating knowledge, innovation and

technologies leading to a sustainable learning society (Office of the Education Council, 2010).

Education is key to human resource development and the foundation of the country’s growth.

However, the results of Thailand’s education reform did not turn out as expected, as seen in a report

by the International Institute of Management Development (IMD) that ranks competitiveness of

different countries on the global scale. Thailand’s education in 2006 was ranked no. 46 out of 55

countries while, in 2008, it was ranked no. 43 out of 55 countries (Office of the Higher Education

Commission, 2008). Results from the evaluation of education quality of 17,562 schools nationwide

(49.1% of all schools), six years after the education reform and enactment of the National Education

Act, B.E. 2542, showed that only 26.5% of the learners had self-directed learning skills, loved learning

and continuous personal development and were of quality (Ratmanee, 2011). These results showed that

education quality had not improved as anticipated and learners were not actively seeking knowledge

and developing themselves.

Education has to adjust to changes in the scientific, technological, social, economic and cultural

domains. Self-directed learning is a characteristic essential for learners in the modern world where

everything changes so rapidly. This is consistent with the National Education Act, Section 1 (General:

Objectives and Principles, Article 7), stating that the learning process must encourage learners to

continuously rely on themselves, be creative, eager for knowledge and learn independently (Office of

the Education Council, 2002). This is also consistent with the concept of Isarawat (1999) who said that

self-directed learning could be created and developed. Whenever a learner learns by themselves, and

comes to love searching for knowledge, that learner will keep learning until he/she becomes a lifelong

learner. This leads to the social practice of learning (Hung et al, 2009), which is the goal of modern

academics. Self-directed learning is a trait important for education and in everyday life.

Theorists disagree on the number of key traits involved in self-directed learning. According to

Knowles (1975) there are nine traits, according to Guglielmino (1977) there are eight traits, Skager

(1978) claims there are seven traits, Isarawat (2000) suggests there are only three, and the Educational

Research Division (2000) suggests eight traits. Accordingly, these traits both differ and overlap. The

structures of the various factors are not consistent. Translation criteria are also not always clear or

suitable for the Thai context. This is similar to the theory of Sapyaprapa (1997), who states that a good

measuring model has to be based on culture, values and characteristics of each particular country, with

validity measurement, population and standard criteria created for people in each country.

Considering the structure of factors, there are many concepts of self-directed learning. They are not

consistent. Scores are not interpreted based on standard criteria suitable for Thai society. Previous

studies inside and outside Thailand have focused on factors affecting self-directed learning by students,

followed by self-directed learning characteristics. Most of these studies addressed basic education.

Therefore, a self-directed learning model must be developed.

This research was conducted with students from technical colleges affiliated with the Office of

Vocational Education Commission of Thailand. They were selected for study because they were

becoming adults and could play their roles in society appropriately, adjust themselves, accept changes,

have mental and emotional freedom, prepare to select their careers, and demonstrate intelligence and an

understanding of sophisticated concepts (Kotrakun, 2005). Moreover, they were eager to learn and

enter into the higher education system. They were competitive and ready to deal with problems and

enter into the labour market. The Office of the Education Council (2008) found that there were not

enough researches and vocational advances. Therefore, this study will focus on development of learners

in an effective and efficient way. This research also helped learners develop a self-directed learning

system using self-assessment.

Purpose of the study

This research aims to develop a valid and reliable model to measure and determine self-directed

learning by technical college students. Specific objectives are as follows: To analysis the self-directed

learning model of technical college students by factor analysis and multidimensional item response

analysis, and to validate the self-directed learning model for technical college students.

Research methods

Findings

Conclusions

The model developed from the theory of Guglielmino and the self-directed learning model that the

researcher developed (44 items) had items suitable for 41 items of the self-directed learning model

(93.18%). The model was consistent with empirical data (Chi-square = 933.94 (df = 865, p = .051), GFI

= .84, AGFI = .82, RMR = .062, RMSEA = .019). When responses were analyzed, all multidimensional

items were found suitable for the self-directed learning model (100.00%). The model had G2 =

26655.297, np = 168, AIC = 26991.297 (The two analyzing methods were highly congruent, with a

value of .93.) The self-directed learning model that was developed had eight factors: 1) openness to

learning opportunities, 2) self-conception as an effective learner, 3) initiative and independence in

learning, 4) informed acceptance of responsibility for one’s own learning, 5) love of learning, 6)

creativity, 7) a positive orientation to the future, and 8) the ability to use basic study skills and problem-

solving skills (32 items).

The self-directed learning model of technical college students had validity that was developed. The

chi-square test statistic was 418.96 (df=376, p=.062) with no statistical significance. The goodness-of-

fit index (GFI) was .98. The adjusted goodness-of-fit index (AGFI) was .98. The root mean squared

residual (RMR) was .023, and the root mean squared error of approximation (RMSEA) was .008.

Discussion

The first topic for discussion is the self-directed learning model. This study found that, in the self-

directed learning model analyzed by analysis factors, when considered item-by-item, three items

(6.82%) did not pass the statistical significance and/or the practical significance. It is considered that

this model was perfectly appropriate (93.18%) and consistent with overall statistics of the model, which

can be considered from statistics of congruence with the experimental data. All statistics were

acceptable and reflected congruence between the model and experimental data.

The self-directed learning model analyzed by the multidimensional factors found appropriateness of

every item and item fit. Wright et al. (1994) suggest statistics of congruence based on estimation with

values from .60 to 1.40. This means that all items were congruent with the self-directed learning model

under the theory of responses to multidimensional tests (Chianchana, 2009), i.e. students with high self-

directed learning capabilities had a higher chance of answering these items than students with low self-

directed learning capabilities.

It can be seen that there were congruence between factor analysis and multidimensional analysis with the value of .93. This showed that factor analysis and multidimensional analysis were congruent at a very high level, which was consistent with the reliability consideration of Nunnally & Bernstein (1994), who suggested considering an evaluation with high impact at .90. This was with Chianchana (2012), who suggested that the confidence was .60-.79. The result was quite good and .90 up meaning very good.

The self-directed learning model of technical college students was developed from eight factors,

namely openness to learning opportunities, self-conception as an effective learner, initiative and

independence in learning, informed acceptance of responsibility for one’s own learning, love of

learning, creativity, a positive orientation to the future, and the ability to use basic study skills and

problem-solving skills via factor analysis. Analysis of responses to multidimensional tests

(multidimensional item response theory) showed validity according the developed structure with chi-

square test statistics of 418.96 (df=376, p=.062) with no statistical significance. Goodness-of-fit index

(GFI) was .98. Adjusted goodness-of-fit index (AGFI) was .98. Root mean squared residual (RMR)

was .023. Root mean squared error of approximation (RMSEA) was .008. All indexes complied with a

consideration of Bollen in 1989 Kelloway in 1998 and Diamantopoulos, & Siguaw in 2000, who

showed the model developed, with congruence with empirical data (Bollen, 1989; Kelloway, 1998;

Diamantopoulos, & Siguaw, 2000).

Regarding implementation, the self-directed learning model should be implemented among technical

college students, in terms of examination and interpretation, in order to develop a reliable self-directed

learning model suitable for their age groups and schools. The self-directed learning model was

consistent with experimental data. Future studies should aim to develop a self-directed learning system

by way of self-assessment.

Acknowledgments

This research work is funded by the Office of the Higher Education Commission, and King

Mongkut's University of Technology, North Bangkok, Thailand.

References

1. Bollen, K.A. (1989). Structural equations with with latent variables. New York, NY: John Wiley & Sons, Inc.
2. Chianchana, C. (2009). Multidimensional analysis. Journal of Education Khon Kaen University, 32(4), 13-22.
3. Chianchana, C. (2012). Research Methodology. Bangkok: King Mongkut’s University of Technology North Bangkok (Thailand).
4. Cross, K. P. (1981). Adults as learners: Increasing participation and facilitating Learning. San Francisco: Jossey-Bass.
5. Diamantopoulos, A., & Siguaw, J.A. (2000). Introducing LISREL: A Guide for the uninitiated. London: SAGE Publication.
6. Educational Research Division. (2000). Research reports for patterns that enhance the learning process, there are very good health features in elementary education. Bangkok: The religion.
7. Guglielmino, L.M. (1977). Development of the Self-Directed Learning Readiness Scale. Unpublished Doctoral
8. Dissertation, University of Georgia. Dissertation Abstracts International, 38 (11a), 6467.
9. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2006). Multivariate Data Analysis. (6th ed). New Jersey: Pearson Education.
10. Hung, D., Ng, P.T., & Koh, T.S. (2009). The social practice of learning: a craft for the 21st century. Asia Pacific Education Review, 10(2), 205-214. doi:10.1007/s12564-009-9025-0.
11. Isarawat, S. (1999). Research reports and training styles of Thai people in the rural areas, which affects the self-directed learning. Bangkok: Faculty of social sciences and human sciences, Mahidol University (Thailand).
12. Isarawat, S. (2000). Teaching adults. Bangkok: Faculty of social sciences and human sciences, Mahidol University (Thailand).
13. Kellowey, E. (1998). Using LISREL for structural equation modeling: A researcher's guide. Thousand Oaks: SAGE Publications.
14. Knowles, M. S. (1975). Self-Directed Learning: A Guide for Learners and Teacher. Chicago: Association Press.
15. Kotrakun, S. (2005). Educational psychology. (6th ed). Bangkok: Chulalongkorn University.
16. Nunnally, J.C., & Bernstein, I.H. (1994). Psychometric theory. (3rd ed). New York: McGraw-Hill.
17. Office of the Education Council. (2002). The National Education Act 1999 and amendment (vol. 2) 2002. Bangkok: Office of the Education Council.
18. Office of the Education Council. (2008). Report on the monitoring and evaluation of learning management, vocational level. Bangkok: Office of the Education Council.
19. Office of the Education Council. (2010). The national education plan, revised (2009-2016). Bangkok: Office of the Education Council.
20. Office of the Higher Education Commission. (2008). Project report strategic network grants allocated for the year 2008. Bangkok: Office of the Higher Education Commission.
21. Ratmanee, A. (2011). A repository of knowledge: why education is a slow development, Thai. Study of slow development. Retrieved from http://www.muslimthai.com/main/1428/content. php?category= 110&id=16660.
22. Rogers, C. R. (1983). Freedom to learn for the 80's. Columbus, OH: Merrill.
23. Sapyaprapa, P. (1997). Adjustment and use of the standard psychological tests. In T. Khemmani & S. Sakonrak (Eds.), Design and tools of educational research(pp.427-438). Bangkok: Chulalongkorn University.
24. Skager, R. (1978). Lifelong Education and Evaluation Practice. Oxford: Franfurt Unesco Institute for Education.
25. Yen, W.M. & Fitzpatrick, A.R. (2006). Item response theory. In R.L. Brennan (ed.), Educational Measurement. (4th ed., pp. 111-153). American Council on Education and Praeger Publishers: America.