This study is conducted to find out the factors influencing intention to take part in extra-curricular activities. Despite the various contributions, the study has some limitations.
The first is the sample limitation. The samples in this research are collected from two public universities: The university of Economic Ho Chi Minh city and Open University. This study did not compare differences between public and private schools. In addition the sample size is 278, it is so small to apply in the population. In future researches, it should be done in other private universities and in other geographic areas such as: the Central and the North of Vietnam. This make us understand clearly about behavior of student in different zone because of different culture, different economy. In addition, the future researches should be conducted with a large sample in other to infer to population.
The second thing is that there are some research results that was not explained in this study such as differences about gender and job after school. The next researches should be conducted in these gaps to make clear it.
The last limitation is that using Clarity of extra-curricular information variable is not enough to explain Attitudes toward extra-activities (R square is .032). Therefore, in future researches, researchers should find out other variables for predicting Attitude.
REFERENCES 1. Article
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Ajzen, I. & Driver, B.L. (1992). Application of the theory of planned behavior to leisure choice. Journal of Leisure Research, 24(3), 207-24.
Ajzen, I.,& Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice:
A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
Barnett, L. (2007). “Winners” and “losers”: The effects of being allowed or denied entry into competitive extracurricular activities. Journal of Leisure Research, 39(3), 16-341.
Bợrzộa, C., David Kerr, D., Mikkelsen, R., Froumin, I., Losito, B., Pol, M. and Sardoc, M. (2004). Education for democratic citizenship activities 2001–2004:
All-European study on EDC policies. Strasbourg: Council of Europe.
Broh, B. A. (2002). Linking extracurricular programming to academic achievement:
Who benefits and why?. Sociology of Education, 75(1), 69-95.
Budd, R. J. (1986). Predicting cigarette use: The need to incorporate measures of salience in the theory of reasoned action. Journal of Applied Social Psychology, 16(8), 663-685.
Budd, R. J., & Spencer, C. P. (1984). Understanding seat-belt use: A test of Bentler- Speckart’s extension of the “theory of reasoned action”. European Journal of Social Psychology, 14(1), 69-78.
Carns, A. W., Carns, M. R., Wooten, H. R., Jones, L., et al. (1995). Extracurricular activities: Are they beneficial? TCA Journal, 23(2), 37-45.
Cavana, R., Delahaye, B, & Sekaran, U. (2001). Applied Business Research:
Qualitative and Quantitative Methods. Milton, Queensland: John Wiley &
Sons Australia Ltd.
Chia, Y. M. (2005). Job offers of multi-national accounting firms: The effects of emotional intelligence, extra-curricular activities, and academic performance.
Accounting Education: An International Journal, 14(1), 75–93.
Chodorow, N. (1990). What is the relation between psychoanalytic feminism and the psychoanalytic psychology of women?. In D. Rhode (Ed.), Theoretical perspectives on sexual difference. New Haven: Yale University Press.
Chung, W., & Kalnins, A. (2001). Agglomeration effects and performance: A test of the Texas lodging industry. Strategic Management Journal, 22(10), 969- 988.
Connelly, Brian L.; Certo, S. Trevis; Ireland, R. Duane; & Reutzel, Christopher R.
(2011). Signaling Theory: A Review and Assessment. Journal of management 37(1), 39-67
Constance, E. P & Naveen, D. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999–1007
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Cambridge, MA: MIT Sloan School of Management)
Dole, S. (2000). The impliciations of the risk and resilience literature for gifted students with learning disabilities. Roeper Review, 23(2), 91-96.
Erdem, T. and Swait, J. (1998). Brand equity as signaling phenomenon. Journal of Consumer Psychology, 7(2), 131-57.
Filatotchev, I., & Bishop, K. (2002). Board composition, share ownership, and
“underpricing” of U.K. IPO firms. Strategic Management Journal, 23(10), 941-955.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fredricks, A.J., & Dossett, D.L. (1983). Attitude behavior relation: A comparison of the Fishbein-Ajzen and the Bentler-Speckart models. Journal of Personality and Social Psychology, 45(3), 501-512
Gaston Godin. (1994). Theories of reasoned action and planned behavior:
usefulness for exercise promotion. Medicine and science in sports and exercise 26(11),1391-1394
Gilligan, C. (1982). In a different voice: Psychological theory and women’s development. Cambridge, MA: Harvard University Press.
Hà An (2012). Thách thức đối với thị trường lao động, việc làm. Retrieved
September 10, 2012, from
http://www.daibieunhandan.vn/default.aspx?tabid=74&NewsId=257578
Hair, J.F. Jr., Anderson, R.E., Tatham, R.L., & Black, W.C. (Eds.). (1998).
Multivariate Data Analysis. Upper Saddle River, NJ: Prentice Hall.
Hair, J. F., Anderson, R. E., Tatham, L., & Black, W. (Eds.). (2003). Multivariate Data Analysis. Upper Saddle River, NJ: Prentice Hall.
Hair, J. F. Jr. Black, W. C., Babin, B. J. Anderson, R. E. and Tatham, R. L. (Eds.).
(2006). Multivariate data analysis. New Jersey: Prentice Hall
Hair, Joseph F. & Money, Arthur H. & Samouel, Phillip & Page, Mike (Eds.).
(2007). Research method for business. West Sussex, England: John Wiley &
Sons Ltd,
Jabnoun, N., Hassan, H. A., & Tamimi, A. (2003). Measuring perceived service quality at UAE commercial banks. The International Journal of Quality &
Reliability Management, 20 (4), 458-472.
Janney, J. J., & Folta, T. B. (2006). Moderating effects of investor experience on the signaling value of private equity placements. Journal of Business Venturing, 21(1), 27-44.
Kaiser, H.F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
Kenneth R. Bartkus, Blake Nemelka, Mark Nemelka, Phil Gardner. (2012).
Clarifying The Meaning Of Extracurricular Activity: A Literature Review Of Definitions. American Journal Of Business Education, 5(6), 693-704
Kluckhohn, C. (1951). Values and value-orientations in the theory of action: An exploration in definition and classification. In T. Parsons & E. Shils (Eds.), Toward a general theory of action (pp. 388-433). Cambridge, MA: Harvard University Press.
Kohn, M.L., & Schooler, C. (1983). Work and personality. Norwood, NJ: Ablex.
Liska, A. E. (1984). A critical examination of the causal structure of the Fishbein/Ajzen attitude-behavior model. Social Psychology Quarterly, 47, 61- 74.
Malhotra, N. K. (1996). Marketing Research: An Applied Orientation. Newjersey, USA: Prentice-Hall
Maslow, A. H. (1965). Eupsychian management. Homewood, IL: Dorsey.
Mohammad Reza Jalilvand, Neda Samiei. (2012). The impact of electronic word of mouth on a tourism destination choice: Testing the theory of planned behavior (TPB). Internet Research, 22(5), 591 – 612
Nelson, I. T., V. P. Vendrzyk, J. J. Quirin, and R. D. Allen. (2002). No, the sky is not falling: Evidence of accounting student characteristics at FSA schools, 1995-2000. Issues in Accounting Education, 17(3), 269-287.
Netmeyer, R. G., & Burton, S. (1990). Examing the ralationships between voting behavior, intention, perceived control, and expectation. Journal of Applied Social Psychology, 20(8), 661-680.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. New York:
McGraw-Hill.
Pajares, F. (1997). Current directions in self-efficacy research. In M. Maehr & P. R.
Pintrich (Eds.). Advances in motivation and achievement, 10, 1-49.
Greenwich, CT: JAI Press.
Parker, D., Manstead, A.S.R., Stradling, S.G., Reason, J.T. and Baxter, J.S. (1992).
Intention to commit driving violations: an application of the theory of planned behavior. Journal of Applied Psychology, 77(1), 94-101.
Rubin, R.S., Bommer, W.H., & Baldwin, T.T. (2002). Using extracurricular activity as an indicator of interpersonal skill: Prudent evaluation or recruiting malpractice?. Human Resource Management, 41(4), 441–454.
Saunders, M., Lewis, P., & Thornhill, A. (2000). Research Methods for business students. Essex: Pearson Educations.
Schwartz, S. H. (1992). Universals in the content and structure of values: Theory and empirical tests in 20 countries. In M. Zanna (Ed.), Advances in experimental social psychology (vol. 25, pp. 1-65). New York: Academic Press.
Schwartz, S. H. (2005). Basic human values: Their content and structure across countries. In A. Tamayo & J. B. Porto (Eds.), Valores e comportamento nas organizaỗừes [Values and behavior in organizations] (pp. 21-55). Petrúpolis, Brazil: Vozes.
Schwartz, S. H. (2006). Basic human values: Theory, measurement, and applications. Revue Franỗaise de Sociologie, 47(4), 249-288.
Sekaran, U. (2006). Research methods for business: A skill building approach. New York: John Wiley & Sons, Inc.
Selim, H. M. (2003). An empirical investigation of student acceptance of course web sites. Computers & Education, 40(4), 343–360.
Spence, M. (2002). Signaling in retrospect and the informational structure of markets. American Economic Review, 92(3), 434-459.
Thành Luân (2012). Kinh tế Việt Nam sau 5 năm gia nhập WTO: Bộn bề thách thức. Retrieved , Feburary 18, 2012, from http://www.baomoi.com/Kinh-te- Viet-Nam-sau-5-nam-gia-nhap-WTO-Bon-be-thach-thuc/45/7903653.epi Thùy Vinh (2012). Yếu kỹ năng, ngoại ngữ. Retrieved December 9, 2012, from
http://nld.com.vn/2012120909379366p0c1017/yeu-ky-nang-ngoai-ngu.htm Tho, D. N. (2009). Signal quality and service quality: a study of local and
international MBA programs in Vietnam. Quality Assurance in Education, 17(4), 364-376
Trọng, Hoàng & Ngọc, Chu Nguyễn Mộng. (2008). Phân tích dữ liệu nghiên cứu với SPSS. Hanoi, Vietnam: Nxb Hồng Đức.
Wright, John Paul, Tibbetts, Stephen G., & Daigle, Leah E. (2008). Criminals in the Making Criminality Across the Life Course. Thousand Oaks, California:
SAGE Publications.
Ya-Yueh Shih, Kwoting Fang. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Research, 14(3) 213 – 223
Zhang, Y., & Wiersema, M. F. (2009). Stock market reaction to CEO certification:
The signaling role of CEO background. Strategic Management Journal, 30(7), 693-710.
APPENDIX A
THE SCALES FOR REFERENCE
1. The scale of Ya-Yueh Shih et al. (2004) for internet baking field
Behavior intention
INT1 :I plan to use Internet banking.
INT2 : I intend to use Internet banking within the next 3 months.
INT3 : I will add Internet banking to my favorite links.
Attitude
ATT1 : I feel using Internet banking is a wise idea.
ATT2 : I feel using Internet banking is a good idea.
ATT3 : I like to use Internet banking
Subjective norms
SN1 : Most people who are important to me would think that using Internet banking is a wise idea.
SN2 : Most people who are important to me would think that using Internet banking is a good idea.
SN3 : Most people who are important to me would think I should use Internet banking.
SN4 : My family who are important to me would think that using Internet banking is a wise idea.
SN5 : My family who are important to me would think that using Internet banking is a good idea.
SN6 : My family who are important to me would think I should use Internet banking.
Perceived Behavioral Control
PBC1 : I would be able to operate Internet banking.
PBC2 : I have the resources to use Internet banking.
PBC3 : I have the knowledge to use Internet banking.
PBC4 : I have the ability to use Internet banking.
2. The scale of Mohammad Reza Jalilvand, Neda Samiei (2012) for tourism destination choice
Attitude
What do you think about Iran as a tourism destination?
(ATV1) Very bad ...:...:...:...:...:...:... Very good
(ATV2) Very worthless ...:...:...:...:...:...:... Very valuable (ATV2) Very unpleasant ...:...:...:...:...:...:... Very pleasant
Subjective norm
(SB1) Important people in my life say I ought to visit Iran.
(SB2) Most people who are important to me would want me to visit Iran.
(SB3) People whose opinions I value would prefer me to visit Iran.
Perceived behavioral control (PBC1) I would be able to visit Iran.
(PBC2) I have the resources and the knowledge and the ability to visit Iran.
(PBC3) If I want to visit Iran, it would be easy.
Intention to travel
(IT1) I predict I will visit Iran in the future.
(IT2) I would visit Iran rather than any other tourism destination.
(IT3) If everything goes as I think, I will plan to visit Iran in the future.
3. The scale of Tho (2009) for studying of local and international MBA programs in Vietnam
Signal clarity
(1) This university provides clear information about its MBA program to students.
(2) This university always provides sufficient information about its MBA program for students.
(3) I have no trouble figuring out what this university is trying to provide for students.
APPENDIX B
QUALITATIVE RESEARCH 1. The script of focus group
- The introduction
- The main question
Let me know your ideas about following question.
Q1. Have you ever participated in extra-curricular? If the answer is yes, which kinds of these activities that you like? What purposes for joinning in extra- curricular. If the answer is no, why don’t you take part in extra-curricular?
Q2. Can you give me your idea about which things that you can get and which things that you have to trade off when you join in extra-curricular. Why?
Q3. When you have a problem, who do you ask for advices? Who are important to you? Can you list
Q4. Which elements that you need when you take part in extra-curricular.
Why?
Hello everyone, my name is Huu Phuc from the research group of the University of Economics Ho Chi Minh city. My group is conducting a research name: “Antecedents of student’s intention to participate in extra- curricular”. I would like to thank you for your attentions into this interview.
Do not have wrong or right ideas, all of your thinking, contributions are helpful with us.
Q5. When you want to join to an extra-curricular activity, what information resources do you find out? Why?
Q6. Have you ever seen the information of extra-curricular in you university?
Where did you see them? what do you think about it. Can you assess the content and format of them?
Q7. According to your experience, which factors affect to student’s intention to take part in extra-curricular? Why?
2. The results of the qualitative research The main finding in qualitative research are:
- Respondents in focus groups agree that the benefits that they may get from extra-curricular are: activity mark; soft skills such as working in group, presentation; expanding social network. Besides that, some students said that they do not care about benefits, they just join to extra-curricular because they like it.
- Most students agree that people who have effect to them are their parents, their teachers, and their friends. Some students who have lover said that the lover play important role to their decision. Lover, however, is not consider as member in group of reference in this study because there are some students (not all students) have lover, so that the non-lover students can not answer the survey question concerning to lover.
- The resources that student need for joining extra-curricular activities are:
time; money; vehicle such as motorbike, bicycle. However, there are some students
said that they do not own vehicle but they can take bus or ask their friends picking up them to join in extra-curricular.
- Many students agree that the quality of information have effect to their intention to take part in extra-curricular. For example, one student said that he did not have any plan at the weekend but he saw a poster about an activity occurring at that time and the information was attractive, he had considered to join. Another student said that when he saw a poster that has enough necessary information, especially information concerning benefit of activity, the probability that he joined in is higher than poster with very brief information.
- Finally, through focus group, students have contributed their opinion to develop the complete scale for next quantitative research.
APPENDIX C THE QUESTIONNAIRE
Greeting the students!
This survey is done by research group of International School of Business (ISB) – University of Economics HCM City (UEH) . The primary purpose of this study is to improve the understanding of the intention to participate in extra-curricular activities. We would like to notice that there is no right or wrong opinion. All your ideas are valuable and useful for our research. We greatly appreciate with your sincere co-operation.
I. Personal information 1. You are:
1. Freshman 2. Sophomore
3. Junior 4. Senior
2. Your gender:
1. Male 2. Female
3. Do you have part-time job?
1. Yes 2. No
II. The main question
Please give your agreement level about the below statements at your university:
Please circle your suitable choice for the agreement level:
1. Totally disagree 2. Disagree
3. Neutral 4. Agree
5. Totally agree
Attitudes toward extra-curricular Level of agreement 1 I believe that I can get good activity mark when I take part in extra-
curricular. 1 2 3 4 5
2 I believe that I can learn many good skills when I take part in extra-
curricular. 1 2 3 4 5
3 I believe that I can get many benefits when I take part in extra-curricular. 1 2 3 4 5 4 I believe that I can expand my social network when I take part in extra-
curricular 1 2 3 4 5
5 I feel interesting when I take part in extra-curricular. 1 2 3 4 5 Subjective norm toward extra-curricular
1 My parents would think that I should take part in extra-curricular. 1 2 3 4 5 2 My teachers would think that I should take part in extra-curricular. 1 2 3 4 5 3 My classmate would think that I should take part in extra-curricular. 1 2 3 4 5 4 My best friends would think that I should take part in extra-curricular. 1 2 3 4 5
Perceived behavioral control
1 I believe that I can perform extra-curricular well 1 2 3 4 5 2 I have capability to take part in extra-curricular. 1 2 3 4 5 3 I have enough resources to take part in extra-curricular 1 2 3 4 5 4 I believe that I have enough skills to perform extra-curricular easily 1 2 3 4 5
Clarity of extra-curricular information
1 This university provides clear information about extra-curricular
activities 1 2 3 4 5
2 This university always provides sufficient information about extra-
curricular activities 1 2 3 4 5
3 I have no trouble to find out the information about extra-curricular
activities 1 2 3 4 5
4 I have no trouble figuring out what this university is trying to provide for
students. 1 2 3 4 5
Intention to participate in extra-curricular
1 I have intention to take part in extra-curricular 1 2 3 4 5 2 I will take part in extra-curricular when I have information 1 2 3 4 5 3 I will take part in extra-curricular in next course 1 2 3 4 5
Thanks for your sincere collaboration!
APPENDIX D
RELIABILITY STATISTICS
1. Cronbach alpha analysis of factor Attitudes toward extra-curricular (ATT)
Reliability Statistics Cronbach's Alpha N of Items
.724 5
Item Statistics
Mean Std. Deviation N ATT1 3.1079 1.03156 278 ATT2 3.3237 .97415 278 ATT3 3.1583 .84340 278 ATT4 3.1942 .89828 278 ATT5 3.3129 .81452 278
Item-Total Statistics Scale Mean if Item
Deleted
Scale Variance if Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item Deleted
ATT1 12.9892 6.689 .414 .709
ATT2 12.7734 6.891 .416 .705
ATT3 12.9388 6.426 .661 .611
ATT4 12.9029 7.012 .451 .689
ATT5 12.7842 7.072 .515 .668
2. Cronbach alpha analysis of Subjective norm toward extra-curricular (NORM)
Reliability Statistics Cronbach's Alpha N of Items
.689 4
Item Statistics
Mean Std. Deviation N NORM1 3.5396 .88930 278 NORM2 3.0144 .70055 278 NORM3 3.1475 .90117 278 NORM4 2.7626 .78875 278
Item-Total Statistics Scale Mean if Item
Deleted
Scale Variance if Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item Deleted
NORM1 8.9245 3.189 .517 .595
NORM2 9.4496 3.714 .525 .601
NORM3 9.3165 3.069 .551 .570
NORM4 9.7014 3.986 .322 .712
3. Cronbach alpha analysis of Perceived behavioral control (PBC)
Reliability Statistics Cronbach's Alpha N of Items
.812 4
Item Statistics
Mean Std. Deviation N PBC1 3.6835 .91151 278 PBC2 3.5468 .90902 278 PBC3 3.7878 .83359 278 PBC4 3.6079 .90777 278
Item-Total Statistics Scale Mean if Item
Deleted
Scale Variance if Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item Deleted
PBC1 10.9424 4.394 .759 .699
PBC2 11.0791 4.795 .629 .765
PBC3 10.8381 4.844 .705 .732
PBC4 11.0180 5.397 .452 .846
4. Cronbach alpha analysis of Clarity of extra-curricular information (INFO)
Reliability Statistics Cronbach's Alpha N of Items
.720 4
Item Statistics
Mean Std. Deviation N INFO1 3.9820 .72826 278 INFO2 3.6475 .79587 278 INFO3 4.1763 .72690 278
INFO4 3.8489 .78261 278
Item-Total Statistics Scale Mean if Item
Deleted
Scale Variance if Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item Deleted
INFO1 11.6727 3.059 .557 .630
INFO2 12.0072 2.874 .556 .628
INFO3 11.4784 3.413 .397 .719
INFO4 11.8058 2.973 .527 .646
5. Cronbach alpha analysis of Intention to participate in extra-curricular (INT)
Reliability Statistics Cronbach's Alpha N of Items
.694 3
Item Statistics
Mean Std. Deviation N INT1 3.5935 .75780 278 INT2 3.5504 .68716 278 INT3 3.3885 .78810 278
Item-Total Statistics Scale Mean if Item
Deleted
Scale Variance if Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item Deleted
INT1 6.9388 1.603 .482 .636
INT2 6.9820 1.700 .519 .594
INT3 7.1439 1.467 .531 .573
APPENDIX E
EXPLORATORY FACTOR ANALYSIS (EFA) 1. The first EFA for Independent variable
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .756
Bartlett's Test of Sphericity
Approx. Chi-Square 1609.740
df 120
Sig. .000
Total Variance Explained
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Total % of Variance
Cumulative
% Total % of Variance
Cumulative
% Total % of Variance
Cumulative
%
1 4.676 29.226 29.226 4.676 29.226 29.226 2.723 17.021 17.021
2 2.149 13.433 42.659 2.149 13.433 42.659 2.486 15.540 32.561
3 1.623 10.146 52.806 1.623 10.146 52.806 2.338 14.611 47.173
4 1.205 7.530 60.335 1.205 7.530 60.335 2.106 13.163 60.335
5 .946 5.914 66.249
6 .845 5.283 71.532
7 .810 5.063 76.595
8 .656 4.100 80.695
9 .582 3.636 84.331
10 .521 3.254 87.585
11 .450 2.813 90.399
12 .394 2.464 92.863
13 .388 2.422 95.284
14 .301 1.880 97.165
15 .264 1.648 98.813
16 .190 1.187 100.000
Extraction Method: Principal Component Analysis.
Component Matrix(a) Component
1 2 3 4
PBC1 .754 -.326
PBC3 .724 -.417
NORM1 .649 -.315
PBC2 .614 -.451
INFO4 .609 -.355
ATT5 .598 .387
PBC4 .583 -.346
ATT3 .570 .440 .378
NORM3 .477 -.394 .347
INFO3 .461 -.371
INFO2 .380 -.542 .331 .368
INFO1 .435 -.514 .459
ATT4 .415 .490
NORM2 .422 .487 -.343 .343
ATT1 .375 .576
ATT2 .358 .365 .394
Extraction Method: Principal Component Analysis.
a 4 components extracted.
Rotated Component Matrix(a) Component
1 2 3 4
PBC1 .850
PBC3 .830
PBC2 .769
INFO3 .424 .416
ATT3 .774
ATT1 .695
ATT2 .639
ATT5 .626
ATT4 .610 .350
INFO2 .821
INFO1 .806
INFO4 .693
PBC4 .443 .499
NORM2 .779
NORM3 .729
NORM1 .361 .650
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 6 iterations.