A Structural Approach Towards Reinvigorating Student Satisfaction in Industrial Training Institutes - A Contemplating Outlook
DOI:
https://doi.org/10.17010/pijom/2021/v14i5-7/164688Keywords:
Vocational Education And Training
, Industrial Training Institutes, Skill Development, Quality Indicators, Student Satisfaction.JEL Classification
, I230, I240, I250.Paper Submission Date
, April 2, 2020, Paper Sent Back for Revision, December 8, Paper Acceptance Date, February 26, 2021, Paper Published Online, July 10, 2021.Abstract
The research paper focused to conceptualize and empirically test the conceptual model of student satisfaction proposed for Indian vocational education and training (VET), precisely industrial training institutes (ITIs). Even though the upgradation of ITIs through public - private partnership (PPP) is emphasized from the previous decade, little empirical evidence exists about the quality of the institutes. Improved quality in ITIs helps in increased employability of the students and would help in meeting India’s projected skill demand of 191 million youths by 2022. Empirical data were collected from upgraded ITIs of Andhra Pradesh and Telangana states to assess student satisfaction. Student satisfaction gives the measure of student feedback on the quality of the courses. PLS - SEM was applied to develop measurement and structural models. Subsequently, statistical values were used to estimate the validity and reliability of the models. Besides, the predictive accuracy of the model was also tested. The data analysis assisted to ascertain whether to accept or reject the hypothesized relations proposed based on the conceptual model. The results proved that institute quality factors were positively correlated with student satisfaction. Eventually, it was observed that industry exposure was a significant determinant of student satisfaction followed by training facilities & equipment, trainer credibility, learning environment, and placement and counseling services. Above all being said, it can be posited that focusing on the above all quality factors would help in enhancing the quality of ITIsDownloads
Downloads
Published
How to Cite
Issue
Section
References
Agrawal, T. (2012). Vocational education and training in India : Challenges, status and labour market outcomes. Journal of Vocational Education & Training, 64(4), 453-474. https://doi.org/10.1080/13636820.2012.727851
Agrawal, T., & Agrawal, A. (2017). Vocational education and training in India : A labour market perspective. Journal of Vocational Education and Training, 69(2), 246-265. https://doi.org/10.1080/13636820.2017.1303785
Ajithkumar, U., & Pilz, M. (2019). Attractiveness of Industrial Training Institutes (ITI) in India : A study on ITI students and their parents. Education + Training, 61(2), 153-168. https://doi.org/10.1108/ET-04-2018-0102
Alves, H., & Raposo, M. (2009). The measurement of the construct satisfaction in higher education. The Service Industries Journal, 29(2), 203-218. https://doi.org/10.1080/02642060802294995
Bright, L., & Graham Jr., C. B. (2016). Predictors of graduate student satisfaction in public administration programs. Journal of Public Affairs Education, 22(1), 17-34. https://doi.org/10.1080/15236803.2016.12002226
Burlakanti, K., Kumar, J. N., & Srinivas, R. V. (2014). Parents’ perception about factors of quality education in private schools in Kakinada City, Andhra Pradesh. Prabandhan : Indian Journal of Management, 7(4), 5-16. https://doi.org/10.17010/pijom/2014/v7i4/59304
Burnett, P. C., & Clarke, J. A. (1999). How should a vocational education and training course be evaluated ? Journal of Vocational Education and Training, 51(4), 607- 628. https://doi.org/10.1080/13636829900200107
De Oliveira Silva, J. H., de Sousa Mendes, G. H., Ganga, G. M., Mergulhão, R. C., & Lizarelli, F. L. (2020). Antecedents and consequents of student satisfaction in higher technical-vocational education : Evidence from Brazil. International Journal for Educational and Vocational Guidance, 20(2), 351-373. https://doi.org/10.1007/s10775-019-09407-1
Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297-316. https://doi.org/10.25300/MISQ/2015/39.2.02
Douglas, J., Douglas, A., & Barnes, B. (2006). Measuring student satisfaction at a UK university. Quality Assurance in Education, 14(3), 251-267. https://doi.org/10.1108/09684880610678568
Fishbein, M., & Ajzen, I. (1974). Attitudes towards objects as predictors of single and multiple behavioral criteria. Psychological Review, 81(1), 59-74. https://doi.org/10.1037/h0035872
Gallifa, J., & Batallé, P. (2010). Student perceptions of service quality in a multi-campus higher education system in Spain. Quality Assurance in Education, 18(2), 156-170. https://doi.org/10.1108/09684881011035367
Giri, A., Biswas, W., & Biswas, D. (2018). The impact of social networking sites on college students : A survey study in West Bengal. Indian Journal of Marketing, 48(8), 7-23. https://doi.org/10.17010/ijom/2018/v48/i8/130536
Government of India. (2019). Annual report : Periodic labour force survey, 2018-19. National Statistical Office. http://mospi.nic.in › sites › files › publication_reports
Hair Jr., J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Harsolekar, D. D., & Munshi, J. (2018). An empirical analysis of the perception of management students about their employment. Prabandhan : Indian Journal of Management, 11(9), 21-37. https://doi.org/10.17010/pijom/2018/v11i9/131613
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen Jr., D. J., Hair, J. F., Hult, T. M., & Calantone, R. J. (2014). Common beliefs and reality about PLS : Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182-209. https://doi.org/10.1177/1094428114526928
Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135. https://doi.org/10.1007/s11747-014-0403-8
Ibrahim, M. Z., Rahman, M. N. A., & Yasin, R. M. (2014). Determining factors of students’ satisfaction with Malaysian skills training institutes. International Education Studies, 7(6), 9-24. https://doi.org/10.5539/ies.v7n6p9
Jöreskog, K. G., & Wold, H. O. (1982). Systems under indirect observation : Causality, structure, prediction (Vol. 139). North Holland.
Kagaari, J. R. (2007). Evaluation of the effects of vocational choice and practical training on students’ employability. Journal of European Industrial Training, 31(6), 449-471. https://doi.org/10.1108/03090590710772640
King, K. (2012). The cultural challenge in India’s massive skills development ambitions. Vikalpa : The Journal for Decision Makers, 37(3), 1-6. https://doi.org/10.1177/0256090920120301
Knoell, C. M. (2012). The role of the student-teacher relationship in the lives of fifth graders : A mixed methods analysis (Doctoral Dissertation). The College of Education and Human Sciences, University of Nebraska-Lincoln. https://digitalcommons.unl.edu/cehsdiss/134
Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM : The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227-261. https://doi.org/10.1111/isj.12131
Kumar, R., Mandava, S., & Gopanapalli, V. S. (2019). Vocational training in India : Determinants of participation and effect on wages. Empirical Research in Vocational Education and Training, 11(1), 1-17. https://doi.org/10.1186/s40461-019-0078-y
Lenton, P. (2015). Determining student satisfaction : An economic analysis of the National Student Survey. Economics of Education Review, 47, 118-127. https://doi.org/10.1016/j.econedurev.2015.05.001
Mark, E. (2013). Student satisfaction and the customer focus in higher education. Journal of Higher Education Policy and Management, 35(1), 2-10. https://doi.org/10.1080/1360080X.2012.727703
Mehrotra, S. (2014). From 5 million to 20 million a year : The challenge of scale, quality and relevance in India’s TVET. Prospects, 44(2), 267-277. https://doi.org/10.1007/s11125-014-9305-2
Menon, M. E. (2002). The mission of universities and the vocational paradigm : An investigation of students’ perceptions. Journal of Vocational Education and Training, 54(4), 515-532. https://doi.org/10.1080/13636820200200212
Muscalu, E., & Dumitrascu, O. (2014). Determination of students’ satisfaction regarding extracurricular activities conducted in the university. Comparative Study Romania-Germany. Procedia Economics and Finance, 16(May), 568-574. https://doi.org/10.1016/s2212-5671(14)00841-7
Neroorkar, S., & Gopinath, P. (2019). Impact of Industrial Training Institutes (ITIs) on the employability of graduates-a study of government ITIs in Mumbai. Journal of Vocational Education and Training, 72(1), 23-46. https://doi.org/10.1080/13636820.2019.1575895
Parker, E. L. (2008). Factos that contibute to a successful secondary vocational education progam in the State of Mississippi (Doctoral Dissertation). The University of Southern Mississippi. https://aquila.usm.edu/dissertations/1217
Pathak, R., & Patwardhan, M. (2011). Impact of job involvement on organizational effectiveness : A study among faculty members. Prabandhan : Indian Journal of Management, 4(5), 36-42. https://doi.org/10.17010//2011/v4i5/62450
Peugh, J. L., & Enders, C. K. (2004). Missing data in educational research : A review of reporting practices and suggestions for improvement. Review of Educational Research, 74(4), 525-556. https://doi.org/10.3102/00346543074004525
Placklé, I., Könings, K. D., Jacquet, W., Libotton, A., Jeroen, J. G., Merriënboer, V., Engels, N. (2018). Students embracing change towards more powerful learning environments in vocational education. Educational Studies, 44(1), 26-44. https://doi.org/10.1080/03055698.2017.1331840
Roman, I. (2014). Qualitative methods for determining students’ satisfaction with teaching quality. Procedia - Social and Behavioral Sciences, 149, 825-830. https://doi.org/10.1016/j.sbspro.2014.08.320
Rönkkö, M., & Evermann, J. (2013). A critical examination of common beliefs about partial least squares path modeling. Organizational Research Methods, 16(3), 425-448. https://doi.org/10.1177/1094428112474693
Sharma, L., & Nagendra, A. (2016). Skill development in India : Challenges and opportunities. Indian Journal of Science and Technology, 9(48), 1-8. https://doi.org/10.17485/ijst/2016/v9i48/107324
Sharma, P. N., Shmueli, G., Sarstedt, M., Danks, N., & Ray, S. (2021). Prediction - oriented model selection in partial least squares path modeling. Decision Sciences, 52(3), 567-607. https://doi.org/10.1111/deci.12329
Shmueli, G. (2010). To explain or to predict ? Statistical Science, 25(3), 289-310. https://doi.org/10.1214/10-STS330
Shmueli, G., Ray, S., Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room : Predictive performance of PLS models. Journal of Business Research, 69(10), 4552-4564. https://doi.org/10.1016/j.jbusres.2016.03.049
Tara, N., Kumar, S., & Pilz, M. (2016). Quality of VET in India : The case of Industrial Training Institutes. In, TVET@Asia, Issue 7, 1-17. http://www.tvet-online.asia/issue7/tara_etal_tvet7.pdf
Wang, S. - L., Chen, H. - P., Hu, S. - L., & Lee, C. - D. (2019). Analyzing student satisfaction in the technical and vocational education system through collaborative teaching. Sustainability (Switzerland), 11(18), 1-9. https://doi.org/10.3390/su11184856
