Prabandhan: Indian Journal of Management

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A Structural Approach Towards Reinvigorating Student Satisfaction in Industrial Training Institutes – A Contemplating Outlook


Affiliations
1 Assistant Professor, Business Administration (Central Campus), CHRIST (Deemed to be University), Hosur Road, Bangalore - 560 029, Karnataka, India
2 Associate Professor, School of Management, National Institute of Technology, Warangal, Telangana - 506 004, India
     

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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 ITIs

Keywords

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, 2020 ; Paper Acceptance Date : February 26, 2021 ; Paper Published Online : July 10, 2021.

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  • 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 ischolar_main 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


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  • A Structural Approach Towards Reinvigorating Student Satisfaction in Industrial Training Institutes – A Contemplating Outlook

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Authors

Garimidi Siva Sree
Assistant Professor, Business Administration (Central Campus), CHRIST (Deemed to be University), Hosur Road, Bangalore - 560 029, Karnataka, India
Ramlal Porika
Associate Professor, School of Management, National Institute of Technology, Warangal, Telangana - 506 004, India

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 ITIs

Keywords


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, 2020 ; Paper Acceptance Date : February 26, 2021 ; Paper Published Online : July 10, 2021.


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DOI: https://doi.org/10.17010/pijom%2F2021%2Fv14i5-7%2F164688