Dynamics of Performance and Technology in Higher Education: An Applied Stochastic Model and A Case Study

Ahmet Kara

Dynamics of Performance and Technology in Higher Education: An Applied Stochastic Model and A Case Study

Year 2013, Volume: 42 Issue: 1 , 87 - 99 , 01.01.2013

https://izlik.org/JA27WL99WZ

Abstract

The purpose of this paper is to develop a stochastic-dynamic model ofperformance and technology in education sector and bring into lightthe presence, in a particular subset of the Turkish higher educationsector, of stochastically-evolving equilibria moving towards a low performance trap over time. The dynamics of the movement in questionhinges, in part, on two factors, namely, (1) the productivity growth and(2) student population growth. We formulate a stochastically-driven,technology-based policy option that could help the sector to escapethe trap, moving the sector towards high performance equilibria. Theproposed policy option illustrates that technological transformation ineducational practices could solve a structural problem (a low performance trap) in developing-country education sectors.

Keywords

Education , universities , low performance trap , economic dimensions , technology , transformation , stochastic-dynamic models.

References

Barro, R. Education and economic growth, http://www.oecd.org/dataoecd/5/49/1825455.pdf. Bevc, M. Funding, equity and efficiency of higher education: introduction to the special issue, Education Economics 16 (3), 225–227, 2008.
Bevc, M. and Ur, S. Relations between funding, equity, and efficiency of higher education, Education Economics 16 (3), 229–244, 2008.
Dahlgaard, J.J., Kristensen, K. and Kanji, G.K. Total quality management and education, Total Quality Management 6 (5-6), 445–455, 1995.
Dahlgaard, J.J., Kristensen, K. and Kanji, G.K. Total quality in education, Total Quality Management 6 (5-6), 443–444, 1995.
Danchev, A. Social Capital and sustainable behavior of the firm, Industrial Management & Data Systems 106 (7), 953–965, 2006.
Desimone, L. How can comprehensive school reform models be successfully implemented? Review of Educational Research 72 (3), 433–479, 2002.
Easton, S.T. and Rockerbie, D.W. Optimal government subsidies to universities in the face of tuition and enrollment constraints, Education Economics 16 (2), 191–201, 2008.
Ellis, R.A . Investigating the quality of student approaches to using technology in experiences of learning through writing, Computers & Education 46 (4), 371–390, 2006.
Fethke, G. Strategic determination of higher education subsidies and tuitions, Economics of Education Review 24 (5), 601–609, 2005.
Goffe, W.L.; Sosin, K. Teaching with technology: May you live in interesting times, Journal of Economic Education 36 (3), 278–291, 2005.
Kara, A. Discrete stochastic dynamics of Income inequality in education: an applied stochastic model and a case study, Discrete Dynamics in Nature and Society, 1–15, 2007.
Kara, A. Stochastic Modeling Exercises, Fatih University, Mimeo, 2006.
Kara A. and Kurtulmu¸ s, N. Intertemporal equilibria in the public banking sector in Turkey, J. of Economic and Social Research 6 (1), 19–32, 2004.
Leonard, W.P. On becoming a productive university: Strategies for reducing cost and increasing quality in higher education, Economics of Education Review 25 (3), 343–344, 2006.
Lien, D. Quality assurance program and brain drain, Education Economics 16 (1), 59–73, 200 Sargent, T.J. Macroeconomic Theory, Academic Press, 1979.
Tatoglu, F. Y. The relationships between human capital investment and economic growth: A Panel Error Correction Model, , J. of Economic and Social Research 13 (1), 77–90, 2011.