Determinants of School Efficiencies from Innovative Teaching through Digital Mobile E-Learning for High Schools: Application of Bootstrap Truncated Regression Model

The goal of this research is to evaluate the innovative teaching to affect school efficiency through using digital mobile e-learning of high school in Taiwan. Based on data envelopment analysis (DEA) and bootstrap truncated regression (BTR) model. The empirical results of this research indicate the following results: (1) Importing digital mobile e-learning can really enhance the efficiency of school management. (2) The results suggested in BTR model justifies that among the eight-factor analyses, six factors were overestimated and the factors with total equipment expenses and teacher-student ratio were under estimated by Tobit regression model (TRM). Also, the results for the effects of school location and school attribute on school?s operational efficiency were non-significant in TRM. In comparison, the estimated effects of school location and school attribute on school?s operational efficiency by BTR in this study are significant. Therefore, the factors studied here may be important in explaining the determinants of school efficiencies from innovative teaching through digital mobile e-Learning. To increase students learning effectiveness in school, it is necessary to first add school size, Tablet PC numbers, and technical teachers. However, the result shows total equipment expenses associated with tablet PC have a small negative influence on school management efficiency. On the other hand, the results show that the effect of school location, school attribute and school high-vocational attribute on school?s operational efficiency have significant. Mainly, the degree of school?s operational efficiency also needs to be taken into account their school attributes such as equipment, teaching quality, management decisions and etc. by digital mobile e-learning.

[1]  Gwo-Jen Hwang,et al.  A key step to understanding paradigm shifts in e-learning: towards context-aware ubiquitous learning , 2010, Br. J. Educ. Technol..

[2]  Li-Hua Li,et al.  The Operating Efficiency of Vocational and Senior High Schools in Xindian District of New Taipei City: Three Envelopment Models in DEA , 2016 .

[3]  Gwo-Jen Hwang,et al.  Criteria, Strategies and Research Issues of Context-Aware Ubiquitous Learning , 2008, J. Educ. Technol. Soc..

[4]  Nadire Cavus,et al.  Basic elements and characteristics of mobile learning , 2011 .

[5]  Hsiang-Hsi Liu,et al.  Operating Efficiency and its Effect from Innovative Teaching through Digital Mobile e-Learning for Public and Private High Schools , 2017 .

[6]  Timothy Coelli,et al.  An Introduction to Efficiency and Productivity Analysis , 1997 .

[7]  Jenny Eppard,et al.  The Next Generation of Technology: Mobile Apps in the English Language Classroom , 2016, Int. J. Emerg. Technol. Learn..

[8]  Gwo-Jen Hwang,et al.  Applications, impacts and trends of mobile technology-enhanced learning: a review of 2008-2012 publications in selected SSCI journals , 2014, Int. J. Mob. Learn. Organisation.

[9]  J. Hausman Specification tests in econometrics , 1978 .

[10]  Rajiv D. Banker,et al.  Analysis of Cost Variances for Management Control in Hospitals , 1990 .

[11]  Robert G. Dyson,et al.  Performance Measurement and Data Envelopment Analysis , 2000 .

[12]  P. McAndrew,et al.  USING MOBILE DEVICES FOR LEARNING IN INFORMAL SETTINGS: IS IT MOTIVATING? , 2006 .

[13]  R. Banker,et al.  A Comparative Application of Data Envelopment Analysis and Translog Methods: An Illustrative Study of Hospital Production , 1986 .

[14]  David Mayston,et al.  Educational Attainment and Resource Use: Mystery or Econometric Misspecification? , 1996 .

[15]  C. Lovell,et al.  Stochastic Frontier Analysis: Frontmatter , 2000 .

[16]  Ferial Khaddage,et al.  Advancing Mobile Learning in Formal and Informal Settings via Mobile App Technology: Where to From Here, and How? , 2016, J. Educ. Technol. Soc..

[17]  Laurel Evelyn Dyson,et al.  Directions for m-learning research to enhance active learning , 2007 .

[18]  D. Laurillard Pedagogical forms of mobile learning: framing research questions , 2007 .