4John F. Gantz et al: The Diverse and Explo- ding Digital Universe: An Updated Forecast of World- wide Information Growth through 2011 [ EB/OL]. Fram- ingham, MA: IDC, 2008. http://www, emc. com/col- lateral/analyst - reports/diverse - exploding - digital - universe, pdf.
5V. Farrokhi, L. Pokorddi. The necessities for building a model to evaluate Business Intelligence pro- jects Literature Review [ J ]. International Journal of Computer Science & Engineering Survey (IJCSES), 2012(2) :1 - 10.
6Dave Wells. Institutional Intelligence : Applying business intelligence principles to higher education [ EB/ OL]. Campus Technology, 2007. http://campus tech- nology, com/ articles /2007/04/institutional - intelli- gence, aspx. V 81 S. E1Atia. D. IDDerciel. A. Hammad. ImDlica-gence, aspx.
7S. E1Atia, D. Ipperciel, A. Hammad. Implica- tions and Challenges to Using Data Mining in Education- al Research in the Canadian Context [ J ]. Canadian Journal of Education, 2012(2) : 101 - 119.
8Tinto, V. Dropout from Higher Education: A Theoretical Synthesis of Recent Research [ J]. Review of Educational Research, 1975 (45) :89 - 125.
9Richard H.Brodhead. Global Duke:Enhancing Students Capacity for World Citizenship[DB/OL].http://www.provost.duke.edu/QEP-fanal-version-Feb09.pdf,.
10The International Labor Organization. Impact of structural adjustment on the employment and trai-ning of teachers[M].Geneva,Switzerland:ILO,Sectoral Activities Programme,1996.6-12.