Abolghasemi, M. & Mirali Rostami. O. (2013). The investigation of the effective factors on the academic achievements of Tehran engineering departments students for submitting a model to predicting their academic achievements. Iranian Journal of Engineering education.58, 67-84.
Biggs, J. and Tang. C. (2011). Teaching for Quality Learning at University. London. Open University Press.
Blass, E., Jasman, A. & Shelley, S. (2010). Visioning 2035: The Future of the Higher Education Sector in the UK. Futures, 42, 445–453.
Changhui, K. (2007). Classroom Peer Effects and Academic Achievement: Quasi-Randomization Evidence from South Korea. Journal of Urban Economics, 61, 458–495.
Chen, S. and Voyles, D. (2013). HESI Admission Assessment Scores: Predicting Student Success. Journal of Professional Nursing, 9(25): 32–37
Cristescu.M. s. (2013). Differenced instruction – methodological and practical demarches. Procedia - Social and Behavioral Sciences, 76, 759 – 764
Figen, A. (2010). Talented and Average Intelligent Children’s Levels of Using Emotional Intelligence, Procedia Social and Behavioral Sciences, 5, 553–558
Fischer, K. and Müller, K. (2014). Gifted Education and Talent Support in Germany.CEPS Journal,4(3), 31-43
Jonassen, D. H. and Grabowski.B. L. Handbook of individual differences, learning and instruction. Lawrence Erlbaum Associates Publishers, New Jercy. 1993.
Fry, H., ketteridge, S. and Marshal, S. A Handbook for Teaching and Learning in Higher Education: Enhancing academic practice. Routledge. 2014. England.
Gil-Galván, R., & Gil-Galván, F. J. (2013). How to Use Professional and Life Projects to Guide University Students towards Optimal Professional Development. Procedia - Social and Behavioral Sciences, 93, 1901 – 1905.
Gqweta, N. (2012). A perspective of final year diagnostic radiography students. Radiography,18, 212-217
Hardinger, K. L., Schauner, S., Graham, M., &Garavalia, L. (2013). Admission Predictors of Academic Dismissal for Provisional and Traditionally Admitted Students. Currents in Pharmacy Teaching and Learning, 5, 33–38
Javanmard, Sh. & Safaee Movahhed, S. (2018). Educational Needs Assessment of Kharazmi University New Faculty Members in 2014-Academic Year of 2013- 2014. Journal of Management and Planning in Educational Systems, 10 (2), 87-106
Kuznetsova, E. and Regnier. J. C. (2014). Individualization of Educational Process according to C. Freinet: A Pilot Experiment in a Group of Language Learners. Procedia - Social and Behavioral Sciences, 154, 87 – 91
Knauss, P. J. &Wilsson, P. (2013). Predicting Early Academic Success: HESI Admissions Assessment Exam. Journal of Professional Nursing, 29, 28-31
Mahmoodi, D. P. & Raboo, A. (2018). Using Educational Data Mining for Grouping Learners in an E-Learning Environment for Customizing Learning Program. Journal of Management and Planning in Educational Systems, 11 (1), 83-108
McCaffery, P. The Higher Education Manager's Handbook: Effective Leadership and Management in Universities and Colleges. Routledge, England, 2010.
Monzurur Rahman. S. M. (2006). Data Mining Using Neural Networks. A thesis Submitted in fulfillment of the requirements for the Degree of Doctor of Philosophy. RMIT University
Mutai, E. K., Cheruiyot, T. K. and Kirui, J. K. (2015). Impact of participatory Management on employee performance: a case of MOI University. Global institute for research and education,4(2), 54- 59
National Association for Gifted Children. (2010). Pre-K to Grade 12 Gifted Programming Standards.
Nistor, N., & Neubauer, K. (2010). From Participation to Dropout: Quantitative Participation Patterns in Online University Courses. Computers &Education, 55, 663-672.
Nonis, S. A., Hudson, G., Philhours, M. J., &Teng, J. K. (2005). Changes in College Student Composition and Implications for Marketing Education: Revisiting Predictors of Academic Success. Journal of Business Research, 58, 321– 329.
Operating Standards for Identifying and Serving Gifted Students, (2008). Ohio Administrative report.
Pena, A, A. (2014). Educational data mining: a survey and a data mining based analysis of recent work. Expert Systems with Applications, 41 1432–1462
Pooshneh, k. & Malmir, F. (2017). Elementary school teacher`s attitude toward inclusive education. Journal of Management and Planning in Educational Systems 2017, 10 (1), 147-157
Supreme Council of the Cultural Revolution. (1390). Naghsheye jame elmie keshvar. Dabirkhaneye shoraye aalie enghelabe farhangi.
Ramsden, p. Learning to Teach in Higher Education. Psychology Press, 2007. London & New York.
Rodgers, S., Stenhouse, R., McCreaddie, M., & Small, P. (2013). Recruitment, Selection and Retention of Nursing and Midwifery Students in Scottish Universities. Nurse Education Today,
33, 1301–131.
Rosander, P., Bäckström, M., & Stenberg, G. (2011). Personality Traits and General Intelligence as Predictors of Academic Performance: A Structural Equation Modeling Approach. Learning and Individual Differences, 21, 590–596
Shagholi, R. and Sufean, H. (2009). Participatory management: an opportunity for human resources in education. Procedia Social and Behavioral Sciences, 1, 1939–1943
Stukalina, Y. (2013). Management of the Educational Environment: The Context in Which Strategic Decisions Are Made. Procedia - Social and Behavioral Sciences, 99, 1054 – 1062
Su, Y., Feng, L. Yang, C. & Chen, T. (2012). How Teachers Support University Students’ Lifelong Learning Development for Sustainable Futures: The Student’s Perspective. Futures, 44, 158–165
U.S. Department of Education, for Each and Every Child—A Strategy for Education Equity and Excellence, Washington, D.C., 2013
Willcockson, I. U., Johnson, C. W., Hersh, W. & Bernstam, E. V. (2009). Predictors of Student Success in Graduate Biomedical Informatics Training: Introductory Course and Program Success. Journal of the American Medical Informatics Association,16, 837–846
)