A Study of the driving factors in integration and application of distant education and representing a model for distant education

Subject Areas : Research in Curriculum Planning

hossein najafi ¹ , mehran farajolahi ² , norozzadeh reza ³ , reza sarmadi ⁴

1 - 1استادیار گروه علوم تربیتی، دانشگاه پیام نور، ایران
2 - 2 دانشیار گروه علوم تربیتی، دانشگاه پیام نور، ایران
3 - 3 استادیار گروه علوم تربیتی، مؤسسه پژوهش و برنامه ریزی در آموزش عالی
4 - 4 استاد گروه علوم تربیتی، دانشگاه پیام نور، ایران

Received: 2017-10-17 Accepted : 2017-10-17 Published : 2014-12-22

Keywords: technology integration and application, modeling distant education, PNU,

Abstract :

The purpose of the present research was to study the driving factors in integration and application of distant education in PhD courses of Payame Noor University. In order to identify the fundamental factors, a researcher-made questionnaire, consisting of 5 scales and 36 sub-scales, was given to 30 distant education experts. . From a population of 1082 people, 136 were selected as the sample, using random sampling and Cochran’s formula, and the questionnaire was distributed among them. Descriptive statistics as well as inferential analysis mean, slandered diviation, Pearson correlation coefficient, and exploratory analysis were applied for data analysis in SPSS 18 and LISREL 8.53. Based on the initial findings, these were the self-sufficiency, technological skillfulness, practicality, easy access, and comprehensive support which were identified as the driving factors in integration and application of distance education. The correlation coefficients for these factors were 64%, 52%, 49%, 47%, and 39%, respectively. The final results of LISREL analysis showed that the coefficients of determination for the above factors are 27%, 66%, 77%, 61%, and 80%, respectively, indicating the positive relationship of these factors with integration, application, and modeling of distant education. Chi-square to df ratio (2.172) was less than 3, the value of RMSEA (0.0018) was less than the threshold ( ), -value (0.2132) was greater than the threshold ( ), and the values of GFI (0.91) and AGFI (0.90) were equal to or greater than the threshold (0.90), all suggesting the goodness of fit of the model and indicating significant relationships between the five main scales.

References:

Al- Ruz, J, Khasawneh, S. (2011). Jordanian pre- Service Teachers and Technology Integration: A Human Resource Development Approach, Educational Technology &Society, 14(4), 77-87. Anderson, S.E. & Menninger, R.M. (2007).Pre-service teacher’s abilities, beliefs, and intentions regarding tearing technology integration. Journal of Educational computing Research.37 (2), 151-172 Bandera, A., (1997).Self-Efficacy: The Exercise of control. New York: Freeman. Bandera, A., Adams, N.E., & Beyer, J. (1977). Cognitive processes mediating behavior change. Journal of personality and social psychology, 35(3), 125-139. Banister’s., & Vinnitsa, R. (2006). Beginning with a baseline: insuring productive teacher education. Journal of teacher education. 14(1), 209-235. Brown & Warschauer. (2006). from the university to the elementary classroom: students’ experiences in learning to integrate technology in instruction. Journal of technology and teacher education, 14(3), 599-621. Chen, L.L. (2005). Pedagogical strategies to increase pre-service teacher’s confidence in computer learning. Educational technology and society, 7(3), 50-60. Culp, K. M., honey, M., & mandinach, E. (2003).A retrospective on twenty years of education technology policy. Washington. DC: US. Department of education, office of educational technology. Dawson, C., & Rakes, G. C. (2003).the influence of principals’ technology training on integration of technology into schools. Journal of research on technology in education, 36(1), 29-49. Dexter, S., & Riedel, E. (2003). Why improving pre-service teacher education technology preparation must go beyond the college walls. Journal of teacher education, 54, 340-346. Ebrahimzadeh, I. (2007). Transfer from Traditional university to university: Innovation and challenge of change. Research and higher education programining, No. 43, pp.7-14. Ebrahimzadeh, I, (2005). Training based on ICT: conceptual inquiries, quarterly periodical of Payame Noor, fourth year, NO.4, pp 8-17. Fulton, K., glen, A. D., & Valdez, G. (2004). Teacher education and technology planning guide. North central regional education laboratory, learning point Associates. Ghfari, G., Khazempoor,E., & Hussein Mehr.,A.(2011).designing of ICT-Based Curriculum Model and ITS impact in performance of cognitive affective and skills in high school students, , Research in Curriculum planning, ,NO,1. VO, pp, 8. Grassed, C. P., & Loud, B. H. (1986). Validation studies of a new computer attitude scale. Association for education Data System journal, 19, 295-301. Hair, J.E., Anderson, R.E., Tat ham, R.L., &Balk, W.C. (1998). Multivariate data analysis .upper saddle Review NJ: prentice Hall. Harris, C.M. (2002). Is multimedia-based instruction Hawthorne revisited? Is difference? Education, 122(4), 839-843. Hernandez-Ramos. (2005).if not here, where? Understanding teacher use of technology in Silicon Valley schools. Journal of research on technology in education, 38(1), 39-64. Jacobsen, M., Clifford. P., & freshen, S. (2002). Preparing teachers for technology integration: creating a culture of inquiry in the context of use. Contemporary issues in technology and teacher education. 2(3), 363-388. Morris. M. (2002).How new teachers use technology in the classroom. Paper presented at the Annual Summer Conference of the Association of teacher education, Williamsburg, VA. Najafi, H. (2013). Cost effective analysis model of distance learning and electronic based on Wagner's and Jove's views, learning and Education. Najafi, H. (2012). Foundations of distance education pedagogy and its theories, Research in Curriculum planning, VO, 9.NO, 7. Najafi, H. (2011). The Role of Information and Communication Technology in the Evolution of Teaching – Learning, the Quarterly Journal of Payame Noor University, NO, 1.Vo, 9. Norris. C., Sullivan, t., poi rot, G., & solo way, E. (2003). No access, on use no impact: snapshot surveys of educational technology in k-12. Journal of research on technology in education, 36(1), 15-27. Rezaie Rad, M. (2012). Identifying the success in e learning programs, Research in Curriculum planning, No, 6.Vo, 9. Seyeed Naghavi, M.A. (2011). The study Students' attitudes to learning in professor and student: a survey of e-learning in universities with E –Learning in Iran, Quarterly Journal of Research and Planning in Higher Education,No,43 Asmarkolla, C. (2009).Technology acceptance among student teachers and experienced classroom teachers. Journal of educational computing research, 37(1).43 82. Asmarkolla, C. (2008).Efficacy of apparent behavior model: beliefs that contribute to computer usage intention of student teacher and expensed teachers .computers in human behavior, 24(3), 1184 1214 Topper, A. (2004) .How is we doing? Using self assessment to measured changing teacher Technology literacy whiten a gradate educational technology program. Journal of technology and teacher education, 12(3), 303 317. Wall, A. (2004).An evaluation of the computer self-efficacy of preserves teachers. Unpublished dissertation, Tennessee state university, Nashville, Tennessee. Zhao, & frank, K.A. (2003).factors affecting technology uses in schools: An ecological perspective. American educated educational research Journal, 40(4), 807-840.  

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