تبیین ابقاء دانشجو بر اساس ویژگی های روانشناختی، تجارب قبلی، پیشینه تحصیلی، مهارت های مدیریتی و کامپیوتری در محیط یادگیری الکترونیکی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 هیئت علمی

2 دانشگاه پیام نور

3 عضو هیئت علمی دانشگاه پیام نور

چکیده

این پژوهش با هدف بررسی رابطه ویژگی های روانشناختی، تجارب قبلی، پیشینه تحصیلی، مهارت های مدیریتی و کامپیوتری با ابقاء دانشجو در محیط یادگیری الکترونیکی انجام شده است. پژوهش حاضر از نظر هدف، کاربردی- کمی و از نظر نحوه گردآوری داده ها توصیفی- پیمایشی است. جامعه آماری شامل دانشجویان الکترونیکی فعال دانشگاه پیام نور است. اعتبار محتوایی ابزار پژوهش توسط5 نفر از اساتید محترم راهنما، مشاور و خبرگان مورد تایید قرار گرفت. به منظور تعیین روایی سازه ابزار اندازه گیری، از روش تحلیل عاملی تأییدی استفاده شد. پایایی ابزار پژوهش نیز با استفاده از روش آلفای کرونباخ0.83 برآورد شد. داده های جمع آوری شده در قالب دو دسته تحلیل های آمار توصیفی و استنباطی(تحلیل عاملی تأییدی و رگرسیون) تجزیه و تحلیل شد. نتایج آزمون همبستگی پیرسون وجود رابطه معنادار بین پیشینه تحصیلی و ابقاء دانشجو(0.17)، تجارب قبلی و ابقاء دانشجو(0.14) ، مهارت های مدیریت کامپیوتری و ابقاء دانشجو (0.47)، و ویژگی های روانشناختی و ابقاء دانشجو (0.52) را نشان داد. نتایج رگرسیون همزمان نیز نشان داد متغیرهای پیش بین حدود 76 درصد از تغییرات ابقاء دانشجو را تبیین می کنند.

چکیده تصویری

تبیین ابقاء دانشجو بر اساس ویژگی های روانشناختی، تجارب قبلی، پیشینه تحصیلی، مهارت های مدیریتی و کامپیوتری در محیط یادگیری الکترونیکی

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Explaining student retention based on psychological characteristics, previous experiences, academic background, management and computer skills in the e-learning environment.

نویسندگان [English]

  • zohreh esmaeili 1
  • mohammadreza sarmadi 2
  • bahman saeidipour 3
2 Departement of Educational Sciences and Psychology, Payame Noor University
3 Departement of Educational Sciences and Psychology, Payame Noor University
چکیده [English]

This research was conducted to investigate the relationship between psychological characteristics, previous experiences, academic background, management and computer skills and student retention in an e-learning environment. The present research is practical-quantitative in terms of its purpose and descriptive-survey in terms of collecting data. The statistical population in this study encompasses the electronical active students of Payame Noor University. To confirm the content validity of the research tool, experts were used. And also a confirmatory factor analysis was used to determine the validity of the measurement instrument's structure. All of the questions variables were fitted with factor load. The reliability of the tool was confirmed by the Cronbach's alpha coefficient which was equal to 0.83. The results of data collection after adjustment and tabling were analyzed by statistical tests (exploratory and confirmatory factor analysis). The results of Pearson correlation test showed a significant relationship between academic background and student retention (0.17), previous experiences and student retention (0.14), computer management skills and student retention (0.47), and psychological characteristics and student retention (0.52). The results of simultaneous regression also showed that predictor variables account for about 76% of student retention changes.

کلیدواژه‌ها [English]

  • psychological characteristics
  • previous experiences
  • academic background
  • management and computer skills
  • student retention

 

[1] Halkett, R. (2001). E-learning: Research and how to survive it. Industrial and Commercial Training, 34(2), 80-82.

[2] Lee, B. C. H.,Yoon, J., & Lee, I. (2009). Learners acceptance of e-learning in south korea: Theories and results. Computers & Education, 53,1320-1329

[3] Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. Chronicle of Higher Education, 46)23(, 39-41.

[4] Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48(2), 185-204.

[5] Tello, S. F. (2007). An analysis of student persistence in online education. International Journal of Information and Communication Technology Education, 3(3), 47-62.

[6] Berg Z. L., & Huang, Y.P.(2004), A model for sustainable student retention: A holistic perspective on the student dropout problem with special attention to e-Learning. DEOSNEWS, 13(5), 97-108.

[7] Frankola, K. (2001), Why online learners drop out. Workforce, 8(3), 53-58.

[8] Diaz D. P.(2002). Online drop rate revisited. Technology Source. Retrived from https://www.westga.edu/~distance/ojdla/summer122/patterson112.html

[9] Patterson, B., & McFadden, C.(2009). Attrition in online and campus degree programs.OJDLA, 12(2). Retrived from https://www.westga.edu/~distance/ojdla/summer122/patterson112.html

[10] Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education, 54(2), 506-516.

[11] Willging, P. A., & Johnson, S. D. (2004). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 8(4), 105–118.

[12] Ally, M. (2004). Foundations of educational theory for online learning. In Anderson, T. and Elloumi, F. (Eds.) Theory and practice of online learning (pp. 15-44). Canada: Athabasca University

[13] Morris, L. V., Finnegan, C., & Wu, S. (2005). Tracking student behavior, persistence, and achievement in online courses. The Internet and Higher Education, 8(3), 221–231.

[14] Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. Chronicle of Higher Education, 46(23), 39-41.

[15] Nesler, M. (1999). Factors associated with retention in a distance-based liberal arts program.Paper presented at the northeast association for institutional r

esearch. Newport, Wales.

[16] Kember, D. (1989). A longitudinal-process model of drop-out from distance education. The Journal of Higher Education, 60(3), 278-301.

[17] Parker, A. (2003). Identifying predictors of academic persistence in distance education. United States Distance Learning Association Journal, 17(1), 55–61.

[18] Fortoft, N. (1995). Predicting persistence in distance learning programs. Paper presented at the mid-western education research meeting, Chicago, IL.

[19] Svedberg, M. K.(2010). Self-directed learning and persistence in online asynchronous undergraduate programs (Unpublished doctoral dissertation). Virginia polytechnic institute and state university, US.

[20] Joo, Y., Joung, S., & Sim, W. (2011). Structural relationships among internal locus of control, institutional support, flow, and learner persistence in cyber universities. Computers in Human Behavior, 27(2), 714–722.

[21] Gianakos, I. (2002). Predictors of coping with work stress: The influences of sex, gender-role, social desirability, and locus of control. Sex Roles, 46(5), 149–158.

[22] Krause, N., & Stryker, S. (1984). Stress and well-being: The buffering role of locus of control beliefs. Social Science & Medicine, 18(9), 783–790.

[23]Babaei, M. (2010). Introduction to electronic learning. Tehran: Iran's science and information technology research institute and chapar publishing. [in Persian]

[24] Hart, C.(2012) Factors associate sociated with student persistence in an online program off study: A review of the literature. Journal of Interactive Online Learning, 11(1),19-42.

[25] Osborn, V. (2001). Identifying at-risk students in videoconferencing and web-based distance education. American Journal of Distance Education, 15(1), 41–54.

[26] Ivankova, N. V., & Stick, S. L. (2007). Students’ persistence in a distributed doctoral program in educational leadership in higher education: A mixed methods study. Research in Higher Education, 48(1), 93–135.

[27] Cheung, L. L. W., & Kan, A. C. N. (2002). Evaluation of factors related to student performance in a distance-learning business communication course. Journal of Education for Business, 77(5), 257.

[28] Castles, J. (2004). Persistence and the adult learner: Factors affecting persistence in open university students. Active Learning in Higher Education, 5(2), 166-179.

[29] Holder, B.(2007). An investigation of hope, academics, environment, and motivation as predictors of persistence in higher education online programs. Internet and Higher Education, 10(4), 245–260.

[30] Moore, K., Bartkovich, J., Fetzner, M., & Ison, S. (2003). Success in cyberspace: Student retention in online courses. Journal of Applied Research in the Community College, 10(2), 107-118.

[31] Mu¨ller, T. (2008). Persistence of women in online degree-completion programs. International Review of Research in Open and Distance Learning, 9(2), 1-18.

[32] Dupin-Bryant, P. (2004). Pre-entry variables related to retention in online distance education. American Journal of Distance Education, 18(4), 199–206.

[33] Hong, K. S. (2002). Relationships between student’ and instructional variables with satisfaction and learning from a web-based course. The Internet and Higher Education, 5, 267–281.

[34] Roca, J. C., & Gagne, M. (2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavio , 24, 1585–1604.

[35] Pituch, K. A., Lee, Y. K. (2006). The influence of system characteristics on e-learning use. Computers & Education,47, 222-244.

[36] Xenos, M., Pierrakeas, C., & Pintelas, P. (2002).A survey on student dropout rates and dropout causes concerning the students in the course of informatics. Computers & Education, 39(4), 361-377.