ارائه مدل ارزیابی میزان رضایت کارکنان از سیستم مدیریت آموزش الکترونیکی (LMS)
محورهای موضوعی : روش های نوین آموزش وتوسعه منابع انسانیسیما سوفی نیارکی 1 , محمدجواد ارشادی 2 * , علی نعیمی صدیق 3
1 - دانشگاه آزاد واحد الکترونیکی
2 - پژوهشگاه علوم و فناوری اطلاعات ایران (ایرانداک)
3 - پژوهشگاه علوم و فناوری اطلاعات ایران (ایرانداک)
کلید واژه: آموزش الکترونیکی ارزیابی رضایت کارکنان سازمان ثبت اسناد وب¬, کوآل سیستم آموزش الکترونیکی (LMS) ,
چکیده مقاله :
امروزه سیستم آموزش الکترونیکی به بخشی جداناپذیر از یک سیستم آموزش در هرسازمانی تبدیل شده است. کارکنان سازمان ثبت اسناد و املاک بمنظور افزایش بهره‌وری و بخصوص کاهش اتلاف وقت و انرژی و همچنین استفاده از سطوح کاربری بالا و انعطاف پذیری در دریافت خدمات آموزشی تمایل زیادی به استفاده از خدمات آموزش الکترونیکی دارند و این موضوع موجب گسترش این نوع آموزش در سازمان شده است. بدر پژوهش حاضر ابعاد مختلف ارزیابی سیستم آموزش الکترونیکی برپایه مدل ای‌کوال توسعه داده شده است. سازمان ثبت اسناد باتوجه به پراکندگی جغرافیایی سازمان‌های اقماری و لزوم استفاده از این سیستم مورد مطالعه این پژوهش بوده است. مدل توسعه یافته از شاخص های مختلفی نظیر معیار ظاهری، محتوایی، امنیت، سازگاری با ابزارهای مجازی و غیره تشکیل شده است. بدین منظور، یک پرسشنامه 3 بعدی طراحی و توزیع شده است. در این پرسشنامه سوالات مورد نیاز برای ارزیابی میزان رضایت کارکنان طراحی شده و بین 80 نفر از کارمندان این سازمان توزیع شده است. نتایج ارزیابی و تحلیل آماری نشان می دهد که ویژگی ظاهری بالاترین اهمیت را از دید کاربران دارد و مسئله ی امنیت، از میزان اهمیت پائینی از نظر آنها برخوردار است. در انتها پیشنهادات اجرایی بمنظور بهبود کیفیت سیستم آموزش الکترونیکی ارائه شد.
Today, the e-learning system has become an integral part of a learning system at the cutting edge. The staff of the organization of registration of documents and real estate in order to increase productivity and especially reduce the waste of time and energy, as well as the use of high user levels and flexibility in receiving educational services are keen to use e-learning services, and this has led to the expansion of this type of training in the organization. Is. The present study has developed various aspects of the evaluation of the e-learning system based on the ECVAL model. The organization of registration of documents in view of the geographical dispersion of satellite organizations and the necessity of using this system have been studied in this study. The developed model consists of various indexes such as apparent standards, content, security, compatibility with virtual instruments, etc. To this end, a 3D questionnaire has been designed and distributed. In this questionnaire, questions were asked to evaluate employee satisfaction and distributed among 80 employees of this organization. The results of the evaluation and statistical analysis show that the apparent character is of the highest importance to the users, and the security issue is of low importance to them. Finally, executive suggestions were made to improve the quality of the e-learning system.
[1] Cloete, E. 2011. Electronic education system model. Computers & Education 36 (2): 171–182.
[2] Deng, W. J., Y. F. Kuo, and W. C. Chen. 2014. Revised importance–performance analysis: Threefactor theory and benchmarking. The Service Industries Journal 28 (1): 37-51.
[3] Elangovan, N. 2013. Evaluating perceived quality of B-School websites. Journal of Business and Management (IOSR-JBM) 12 (1): 92-102.
[4] Engelbrecht, E. 2015. Adapting to changing expectations: Postgraduate students’ experience of an elearning tax program. Computers & Education 45 (2): 217–229.
[5] Fazlollahtabar, H., M. Rezaie, and H. Eslami Nosratabadi. 2012. Applying Kano model for users' satisfaction assessment in e-learning systems: A case study in Iran virtual higher educational systems. International Journal of Information and Communication Technology Education 8 (3): 1-12.
[6] Fuller, J., and K. Matzler. 2016. Customer Delight and Market Segmentation: An Application of the Three-Factor Theory of Customer Satisfaction on Life Style Groups. Tourism Management 29 : 116-26.
[7] Grigoroudis, E., C. Litos, V. A. Moustakis, Y. Politis, and L. Tsironis. 2017. The assessment of userperceived web quality: Application of a satisfaction benchmarking approach. European Journal of Operational Research 187 (3): 1346–1357.
[8] Hermana, B. 2014. A review of empirical research on website quality measurement model based on consumer’s perception. International Conference on Internet Studies. August 16-17. Singapore. http://bhermana.staff.gunadarma.ac.id/Downloads/files/39312/A_REVIEW_OF_WEBSITE_Q ALI TY_NETS2014.pdf (accessed Dec. 18, 2014).
[9] Hudek, R., and N. Vrcek. 2016. E-service quality evaluation instruments. In Proceedings of MIPRO. http://bib.irb.hr/datoteka/284483.MIPRO2006.pdf (accessed Nov. 3, 2016).
[10] Jati, H., and D. Dominic. 2015. Quality evaluation of e-government website using web diagnostic tools: Asian case. Information Management and Engineering, April 3-5, 2015, Kuala Lumpur, India, 85 – 89. In Press with IEEE Publisher.
[11] Kahneman, D., and A. Tversky. 2010. Prospect theory: An analysis of decision under risk.
Econometrica 47 (2): 263-292.
[12] Kano, N., F. Seraku, F. Takahashi, and S. Tsuji. 2011. Attractive quality and Must Be quality,
Hinshitsu. Journal of the Japanese Society for Quality Control 14 (2): 147-156.
[13] Karatepe, O. M., U. Yavas, and E. Babskus. 2015. Measuring service quality- banks: Scale development and validation. Journal of Retailing and Consumer Services 12: 373-383.
[14] Kelly, B., and R. Vidgen. 2015. A quality framework for web site quality: User satisfaction and quality assurance. Poster in: WWW2005, Chiba.
[15] Kim, E. B, and S. B. Eom. 2012. Designing effective cyber store user interface. Industrial management and data systems 102 (5): 241-251.
[16] Liao, C, P. Palvia, and H. N. Lin. 2016. The roles of habit and website quality in e-commerce.
International Journal of Information Management 26 (6): 469-483.
[17] Martilla, J. A. and J. C. James. 2007. Importance-Performance Analysis. Journal of Marketing 41 (1): 77-79.
[18] Matzler, K., and E. Sauerwein. 2012. The Factor Structure of Customer Satisfaction: An Empirical Test of the Importance Grid and Penalty-Reward-Contrast Analysis. International Journal of Service Industry Management 13 (4): 314-32.
[19] Matzler, K., E. Sauerwein, and K. Heischmidt. 2013. Importance-performance analysis revisited: The role of the factor structure of customer satisfaction. The Service Industries Journal 23 (2): 112-129.
[20] Mikulić, J., and D. Prebežac. 2014. Prioritizing improvement of service attributes using impact rangeperformance analysis and impact-asymmetry analysis. Managing Service Quality 18 (6): 559-76.
[21] Mittal, V., and P. M. Baldasare. 2015. Eliminate the negative: Managers should optimize rather than maximize performance to enhance patient satisfaction. Journal of Health Care Marketing 16 (3): 24-31.
[22] Mittal, V., W. T. Ross, and P. M. Baldasare. 2006. The asymmetric impact of negative and positive attribute-level performance on overall satisfaction and repurchase intentions. Journal of Marketing 62 (1): 33-47.
[23] Negash, S., T. Ryan, and M. Igbariab. 2013. Quality and effectiveness in web-based customer support systems. Information & Management 40 (8): 757–768.
[24] Oh, J. C., S. J. Yoon, and B. I. Park. 2012. A structural approach to examine the quality attributes of shopping malls using the Kano model. Asia Pacific Journal of Marketing and Logistics 24 (2): 305-327.
[25] Reisetter, M., L. Lapointe, and J. Korcuska. 2015. The impact of altered realties: Implications of online delivery for learners’ interactions, expectations, and learning skills. International Journal on Elearning 6(1): 55-80.
[26] Trentin, G. 2016. The Xanadu project: Training faculty in the use of information and communication technology for university teaching. Journal of Computer Assisted Learning 22 (3): 182-196.
[27] Wan, Z., Y. Wang, and N. Haggerty. 2008. Why people benefit from e-learning differently: The effects of psychological processes on e-learning outcomes. Information & Management 45 (8): 513-521.
[28] Zhao, M., and Ruby R. Dholakia. 2009. A multi‐attribute model of web site interactivity and customer satisfaction. Managing Service Quality: An International Journal 19 (3): 286-307.
[29] Barnes, S., and R. Vidgen. 2011. Assessing the quality of auction web sites. Proceedings of the Hawaii International Conference on Systems Sciences. January 3-6. Maui, Hawaii. http://www.webqual.co.uk/papers/auction.pdf (accessed Nov. 15, 2014).
[30] Bauk, S., S. Scepanovic, and M. Kopp. 2014. Estimating students’ satisfaction with web based learning system in blended learning environment. Education Research International. http://dx.doi.org/10.1155/2014/731720 (accessed Aug. 8, 2015).
[31] Bressolless, G., and J. Nantel. 2014. Electronic service quality: A comparison of three measurements. Proceedings of the 33th EMAC Conference. Murcia, Spain. www.chairerbc.com/axisdocument.aspx?id=75&langue=en. true (accessed Apr. 25, 2015).
[32] Büyüközkan, G., D. Ruan, and O. Feyziog lu. 2007. Evaluating e-learning Website quality in a fuzzy environment. International Journal of Intelligent Systems 22 (5): 567–586.
[33] Büyüközkan, G., J. Arsenyan, and G. Ertek. 2010. Evaluation of e-Learning web sites using fuzzy axiomatic design based approach. International Journal of Computational Intelligence Systems 3 (1): 28-42.