نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری حسابداری، دانشگاه شیراز، شیراز، ایران

2 دانشجوی دکتری حسابداری، دانشگاه آزاد اسلامی، واحد بندرعباس، ایران

چکیده

هدف از پژوهش حاضر، بررسی رابطه پذیرش و استفاده از فناوری توسعه‏یافته با یادگیری سیار در دانشجویان حسابداری بود. این پژوهش کاربردی و از نوع توصیفی- همبستگی بوده و جامعه آن دانشجویان حسابداری مقاطع و دانشگاه‏های مختلف کشور بودند که 141 نفر با استفاده از نمونه‏گیری تصادفی ساده انتخاب شدند. برای سنجش متغیرها نیز از پرسشنامه استاندارد فاگان (2019) پس از تائید روایی و پایایی استفاده‏ شد. همچنین، دوره زمانی موردمطالعه، سال تحصیلی 1397-1398 است. برای آزمون فرضیه‏ها نیز از تحلیل معادلات ساختاری استفاده ‏شد. یافته‏ها نشان داد که بین پذیرش و استفاده از فناوری توسعه‏یافته و یادگیری سیار رابطه مثبت و معنادار (80 درصد) در سطح اطمینان 95 درصد وجود دارد. سایر یافته‏ها نیز نشان داد که بین امید به تلاش و یادگیری سیار (67 درصد)، بین امید به عملکرد و یادگیری سیار (31 درصد)، بین تأثیرهای اجتماعی و یادگیری سیار (21 درصد)، بین انگیزه و یادگیری سیار (19 درصد)، بین انگیزه و امید به تلاش (71 درصد) و بین انگیزه و امید به عملکرد (73 درصد) رابطه مثبت و معناداری در سطح اطمینان 95 درصد وجود دارد. همچنین، اثر معنادار سن و جنس بر یادگیری نیز مشاهده نشد. باوجودآنکه پژوهش‏های آموزش حسابداری تاکنون چندان متمرکز بر پیاده‏سازی یادگیری سیار نبوده‏اند، استفاده از ابزارهای الکترونیکی شخصی از قبیل گوشی‏های هوشمند برای یادگیری روبه گسترش است و متناسب با نیازهای اجتماعی کنونی بوده که این مهم انگیزه دانشجویان و رضایت‏مندی نسبت به محتوای یادگیری را ارتقا می‏بخشد.

کلیدواژه‌ها

عنوان مقاله [English]

The Relationship between Adoption and Use of Technology with Mobile Learning in Accounting Students

نویسندگان [English]

  • Alireza Momtazian 1
  • Hossein Rajabdorri 2

1 Ph.D. Candidate of Accounting in Shiraz university

2 Ph.D. Candidate of Accounting and Member of Young Researchers and Elite Club, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran

چکیده [English]

The purpose of this study was to identify the relationship between adoption and use of technology (UTAUT) on M- learning in accounting students. This research is a descriptive- correlational study and the population is 141 students of accounting in Iran which was selected using simple random sampling. Fagan's (2019) standard questionnaire after validity and reliability was used to measure the variables. Also, the period studied is the academic year 2018-2019. Structural equation analysis and Smart PLS software were also used to test the hypotheses. Findings showed (in 95% confidence level) that there is a positive and significant relationship (80 %) between UTAUT and M- learning. Other Findings also found that between effort expectancy (EE) and M- learning is 67 percentage, between performance expectancy (PE) and M- learning is 31 percentage, between social influences and M- learning is 21 percentage, between motivation and M- learning is 19 percentage There was a significant positive relationship between motivation and EE is 71 percentage and motivation and PE is 73 percentage. Also, there was no significant effect of age and gender on M- learning. Although accounting education research has so far not focused on M- learning implementation, the use of personalized electronic tools such as smartphones for learning is expanding and tailored to current social needs, which enhances student motivation and satisfaction with learning content.

کلیدواژه‌ها [English]

  • Technology
  • M-Learning
  • Accounting Students
  • Performance Expectancy
  • Effort Expectancy
باغومیان، ر.، رجب‏دری، ح. و خرمین، م. (1396). بررسی رابطه میان عوامل شخصیتی و یادگیری دانشجویان حسابداری. مطالعات تجربی حسابداری مالی، 14 (55)، 125- 143.
باغومیان، ر. و رحیمی، ع. (1390). موانع پیشرفت آموزش حسابداری در ایران. مطالعات تجربی حسابداری مالی، 9 (35)، 69-91.
باغومیان، ر.، محمدی، ح. و عرب‏زاده، آ. (1394). رفع شکاف بین تئوری حسابداری و نیازهای عملی حسابداران در بازار کار: نقش آموزش حسابداری. حسابرس، 81، 82- 86.
رضایی، م. (1388). نظریه‏های رایج درباره پذیرش فناوری اطلاعات و ارتباطات. فصلنامه پژوهش‏های ارتباطی، 4 (60)، 63- 93.
قشقایی، ف. و مشایخ، ش. (1398). تدوین مدل بلوغ فرایند پذیری و فناوری اطلاعات در واحد حسابداری. دانش حسابداری و حسابرسی مدیریت، 8 (29)، 91- 118.
مؤمنی، م. و فعال‏قیومی، ع. (1389). تحلیل‏های آماری با استفاده از SPSS. تهران: کتاب نو.
همتی، ح.، پرتوی، ن. و ابراهیمی، م. (1393). بررسی و شناسایی نگرش حاکم بر آموزش حسابداری در دانشگاه‏ها (دیدگاه سنتی یا دیدگاه اخلاقی). تحقیقات حسابداری و حسابرسی، 23، 56- 69.
References
Althunibat, A. (2015). Determining the factors influencing students’ intention to use m-learning in Jordan higher education. Computers in Human Behavior, 52, 65-71.
Arqueroa, J., Fernández-Polvillob, C., Hassallc, T., and Joyceca, J. (2015). Relationships between communication apprehension, ambiguity tolerance and learning styles in accounting students. Spanish Accounting Review, 70, 1- 12.
Bogaards, P. (2000). Aptitude et Affectivité Dans l’apprentissage des L angues étrangères. Paris: Crédif.
Spector, P., & Brannick, M. T. (2011). Methodological urban legends: The misuse of statistical control variables. Organizational Research Methods, 14(2), 287–305.
Brière, E. J. (1978). Variables Affecting Native Mexican Children’s Learning Spanish as a Second Language. Language Learning, 28, 159-174.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426.
Cyr, P., & Germain, C. (1998). Les Stratégies D’apprentissages. Paris: C. L. E. International.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. New York, NY: Plenum Press.
Decman, M. (2015). Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender. Computers in Human Behavior, 49, 272–281.
DeLozier, S. J., & Rhodes, M. G. (2016). Flipped Classrooms: a Review of Key Ideas and Recommendations for Practice. Educational Psychology Review, 29(1), 141-151.
Fagan, M. (2019). Factors Influencing Student Acceptance of Mobile Learning in Higher Education. Computers in the Schools, 36 (2), 105-121.
Fagan, M. H., Neill, S., & Wooldridge, B. R. (2008). Exploring intention to use computers: An empirical investigation of the role of intrinsic motivation, extrinsic motivation, and perceived ease of use. Journal of Computer Information Systems, 48(3), 31–37.
Gaebel, M., Zhang, T., Bunescu, L., & Stoeber, H. (2018). Trends 2018: Learning and teaching in the European Higher Education Area. European University Association (EUA), Brussels, Belgium.
Gerow, J. E., Ayyagari, R., Thatcher, J. B., & Roth, P. L. (2009). Is intrinsic motivation as important in utilitarian systems as it is in hedonic systems?, A preliminary meta-analysis. Proceedings of the 15th Americas Conference on Information Systems:AMCIS 2009 (Paper 671), San Francisco, CA.
Hwang, G., Yang, T., Tasi, C., & Yang, S. J. H. (2009). A context-aware ubiquitous learning environment for conducting complex science experiments. Computers & Education, 53(2), 402–413.
Jeno, L. M., Grytnes, J-A., Vandvik, V., & Deci, E. L. (2018). The effects of m learning ‐ on motivation, achievement and well‐being: A Self‐Determination Theory approach. British Journal of Educational Technology, 50(2), 669-683.
Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(1), 752–780.
Lewis, C. C., Fretwell, C. E., Ryan, J., & Parnham, J. B. (2013). Faculty use of established and emerging technologies in higher education: A unified theory of acceptance and use of technology perspective. International Journal of Higher Education, 2(2), 22–34.
Liaw, S. S., & Huang, H. M. (2012). A case of Study of Investigating Users’ Acceptance Toward Mobile Learning. In F. Gaol (Ed.), Recent progress in data engineering and Internet technology (pp. 299–305). Berlin, Germany: Springer.
Marzuki, M., Subramaniam, N., Cooper, B., & Dellaportas, S. (2017). Accounting Academics’ Teaching Self-Efficacy and Ethics Integration in Accounting Courses: A Malaysian Study. Asian Review of Accounting, 25(1), 1- 38.
Nikou, S. A., & Economides, A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers & Education, 109, 56–73.
Raman, A., & Don, Y. (2013). Preservice teachers’ acceptance of learning management software: An application of the UTAUT2 model. International Education Studies, 6(7), 157–164.
Raman, A., & Don, Y. (2013). Preservice teachers’ acceptance of learning management software: An application of the UTAUT2 model. International Education Studies, 6(7), 157–164.
Roediger H., & Pyc, M.A. (2012). Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice, Journal of Applied Research in Memory and Cognition, 1(4), 242-248.
Russ, T. L. (2012). Preferences in an organizational setting the relationship between communication apprehension and learning. Journal of Business Communication, 49(4), 312–331.
Sandu, I., Giesbers, B., & Roelofsen, E. (2019). Reinforcing Accounting: A Case Study on using M-Learning in a Technology- Enhanced Bachelor Course. In J. Theo Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 1827-1834). Amsterdam, Netherlands: Association for the Advancement of Computing in Education (AACE). Retrieved September 24, 2019 from.
Spanjers, I. A. E., Könings, K. D., Leppink, J., Verstegen, D. M. L., de Jong, N., Czabanowska, K., & Van Merriënboer, J. J. G. (2015). The promised land of blended learning: Quizzes as a Moderator. Educational Research Review, 15, 59-74.
Ting, Y. (2012). The pitfalls of mobile devices in learning: A different view and implications for pedagogical design. Journal of Educational Computing Research, 46(2), 119–134.
Tosuntas, S. B., Karadag, E., & Orhan, S. (2015). The factors affecting acceptance and use of interactive whiteboard within the scope of the FATIH project: A structural equation COMPUTERS IN THE SCHOOLS 119 model based upon the unified theory of acceptance and use of technology. Computers & Education, 81, 169–178.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.
Venkatesh, V., & Speier, C. (1999). Computer technology training in the workplace: A longitudinal investigation of the effect of mood. Organizational Behavior and HumanDecision Processes, 79(1), 1–28.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Venkatesh, V., Sykes, T. A., & Zhang, X. (2011). Just what the doctor ordered’: A revised UTAUT for EMR system adoption and use by doctors. Proceedings of the 44th Hawaii International Conference on System Sciences (HICSS), Washington, DC: IEEE Computer Society.
Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92–118.
Waterman, A. S., Schwartz, S. J., & Conti, R. (2008). The implications of two conceptions of happiness (hedonic enjoyment and eudaimonia) for the understanding of intrinsic motivation. Journal of Happiness Studies, 9(1), 41–79.
Wu, W. H., Wu, Y. C. J., Chen, C. Y., Kao, H. Y., Lin, C. H., & Huang, S. H. (2012). Review of trends from mobile learning studies: A meta-analysis. Computers & Education, 59(2), 817–827.
Yi, M. Y., & Hwang, Y. (2003). Predicting the use of web-based information systems: Selfefficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 431–449.