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Education and Information Technologies
Erschienen in: Education and Information Technologies 3/2019

17.01.2019

A new integrated model to explore factors that influence adoption of mobile learning in higher education: An empirical investigation

verfasst von: Faisal Aburub, Ibrahim Alnawas

Erschienen in: Education and Information Technologies | Ausgabe 3/2019

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Abstract

The aim of this paper is to test the combined effect of the key components of the Technology Acceptance Model (TAM) and those of the Usage and Gratification Approach (U&G) on intention to adopt mobile learning in higher education. Data were collected from 820 students from ten universities in Jordan. Structural equation modeling (AMOS 18) was used to analyze the data. The findings of the current research reveal that perceived ease of use and cognitive gratification had the highest impact on intention to adopt mobile learning; perceived usefulness and hedonic gratification had the lowest effect; and personal integrative gratification had no effect. The key contribution of this research stems from the integration of two major theories into a broader conceptualization in order to test their combined effect on intention to adopt mobile learning in higher education.
Vorheriger Artikel Mobile learning technology acceptance in Saudi Arabian higher education: an extended framework and A mixed-method study
Nächster Artikel Reexamining the impact of self-determination theory on learning outcomes in the online learning environment

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Literatur
Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model for E-learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238–256.
Adegbija, M. V., & Bola, O. O. (2015). Perception of undergraduates on the adoption of Mobile Technologies for Learning in selected universities in Kwara state, Nigeria. Procedia-Social and Behavioral Sciences, 176, 352–356.
Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93–102.
Almaiah, M., Jalil, M., and Man, M. (2016). Empirical investigation to explore factors that achieve high quality of mobile learning system based on students’ perspectives. Engineering Science and Technology, an International Journal. Article in Press.
Ardi, P. (2017). Promoting learner autonomy through Schoology M-learning platform in an EAP class at an Indonesian University. Teaching English with Technology, 17(2), 55–76.
Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F. J. (2017). Learning with mobile technologies–students’ behavior. Computers in Human Behavior, 72, 612–620.
Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8–19.
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054–1064.
Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160–175.
Coursaris, C. K., & Kim, D. J. (2011). A meta-analytical review of empirical mobile usability studies. Journal of Usability Studies, 6(3), 117–171.
Criollo-C, S., Luján-Mora, S. and Jaramillo-Alcázar, A., 2018. Advantages and Disadvantages of M-Learning in Current Education. In 2018 IEEE World Engineering Education Conference (EDUNINE) (pp. 1–6). IEEE.
Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers in Education, 123, 53–64.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–340.
Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487.
Dobos, J., & Dimmick, J. (1988). Factor analysis and gratification constructs. Journal of Broadcasting & Electronic Media, 32(3), 335–350.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research (18:1), 39–50.
Grissa, K., 2017. What “Uses and Gratifications” Theory Can Tell Us About Using Professional Networking Sites (EG LinkedIn, Viadeo, Xing, SkilledAfricans, Plaxo…). In International Conference on Digital Economy (pp. 15–28). Springer, Cham.
Ha, Y. W., Kim, J., Libaque-Saenz, C. F., Chang, Y., & Park, M. C. (2015). Use and gratifications of mobile SNSs: Facebook and KakaoTalk in Korea. Telematics and Informatics, 32(3), 425–438.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, L. R. (2006). Multivariate data analysis (6th ed.). New Jersey: Prentice Hall.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (pp. 277–319). Emerald Group Publishing Limited.
Hwang, G. J., & Tsai, C. C. (2011). Research trends in mobile and ubiquitous learning: A review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology, 42(4), E65–E70.
James, M. L., Wotring, C. E., & Forrest, E. J. (1995). An exploratory study of the perceived benefits of electronic bulletin board use and their impact on other communication activities. Journal of Broadcasting & Electronic Media, 39(1), 30–50.
Joo, J., & Sang, Y. (2013). Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Computers in Human Behavior, 29(6), 2512–2518.
Khan, A. I., Al-Shihi, H., Al-Khanjari, Z. A., & Sarrab, M. (2015). Mobile learning (M-learning) adoption in the Middle East: Lessons learned from the educationally advanced countries. Telematics and Informatics, 32(4), 909–920.
Kutluk, F. A., & Gülmez, M. (2014). A research about mobile learning perspectives of university students who have accounting lessons. Procedia-Social and Behavioral Sciences, 116, 291–297.
Lijanporn, S., & Khlaisang, J. (2015). The development of an activity-based learning model using educational mobile application to enhance discipline of elementary school students. Procedia-Social and Behavioral Sciences, 174, 1707–1712.
Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599–607.
Louis, R. S. (2006). Helping students become autonomous learners: Can technology help? Teaching English with Technology, 6(3).
Mbarek, R., & El Gharbi, J. E. (2013). A meta-analysis of e-learning effectiveness antecedent. International journal of innovation and applied. Studies, 3(1), 48–58.
Muhammed, A. A. (2014). The impact of mobiles on language learning on the part of English foreign language (EFL) university students. Procedia-Social and Behavioral Sciences, 136, 104–108.
Musa, A. S., Azmi, M. N. L., & Ismail, N. S. (2015). Exploring the uses and gratifications theory in the use of social media among the students of mass communication in Nigeria. Malaysian Journal of Distance Education, 17(2), 83–95.
Muttoo, S., 2011. Mobile’changes in the Arab world. Retrieved October, 14, p.2012.
Nambisan, S., & Baron, R. A. (2007). Interactions in virtual customer environments: Implications for product support and customer relationship management. Journal of Interactive Marketing, 21(2), 42–62.
Nistor, N., Baltes, B., Dascălu, M., Mihăilă, D., Smeaton, G., & Trăuşan-Matu, Ş. (2014). Participation in virtual academic communities of practice under the influence of technology acceptance and community factors. A learning analytics application. Computers in Human Behavior, 34, 339–344.
Ordóñez de Pablos, P. ed., (2014). Assessing the role of mobile technologies and distance learning in higher education. IGI Global.
Padilla-Meléndez, A., Del Aguila-Obra, A. R., & Garrido-Moreno, A. (2013). Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Computers & Education, 63, 306–317.
Palmgreen, P. (1984). Uses and gratifications: A theoretical perspective. In R. N. Bostrom (Ed.), Communication yearbook (Vol. 8, pp. 20–55). Beverly Hills: Sage.
Palmgreen, P., Wenner, L. A., & Rayburn, J. D. (1980). Relations between gratifications sought and obtained: A study of television news. Communication Research, 7(2), 161–192.
Park, N. (2010). Adoption and use of computer-based voice over internet protocol phone service: Toward an integrated model. Journal of Communication, 60(1), 40–72.
Persico, D., Manca, S., & Pozzi, F. (2014). Adapting the technology acceptance model to evaluate the innovative potential of e-learning systems. Computers in Human Behavior, 30, 614–622.
Pew Research Center, (2017). Mobile fact sheet. Pew Research Center: Internet, Science & Tech.
Phang, C. W., Kankanhalli, A., & Sabherwal, R. (2009). Usability and sociability in online communities: A comparative study of knowledge seeking and contribution. Journal of the Association for Information Systems, 10(10), 721–747.
Pimmer, C., Mateescu, M., & Gröhbiel, U. (2016). Mobile and ubiquitous learning in higher education settings. A systematic review of empirical studies. Computers in Human Behavior, 63, 490–501.
Pollara, P., & Broussard, K. K. (2011). Mobile technology and student learning: What does current research reveal?. International Journal of Mobile and Blended Learning (IJMBL), 3(3), 34–42.
Poushter, J. (2016). Smartphone ownership and internet usage continues to climb in emerging economies. Pew Research Center, 22, 1–44.
Reychav, I., & Wu, D. (2014). Exploring mobile tablet training for road safety: A uses and gratifications perspective. Computers & Education, 71, 43–55.
Roca, J. C., Chiu, C. M. & Martínez, F.J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of human-computer studies, 64(8), 683–696.
Rubin, A. M. (1984). Ritualized and instrumental television viewing. Journal of Communication, 34(3), 67–77.
Shin, D. H. (2011). Understanding e-book users: Uses and gratification expectancy model. New Media & Society, 13(2), 260–278.
Shyu, S. H. P., & Huang, J. H. (2011). Elucidating usage of e-government learning: A perspective of the extended technology acceptance model. Government Information Quarterly, 28(4), 491–502.
Soleimani, E., Ismail, K., & Mustaffa, R. (2014). The acceptance of mobile assisted language learning (MALL) among post graduate ESL students in UKM. Procedia-Social and Behavioral Sciences, 118, 457–462.
Spiegel, A., & Rodríguez, G. (2016). Students at university have Mobile technologies. Do they do m-learning? Procedia-Social and Behavioral Sciences, 217, 846–850.
Taleb, Z., & Sohrabi, A. (2012). Learning on the move: The use of mobile technology to support learning for university students. Procedia-Social and Behavioral Sciences, 69, 1102–1109.
Tan, G. W. H., Ooi, K. B., Leong, L. Y., & Lin, B. (2014). Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-neural networks approach. Computers in Human Behavior, 36, 198–213.
Teo, T., Lee, C. B., & Chai, C. S. (2008). Understanding pre-service teachers' computer attitudes: Applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2), 128–143.
Utluk, F. A., & Gülmez, M. (2014). A research about mobile learning perspectives of university students who have accounting lessons. Procedia-Social and Behavioral Sciences, 116, 291–297.
Valero, C., Roura Redondo, M. and Sanchez Palacín, A. (2012). Tendencias actuales en el uso de dispositivos móviles en educación. La Educ@ción digital magazine, 147. Available at:
Viberg, O., & Grönlund, Å. (2013). Cross-cultural analysis of users' attitudes toward the use of mobile devices in second and foreign language learning in higher education: A case from Sweden and China. Computers & Education, 69, 169–180.
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.
Metadaten
Titel
A new integrated model to explore factors that influence adoption of mobile learning in higher education: An empirical investigation
verfasst von
Faisal Aburub
Ibrahim Alnawas
Publikationsdatum
17.01.2019
Verlag
Springer US
Erschienen in
Education and Information Technologies / Ausgabe 3/2019
Print ISSN: 1360-2357
Elektronische ISSN: 1573-7608
DOI
https://doi.org/10.1007/s10639-019-09862-x

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