The Enriched UTAUT Model for the Acceptance of Software Engineering Tools in Academic Education

References

• Ajzen, I. (1991). The theory of planned behavior. Behavior and Human Decision Processes, 50, 179–211.
   Web of Science ®Google Scholar
• Alrawashdeh, T. A., Muhairat, M. I., & Alqatawnah, S. (2012). Factors affecting acceptance of web-based training system: Using extended UTAUT and structural equation modeling. Retrieved from https://arxiv.org/abs/1205.1904
   Google Scholar
• Anderson, J., Schwager, P., & Kerns, R. (2006). The drivers for acceptance of tablet PCs by faculty in a College of Business. Journal of Information Systems Education, 17(4), 429–440.
   Google Scholar
• Blanc, X., Gervais, M. P., & Sriplakich, P. (2005). Model bus: Towards the interoperability of modelling tools. In Model driven architecture. Berlin Heidelberg: Springer.
   Google Scholar
• Bollen, K. A. (2005). Structural equation models. In Encyclopedia of Biostatistics; Second Edition. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258. doi:10.1177/0049124192021002005
   Web of Science ®Google Scholar
• Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications and programming. (2nd ed.). New York: Routledge.
   Google Scholar
• Compeau, D. R., & Higgins, C. A. (1995). Computer self efficacy: Development of a measure and initial test. MIS Quarterly, 19, 189–211.
   Web of Science ®Google Scholar
• Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003. doi:10.1287/mnsc.35.8.982
   Web of Science ®Google Scholar
• 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. doi:10.1111/jasp.1992.22.issue-14
   Web of Science ®Google Scholar
• Day, N. A., & Joyce, J. J. (2000, June). A framework for multi-notation requirements specification and analysis. In Requirements Engineering, 2000. Proceedings. 4th International Conference on IEEE, Schaumburg, IL.
   Google Scholar
• Dunn, T. J., Baguley, T., & Brunsden, V. (2013). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412.
   PubMed Web of Science ®Google Scholar
• Giannakos, M., & Vlamos, P. (2011, June). Identifying the predictors of educational webcasts’ adoption. In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education. ACM, New York. pp. 376–376.
   Google Scholar
• Hair, J. F., & Black, W. C. (2009). Multivariate data analysis. (7th International Economy Edition). Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Kaiser, H. (1974). An index of factorial simplicity. Psychometrika, 39, 31–36. doi:10.1007/BF02291575
   Web of Science ®Google Scholar
• Kern, H., & Kuhne, S. (2007, October). Model interchange between ARIS and eclipse EMF. In 7th OOPSLA Workshop on Domain-Specific Modeling at OOPSLA. ACM, University of Jyväskylä at Finland. pp. 105–114.
   Google Scholar
• Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The technology acceptance model: Past, present and future. Communications of the Association for Information Systems, 12(1), 752–780.
   Google Scholar
• Lundell, B., Lings, B., Persson, A., & Mattsson, A. (2006). UML model interchange in heterogeneous tool environments: An analysis of adoptions of XMI 2. In Model Driven Engineering Languages and Systems (pp. 619–630). Berlin Heidelberg: Springer.
   Google Scholar
• Marchewka, J. T., Liu, C., & Kostiwa, K. (2014). An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7, 2.
   Google Scholar
• Marcinkowski, B., & Wrycza, S. (2015, November). CASE tools’ acceptance in higher education – Assessment and enhanced UTAUT model. In 2015 Conference on Information Systems Applied Research Proceedings. Information Systems and Computing Academic Professionals, Wilmington, NC.
   Google Scholar
• Marques, B. P., Villate, J. E., & Carvalho, C. V. (2011, June). Applying the UTAUT model in engineering higher education: Teacher’s technology adoption. In Information Systems and Technologies (CISTI), 2011 6th Iberian Conference on IEEE, Chaves, Portugal.
   Google Scholar
• Martinig & Associates. (2014). UML unified modeling language tools: Use cases, class diagram, sequence diagram, object diagram, MDA. Retrieved from http://www.umltools.net
   Google Scholar
• Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. doi:10.1287/isre.2.3.192
   Web of Science ®Google Scholar
• Object Management Group (OMG). (2012). UML vendor directory listing. Retrieved from http://uml-directory.omg.org/vendor/list.htm
   Google Scholar
• Oye, N. D., Iahad, N. A., & Rahim, N. A. (2014). The history of UTAUT model and its impact on ICT acceptance and usage by academicians. Education and Information Technologies, 19(1), 251–270. doi:10.1007/s10639-012-9189-9
   Google Scholar
• Phahlane, M. M., & Kekwaletswe, R. M. (2014, March). Management information systems use in higher education environments. In Proceedings of the Southern Association for Information Systems Conference. AIS, Atlanta.
   Google Scholar
• Prieto, J. C. S., Miguelanez, S. O., & Garcia-Penalvo, F. J. (2014, October). Mobile learning adoption from informal into formal: An extended TAM model to measure mobile acceptance among teachers. In Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality. ACM, New York. pp. 595–602.
   Google Scholar
• Roca, J. C., Chiu, C. M., & Martinez, 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. doi:10.1016/j.ijhcs.2006.01.003
   Web of Science ®Google Scholar
• Roy, J. F., Kealey, J., & Amyot, D. (2006). Towards integrated tool support for the user requirements notation. In System Analysis and Modeling: Language Profiles (pp. 198–215). Berlin Heidelberg: Springer.
   Google Scholar
• Schaper, L. K., & Pervan, G. P. (2007). ICT and OTS: A model of information and communication technology acceptance and utilizations by occupational therapist. International Journal of Medical Informatics, 76, S212–S221. doi:10.1016/j.ijmedinf.2006.05.028
   PubMedGoogle Scholar
• Schmitt, N. (1996). Uses and abuses of coefficient alpha. Psychological Assessment, 8(4), 350–353. doi:10.1037/1040-3590.8.4.350
   Web of Science ®Google Scholar
• Sekaran, U., & Bougie, R. (2013). Research methods for business – A skill building approach (6th ed.). Hoboken, NJ: John Wiley and Sons.
   Google Scholar
• Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s Alpha. Psychometrika, 74(1), 107–120. doi:10.1007/s11336-008-9101-0
   PubMed Web of Science ®Google Scholar
• Smith, T. D., & McMillan, B. F. (2001). A primer of model fit indices in structural equation modeling. Retrieved from http://files.eric.ed.gov/fulltext/ED449231.pdf
   Google Scholar
• Sorebo, O., Halvari, H., Gulli, V. F., & Kristiansen, R. (2009). The role of self-determination theory in explaining teachers’ motivation to continue to use e-learning technology. Computers & Education, 53(4), 1177–1187. doi:10.1016/j.compedu.2009.06.001
   Web of Science ®Google Scholar
• Straub, D., Keil, M., & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management, 33(1), 1–11. doi:10.1016/S0378-7206(97)00026-8
   Web of Science ®Google Scholar
• Sumak, B., Polancic, G., & Hericko, M. (2010). An empirical study of virtual learning environment adoption using UTAUT. In Mobile, Hybrid, and On-Line Learning, 2010. ELML’10. Second International Conference on IEEE, Saint Maarten, Netherlands.
   Google Scholar
• Taneja, A. (2009). The influence of personal response systems on students’ perceived learning outcomes and course satisfaction. Journal of Computing Sciences in Colleges, 25, 2.
   Google Scholar
• Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. doi:10.1287/isre.6.2.144
   Web of Science ®Google Scholar
• Tibenderana, P. K., & Ogao, P. J. (2008). Acceptance and use of electronic library services in Ugandan universities. In Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries. ACM, New York, pp. 323–332.
   Google Scholar
• Tomar, N. (2011). Computer aided software engineering tools (CASE). Retrieved from http://www.c-sharpcorner.com/UploadFile/nipuntomar/computer-aided-software-engineering-tools-case
   Google Scholar
• van der Merwe, T. M., & van Heerden, M. E. (2013). Ease of use and usefulness of webinars in an open distance learning environment: An activity theory perspective. In Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference. ACM, New York, pp. 262–270.
   Google Scholar
• Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. doi:10.1111/j.1540-5915.2008.00192.x
   Web of Science ®Google Scholar
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478.
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
   Web of Science ®Google Scholar
• Williams, M., Rana, N., Dwivedi, Y., & Lal, B. (2011, June). Is UTAUT really used or just cited for the sake of it? A systematic review of citations of UTAUT’s originating article. In ECIS 2011: The 19th European Conference on Information Systems: ICT and Sustainable Service Development, Helsinki, Finland.
   Google Scholar
• Wong, K.-T., Teo, T., & Russo, S. (2013). Interactive whiteboard acceptance: Applicability of the UTAUT model to student teachers. The Asia-Pacific Education Researcher, 22(1), 1–10. doi:10.1007/s40299-012-0001-9
   Web of Science ®Google Scholar
• Xiong, J., Tripathi, A., Nguyen, C., & Najjar, L. (2014). Information and communication technology for development: Evidence from MOOCs adoption. In Proceedings of the Ninth Midwest Association for Information Systems Conference. AIS, Atlanta.
   Google Scholar