EVALUASI KINERJA MAHASISWA BERDASARKAN TEKNOLOGI SMARTPHONE MENGGUNAKAN METODE MODIFIED TASK-TECHNOLOGY FIT

Mohammad Fauzan Bahadjai, Wing Wahyu Winarno, Paulus Insap Santosa

Abstract


 Di masa perkembangan teknologi informasi dan komunikasi melaju dengan pesat, smartphone muncul dengan bentuk, kemampuan dan daya tarik yang luar biasa serta menawarkan layanan yang bervariasi, baik untuk pelaku bisnis maupun masyarakat biasa. Tidak hanya itu, kepopuleran smartphone akhirnya menggeser teknologi pendahulunya, notebook dan PDA. Teknologi ini sudah tidak asing lagi di kalangan mahasiswa. Namun, apakah pemanfaatan teknologi ini sudah sesuai dengan aktifitas dan tugas mereka sebagai mahasiswa secara optimal masih belum menemukan titik terang. VARK Learning Styles merupakan suatu konsep yang memahami karakteristik gaya belajar mahasiswa yang terdiri dari Visual (penglihatan), Aural (pendengaran), Read/write (Baca/tulis) dan Kinesthetic (Praktek secara langsung). Setiap mahasiswa memiliki gaya belajar sendiri dalam memahami materi yang didapatkan. Oleh karena itu, penelitian ini akan menguji keselarasan karakteristik tugas, teknologi dan individu dan pengaruhnya terhadap pemanfaatan dan kinerja mahasiswa. Dengan menggunakan metode Task- Technology Fit yang dimodifikasi dengan menambahkan karakteristik individu berdasarkan konsep VARK Learning Styles. Penelitian ini diharapkan menjawab hipotesis yang ada dan membuktikan berdasarkan data bahwa karakteristik gaya belajar seseorang akan selaras dengan penggunaan teknologi dalam menyelesaikan tugas hingga berpengaruh positif terhadap peningkatkan kinerja.


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References


M. Sarwar and T. R. Soomro, “Impact of Smartphone’s on Society,” vol. 98, no. 2, pp. 216–226, 2013.

Y. F. Chang, C. S. Chen, and H. Zhou, “Smart phone for mobile commerce,” Comput. Stand. Interfaces, vol. 31, no. 4, pp. 740– 747, Jun. 2009.

“41 Juta Masyarakat Indonesia Miliki Smartphone, 95%-nya Digunakan di Rumah.” [Online]. Available: http://www.themarketeers. com/archives/41-juta-masyarakat-indonesia-milikismartphone- 95nya-digunakan-di-rumah.html#.U01llOJ3v4s. [Accessed: 15-Apr-2014].

“Statistics Indonesia.” [Online]. Available: http://www.bps.go.id/tab_sub/view.php?tabel=1&id_subyek=12. [Accessed: 02-Nov-2014].

E. Rogers, “Diffusion of Innovation, 5th Edition,” Free Press 2003, 2003.

Y. Bang, K. Han, A. Animesh, and M. Hwang, “FROM ONLINE TO MOBILE : LINKING CONSUMERS ’ ONLINE PURCHASE BEHAVIORS WITH MOBILE COMMERCE.”

L. Chen, W. Wang, X. Du, X. Rao, M. H. van Velthoven, R. Yang, L. Zhang, J. C. Koepsell, Y. Li, Q. Wu, and Y. Zhang, “Effectiveness of a smart phone app on improving immunization of children in rural Sichuan Province, China: study protocol for a paired cluster randomized controlled trial.,” BMC Public Health, vol. 14, no. 1, p. 262, Jan. 2014.

N. I. Conference, M. Business, N. Global, and M. Roundtable, “Analysis of Smartphone User Behavior,” pp. 259–264, 2010.

R. Basole, “Enterprise Mobility: Applications, technology and strategies,” IOS Press, 2008.

S. Balasubramaniam, R. . Peterson, and S. . Jarvenpaa, “Exploring the Implications of M-commerce for Markets and Marketing,” Acad. Mark. Sci., vol. 30, no. 4, pp. 348–361, 2002.

E. Scornavacca and S. J. Barnes, “The Strategic Value of Enterprise Mobility: Case study insights,” Inf. Knowl. Syst. Manag., vol. 7, no. 1,2, pp. 227–241, 2008.

M. Hanley and R. E. Boostrom, “How the Smartphone is Changing College Student Mobile Content Usage and Advertising Acceptance:,” 2008.

M. Kumar, “Impact of the Evolution of Smart Phones in Education Technology and its Application in Technical and Professional Studies: Indian Perspective,” Int. J. Manag. Inf. Technol., vol. 3, no. 3, pp. 39–49, Aug. 2011.

“Why Use Mobile Device in Education?” [Online]. Available: Http://www.ehow.com/about_6164403_use-mobile-deviceseducation_. html. [Accessed: 04-Jun-2014].

J. Mareš, Styly učení žáků a studentů. Praha: Portal, 1998, p. 77.

E. Bhattacharyya and A. B. M. S. @ Shariff, “Learning Style and its Impact in Higher Education and Human Capital Needs,” Procedia - Soc. Behav. Sci., vol. 123, pp. 485–494, Mar. 2014.

M. Klement, “How do my Students Study? An Analysis of Students’ of Educational Disciplines Favorite Learning Styles According to VARK Classification,” Procedia - Soc. Behav. Sci., vol. 132, pp. 384–390, May 2014.

N. D. Fleming and C. Mills, “Not Another Inventory , Rather a Catalyst for Reflection,” vol. 11, 1992.

D. L. Goodhue, “Understanding User Evaluations of Information Systems,” Manage. Sci., vol. 41, no. 12, pp. 1827–1844, Dec. 1995.

D. L. Goodhue and R. L. Thompson, “Task-Technology Fit and Individual Performance,” MIS Q., vol. 19, no. 2, p. 213, Jun. 1995.

W. H. DeLone and E. R. McLean, “Information System Success: The Quest for the Dependent Variable,",” Inf. Syst. Res., vol. 3, no. 1, pp. 60–95, 1992.

R. Chompu-inwai and T. Doolen, “A Methodology for Studying the Impact of Laptops in Engineering Classrooms,” Proceedings. Front. Educ. 36th Annu. Conf., pp. 20–25, 2006.

S. Akter, “Application of the Task-Technology Fit Model to Structure and Evaluate the Adoption of E-Books by Academics,” vol. 64, no. 1, pp. 48–64, 2013.

N. Fleming, “I’m different; not dumb. Modes of presentation (VARK) in the tertiary classroom,” Res. Dev. High. Educ. …, pp. 1–7, 1995.

“Definition of Smartphone in Oxford Dictionary (British & World English).” [Online]. Available: http://www.oxforddictionaries.com/definition/english/smartphone . [Accessed: 04-Jun-2014].

T. Kim, E. S. Jung, and Y. Im, “Optimal control location for the customer-oriented design of smart phones,” Inf. Sci. (Ny)., vol. 257, pp. 264–275, Feb. 2014.

H. Verkasalo, C. López-nicolás, F. J. Molina-castillo, and H. Bouwman, “Analysis of users and non-users of smartphone applications,” Telemat. Informatics, vol. 27, no. 3, pp. 242–255, 2010.

“The iPhone is not a smartphone.” [Online]. Available: http://www.engadget.com/2007/01/09/the-iphone-is-not-asmartphone/. [Accessed: 21-Nov-2014].

“The VARK Modalities | VARK.” [Online]. Available: http://varklearncom.digiwebhosting.com/introduction-tovark/ the-vark-modalities/. [Accessed: 21-Nov-2014].

L. Robertson and T. Smellie, “Learning Styles and Fieldwork Education: Students’ Perspectives,” New Zeal. J. …, vol. 58, no. 1, pp. 36–40, 2011.

M. Sholihin and D. Ratmono, Analisis SEM-PLS dengan WarpPLS 3.0 untuk Hubungan Nonlinear dalam Penelitian Sosial dan Bisnis. Yogyakarta: ANDI Offset, 2013.

D. L. Goodhue, R. Littlefield, and D. Straub, “The measurement of the impacts of the IIC on the end-users: The survey,” J. Am. Soc. Inf. Sci., vol. 48, no. 5, pp. 454–465, 1997.

A. I. Shirani, M. H. A. Tafti, and J. F. Affisco, “Task and technology fit: A comparison of two technologies for synchronous and asynchronous group communication,” Inf. Manag., vol. 36, no. 3, pp. 139–150, 1999.

F. Belanger, R. W. Collins, and P. H. Cheney, “Technology requirements and workgroup communications for telecommuters,” Inf. Syst. Res., vol. 12, no. 2, pp. 155–176, 2001.

A. D. Carswell and V. Venkatesh, “Learner outputs in an asynchronous distance education environment,” Int. J. Human– Computer Stud., vol. 56, no. 5, pp. 475–494, 2002.

L. Carswell, P. Thomas, M. Petre, B. Price, and M. Richards, “Distance education via the Internet: The student experience,” Br. J. Educ. Technol., vol. 31, no. 1, pp. 29–46, 2000.

D. L. Goodhue, “Development and measurement validity of a task-technology fit instrument for user evaluations of information systems Decision Sciences,” vol. 29, no. 1, pp. 105–138, 1998.

T. J. McGill and J. E. Klobas, “A task-technology fit view of learning management system impact,” Comput. Educ., vol. 52, no. 2, pp. 496–508, 2009.

N. Nan, “Capturing bottom-up information technology use processes: A complex adaptive systems model,” MIS Q., vol. 35, no. 2, pp. 505–532, 2011.

R. M. Fuller and A. R. Dennis, “Does fit matter? The impact of task-technology fit and appropriation on team performance in repeated tasks,” Inf. Syst. Res., vol. 20, no. 1, pp. 2–17, 2009.


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