The User Characteristics Effects to Smart Board Usage on Technology Acceptance Model Variables
Yasar Akca · Gokhan Ozer · Ayse Derya Isik · Ercan Celik
International Journal of Research in Business and Social Science · 2017 · Vol. 6 / Issue 1 · 106-116
Publication metrics
External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.
Dimensions
Live provider badge. If unavailable, use the Dimensions link above.
Observed 21 Oct 2026, 07:22 UTC
Observed 22 Oct 2026 01:36 UTC
Observed 22 Oct 2026 01:36 UTC
OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.
Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.
2017–2026 Annual history last updated:
Citations received
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
View data & coverage
2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.
Abstract
A new technology’s acceptance also gets shaped according to users’ features, expectations and perceptions. Technology Acceptance Model (TAM) that developed by Davis (1989), defends that there are perceived usefulness and perceived ease of use variables to determinants of a new technology’s usage by user. These perceptions predict the user’s behavior and explain it. The smart board that has common usage in modern classrooms provides effectiveness at education and learning activities. Teachers who use smart boards can present more effectively. This situation increases the teacher’s productivity and student’s learning success and improvement the class’s education quality. Existence of the smart board in the classroom motivates all by self. Thanks to this technological device, it is easy to access internet based study materials. This study’s purpose is testing the user features explanation power effects to usage of smart board, which is a new education tool, based on TAM variables. For performing of the research, surveys have actualized with 24 teachers at Bartin High School with smart boards. Survey data have been interpreted based on correlation, factor and regression analyses in WarpPLS 5.0. Results have been concluded from analyse strongly supports research model.
Keywords: {'name': 'User Characteristics'}, {'name': 'Technology Acceptance Model'}, {'name': 'FATIH Project'}, {'name': 'Smart Board'}
Authors & affiliations
Yasar Akca
Affiliation not supplied
Gokhan Ozer
Affiliation not supplied
Ayse Derya Isik
Affiliation not supplied
Ercan Celik
Affiliation not supplied
Deposited references
Supplied references, not a list of publications citing this article.
DOI: 10.1016/S0167-9236(97)00006-7
DOI: 10.1109/17.649864
DOI: 10.1080/014492999119020
DOI: 10.1016/j.compedu.2010.10.024
DOI: 10.2307/25148828
DOI: 10.1016/S1467-0895(03)00026-5
DOI: 10.1111/j.1540-5915.2001.tb00978.x
DOI: 10.1080/10447318.2016.1179083
Cronbach, L.J. (2004). My current thoughts on coefficient alpha and successor procedures, University of California, CSE Report 643, 1-32. Retrieved November 18, 2016, from https://www.cse.ucla.edu/products/reports/r643.pdf
DOI: 10.1023/A:1015221710638
DOI: 10.2307/249008
DOI: 10.1287/mnsc.35.8.982
Demirli, C. and Türel, Y.K. (2012). Interactive whiteboards in higher education: Instructors first impressions, Eurasian Journal of Educational Research, 49, 199-214.
DOI: 10.1016/S0378-7206(98)00090-1
DOI: 10.1016/j.im.2003.08.010
DOI: 10.1016/j.sbspro.2010.03.936
Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2009). Multivariate Data Analysis: A Global Perspective. 7th ed. New Jersey: Upper Saddle River, Prentice Hall.
DOI: 10.1111/j.1365-2729.2005.00118.x
DOI: 10.1016/S0378-7206(01)00134-3
http://fatihprojesi.meb.gov.tr/proje-hakkinda/ (date of access 25.05.2016)
DOI: 10.1080/07421222.1995.11518061
DOI: 10.1016/S0378-7206(99)00032-4
DOI: 10.1016/j.im.2006.03.007
DOI: 10.1016/j.ijmedinf.2006.09.001
DOI: 10.2307/20650309
DOI: 10.1016/j.im.2006.05.003
Kock, N. (2015). WarpPLS 5.0 User Manual, Texas: ScriptWarp Systems.
DOI: 10.1016/j.sbspro.2013.06.113
DOI: 10.1016/S0167-9236(00)00068-3
DOI: 10.2307/25148692
DOI: 10.1016/S0378-7206(01)00143-4
DOI: 10.1108/10662240310478222
DOI: 10.4018/joeuc.2004010104
DOI: 10.1177/001872679905200107
DOI: 10.1016/j.im.2003.12.013
DOI: 10.1016/j.compedu.2011.10.017
DOI: 10.1287/mnsc.46.2.186.11926
DOI: 10.2307/3250981
DOI: 10.1111/j.1467-8535.2007.00703.x
DOI: 10.1016/S0167-9236(03)00062-9
DOI: 10.2307/248807
DOI: 10.2307/249712
DOI: 10.1016/j.ijpe.2004.09.004
DOI: 10.17705/1CAIS.01205