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Year 2015, Volume: 11 Issue: 1, 68 - 88, 16.01.2015

Abstract

Many studies were conducted to find an answer to a question of how individuals' beliefs and attitudes affect their use of information communication technologies (ICT). Based on these studies, theories were developed and used in different disciplines in order to model individuals' behavioural intention to use technology. Among these, The Technology Acceptance Model (TAM) has been used to establish a theoretical-base to assess user acceptance considering different culture and gender samples. The purpose of this study was to investigate a model that predicts the level of technology acceptance by pre-service teachers at a teacher training institute. Data was collected from 337 (female-205, male-132) pre-service elementary teachers by employing TAM to reveal their purposes of technology use. The resulting model was found to have a good fit. Six variables that were expected to affect pre-service teachers' acceptance of technology (computer selfefficacy, facilitating conditions, technological complexity, attitude towards technology use, perceived ease of use, perceived usefulness) explained the purpose of technology use by accounting the variances of 35% among male and 44 % among female pre-service teachers. It was also found that perceived usefulness and computer self-efficacy were the most influential variables in explaining behavioural intention to use technology for both genders

References

  • Ajzen, I. ve Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior, Prentice-Hall. Upper Saddle River, NJ.
  • Akkoyunlu, B. ve Orhan, F. (2003). Relationship between computer usage self-efficacy and their demographic characteristics of teacher candidates. The Turkish Online Journal of Educational Technology, 2(3), 86-93.
  • Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory, NJ: Prentice Hall, Englewood Cliffs.
  • Bao, Y., Xiong, T., Hu, Z., & Kibelloh, M. (2013). Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption. Journal of Educational Computing Research, 49(1), 111-132.
  • Bebetsos, E. ve Antonıou, P. (2009). Gender Differences On Attitudes, Computer Use And Physical Activity Among Greek University Students. The Turkish Online Journal of Educational Technology, 8, 2, 6.
  • Bunz, U., Curry, C., & Voon, W. (2007). Perceived versus actual computer-email-web fluency. Computers in Human Behavior, 23(5), 2321-2344.
  • Cheon, J., Lee, S., Crooks, S. M. ve Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behaviour. Computers and Education, 59(3), 1054-1064.
  • Cheung, W. ve Huang, W. (2005). Proposing a framework to assess internet usage in university education: an empirical investigation from a student’s perspective. British Journal of Educational Technology, 36(2), 237–253.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
  • Compeau, D.R. ve Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Demetriadis, S., Barbas, A., Molohides, A., Palaigeorgiou, G., Psillos, D., Vlahavas, I.,Tsoukalas, I. ve Pombortsis, A. (2003). Culture in negotiation: Teachers’ acceptance/resistance attitudes considering the infusion of technology into schools. Computer & Education, 41(1), 19–37.
  • Dishaw M.T. ve Strong D.M.(1999).Extending the Technology Acceptance Model With Task-Technology Fit Constructs. Information & Management, 36(1), 9-21.
  • Escobar-Rodriguez, T. ve Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58(4), 1085–1093.
  • Fishbein, M. ve Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
  • Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: a study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 8.
  • Groves, M. M. ve Zemel, P. C. (2000). Instructional technology adoption in higher education: An action research case study. International Journal of Instructional Media, 27(1), 57–65.
  • Gülbahar, Y. (2008). Improving the technology integration skills of prospective teachers through practice: A case study. Turkish Online Journal of Educational Technology, 7(4), 1-11.
  • Güldü, Ö. ve Ersoy-Kart, M.(2009). Toplumsal cinsiyet rolleri ve siyasal tutumlar:Sosyal psikolojik bir değerlendirme. Ankara Üniversitesi SBF Dergisi, 64(3), 97-116.
  • Kiraz, E. ve Ozdemir, D. (2006). The Relationship between Educational Ideologies and Technology Acceptance in Pre-service Teachers. Educational Technology & Society, 9(2), 152-165.
  • Knight, C. M., Knight, B. A. ve Teghe, D. (2006). Releasing the pedagogical power of information and communication technology for learners: A case study, International Journal of Education and Development using Information and Communication Technology, 2(2), 27-34.
  • Legris, P., Ingham, J. ve Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204.
  • Lim, C. P. ve Hang, D. (2003). An activity theory approach to research of ICT integration in Singapore school. Computers and Education, 41, 49-63.
  • Ma, W. W. K., Andersson, R. and Streith, K. O. (2005). Examining user acceptance of computer technology: An empirical study of student teachers. Journal of Computer Assisted Learning, 21(6), 387–395.
  • McCoy, S., Galletta, D. F., & King, W. R. (2007). Applying TAM across cultures: the need for caution. European Journal of Information Systems, 16(1), 81-90.
  • Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
  • Ngai, E. W. T., Poon, J. K. L. ve Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48(2), 250–267.
  • Ong, C. S., & Lai, J. Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816-829.
  • Orlando, J. (2009). Understanding changes in teachers' ICT practices: a longitudinal perspective. Technology, Pedagogy and Education, 18(1), 33 – 44.
  • Pamuk, S., & Peker, D. (2009). Turkish pre-service science and mathematics teachers’ computer related self-efficacies, attitudes, and the relationship between these variables. Computers & Education, 53(2), 454-461.
  • Pan, S., & Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in human behavior, 26(5), 1111-1119.
  • Rogers, E. M. (1995). Diffusion of innovations (4th ed.). Free Press, New York.
  • Rosen, L. D. ve Weil, M. M. (1995). Computer availability, computer experience and technophobia among public school teachers. Computers in Human Behavior, 11(1), 9-31.
  • Spence, I., DeYoung, C. G., & Feng, J. (2009). The technology profile inventory: Construction, validation, and application. Computers in Human Behavior, 25(2), 458-465.
  • Teo, T. & Ursavaş Ö. F. (2012) Technology Acceptance of Pre-Service Teachers in Turkey: Cross-Cultural Model Validation Study. International Journal of Instructional Media, 39(3), 193-201.
  • Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312.
  • Teo, T. (2010). Examining the influence of subjective norm and facilitating conditions on the intention to use technology among pre-service teachers: a structural equation modeling of an extended technology acceptance model. The Asia-Pacific Education Researcher, 11(2), 253-262.
  • Teo, T. (2014). Unpacking teachers' acceptance of technology: Tests of measurement invariance and latent mean differences. Computers & Education, 75, 127-135.
  • Teo, T. ve van Schaik, P. (2009). Understanding Technology Acceptance in Pre-Service Teachers: A Structural-Equation Modeling Approach. The Asia-Pasific Education Researcher,18(1),47-66.
  • Teo, T., Lee, C. B. ve Chai, C.S. (2008).Understanding pre-service teachers' computer attitudes: applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2), 128-142.
  • Teo, T., Su-Luan, W. ve Sing, C. C. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: an application of the Technology Acceptance Model (TAM). Educational Technology & Society, 11(4), 265-280.
  • Teo, T., Ursavaş, Ö. F. ve Bahçekapılı, E. (2012). An assessment of pre-service teachers’ technology acceptance in Turkey: A structural equation modeling approach. The Asia-Pacific Education Researcher, 21(1), 191-202.
  • Teo, T., Ursavaş, Ö. F., & Bahçekapılı, E. (2011) Efficiency of the Technology Acceptance Model (TAM) to explain pre-service teachers’ intention to use technology: A Turkish study. Campus-Wide Information Systems, 28(2), 93-101.
  • Terzis, V. ve Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032–1044.
  • Thompson, R. L., Higgins, C. A. ve Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.
  • Torkzadeh, G., & Van Dyke, T. P. (2002). Effects of training on Internet self-efficacy and computer user attitudes. Computers in Human Behavior, 18(5), 479-494.
  • Ursavaş Ö. F. (2013) Reconsidering the role of attitude in the TAM: An answer to Teo (2009) and Nistor and Heymann (2010), and Lopez-Bonilla and Lopez-Bonilla (2011). British Journal of Educational Technology, 44(1), E22-E25.
  • Ursavaş, Ö. F. (2014). Öğretmenlerin bilişim teknolojilerini kullanmaya yönelik davranışlarının modellenmesi. Yayınlanmamış Doktora Tezi. Gazi Üniversitesi, Eğitim Bilimleri Enstitüsü, Ankara.
  • Ursavaş, Ö. F., Şahin, S., & Mcilroy, D. (2014a). Türkiye’deki Öğretmen Adaylarının BİT Kullanımına Yönelik Davranışsal Niyetlerinin Belirlenmesinde Branşlarının Rolü. Education and Science, 39,136-153.
  • Ursavaş, Ö. F., Şahin, S., & Mcilroy, D. (2014b). Technology Acceptance Measure for Teachers: T-TAM. Journal of Theory and Practice in Education, 10(4), 885-917.
  • van Braak, J. (2001). Factors influencing the use of computer mediated communication by teachers in secondary schools. Computers and Education, 36(1), 41-57.
  • Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS quarterly, 24(1), 115-139.
  • 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.
  • Yuen, H. K. ve Ma, W. K. (2002). Gender differences in teacher computer acceptance. Journal of Technology and Teacher Education, 10(3), 365- 382.
  • Yukun Bao, Tao Xiong, Zhongyi Hu, Mboni Kibelloh (2013). Exploring Gender Differences on General and Specific Computer Self-efficacy in Mobile Learning Adoption. Journal of Educational Computing Research. 49(1).111-132.

An examination of gender effect on pre-service teachers’ behavioural intentions to use ICT / Öğretmen adaylarının BİT kullanımına yönelik davranışsal niyetleri üzerindeki cinsiyet etkisinin incelenmesi

Year 2015, Volume: 11 Issue: 1, 68 - 88, 16.01.2015

Abstract

Many studies were conducted to find an answer to a question of how individuals' beliefs and attitudes affect their use of information communication technologies (ICT). Based onthese studies, theories were developed and used in different disciplines in order to model individuals' behavioural intention to use   technology. Among these, The Technology Acceptance Model (TAM) has been used to establish a theoretical-base to assess user acceptance considering different culture and gender samples. The purpose of this study was to investigate a model that predicts the level of technology acceptance by pre-service teachers at a teacher training institute. Data was collected from 337 (female-205, male-132) pre-service elementary teachers by employing TAM to reveal their purposes of technology use. The resulting model was found to have a good fit. Six variables that were expected to affect pre-service teachers' acceptance of technology (computer self-efficacy, facilitating conditions, technological complexity, attitude towards technology use, perceived ease of use, perceived usefulness) explained the purpose of technology use by accounting the variances of 35% among male and 44 % among female pre-service teachers. It was also found that perceived usefulness and computer self-efficacy were the most influential variables in explaining behavioural intention to use technology for both genders.

References

  • Ajzen, I. ve Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior, Prentice-Hall. Upper Saddle River, NJ.
  • Akkoyunlu, B. ve Orhan, F. (2003). Relationship between computer usage self-efficacy and their demographic characteristics of teacher candidates. The Turkish Online Journal of Educational Technology, 2(3), 86-93.
  • Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory, NJ: Prentice Hall, Englewood Cliffs.
  • Bao, Y., Xiong, T., Hu, Z., & Kibelloh, M. (2013). Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption. Journal of Educational Computing Research, 49(1), 111-132.
  • Bebetsos, E. ve Antonıou, P. (2009). Gender Differences On Attitudes, Computer Use And Physical Activity Among Greek University Students. The Turkish Online Journal of Educational Technology, 8, 2, 6.
  • Bunz, U., Curry, C., & Voon, W. (2007). Perceived versus actual computer-email-web fluency. Computers in Human Behavior, 23(5), 2321-2344.
  • Cheon, J., Lee, S., Crooks, S. M. ve Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behaviour. Computers and Education, 59(3), 1054-1064.
  • Cheung, W. ve Huang, W. (2005). Proposing a framework to assess internet usage in university education: an empirical investigation from a student’s perspective. British Journal of Educational Technology, 36(2), 237–253.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
  • Compeau, D.R. ve Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Demetriadis, S., Barbas, A., Molohides, A., Palaigeorgiou, G., Psillos, D., Vlahavas, I.,Tsoukalas, I. ve Pombortsis, A. (2003). Culture in negotiation: Teachers’ acceptance/resistance attitudes considering the infusion of technology into schools. Computer & Education, 41(1), 19–37.
  • Dishaw M.T. ve Strong D.M.(1999).Extending the Technology Acceptance Model With Task-Technology Fit Constructs. Information & Management, 36(1), 9-21.
  • Escobar-Rodriguez, T. ve Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58(4), 1085–1093.
  • Fishbein, M. ve Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
  • Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: a study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 8.
  • Groves, M. M. ve Zemel, P. C. (2000). Instructional technology adoption in higher education: An action research case study. International Journal of Instructional Media, 27(1), 57–65.
  • Gülbahar, Y. (2008). Improving the technology integration skills of prospective teachers through practice: A case study. Turkish Online Journal of Educational Technology, 7(4), 1-11.
  • Güldü, Ö. ve Ersoy-Kart, M.(2009). Toplumsal cinsiyet rolleri ve siyasal tutumlar:Sosyal psikolojik bir değerlendirme. Ankara Üniversitesi SBF Dergisi, 64(3), 97-116.
  • Kiraz, E. ve Ozdemir, D. (2006). The Relationship between Educational Ideologies and Technology Acceptance in Pre-service Teachers. Educational Technology & Society, 9(2), 152-165.
  • Knight, C. M., Knight, B. A. ve Teghe, D. (2006). Releasing the pedagogical power of information and communication technology for learners: A case study, International Journal of Education and Development using Information and Communication Technology, 2(2), 27-34.
  • Legris, P., Ingham, J. ve Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204.
  • Lim, C. P. ve Hang, D. (2003). An activity theory approach to research of ICT integration in Singapore school. Computers and Education, 41, 49-63.
  • Ma, W. W. K., Andersson, R. and Streith, K. O. (2005). Examining user acceptance of computer technology: An empirical study of student teachers. Journal of Computer Assisted Learning, 21(6), 387–395.
  • McCoy, S., Galletta, D. F., & King, W. R. (2007). Applying TAM across cultures: the need for caution. European Journal of Information Systems, 16(1), 81-90.
  • Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
  • Ngai, E. W. T., Poon, J. K. L. ve Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48(2), 250–267.
  • Ong, C. S., & Lai, J. Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816-829.
  • Orlando, J. (2009). Understanding changes in teachers' ICT practices: a longitudinal perspective. Technology, Pedagogy and Education, 18(1), 33 – 44.
  • Pamuk, S., & Peker, D. (2009). Turkish pre-service science and mathematics teachers’ computer related self-efficacies, attitudes, and the relationship between these variables. Computers & Education, 53(2), 454-461.
  • Pan, S., & Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in human behavior, 26(5), 1111-1119.
  • Rogers, E. M. (1995). Diffusion of innovations (4th ed.). Free Press, New York.
  • Rosen, L. D. ve Weil, M. M. (1995). Computer availability, computer experience and technophobia among public school teachers. Computers in Human Behavior, 11(1), 9-31.
  • Spence, I., DeYoung, C. G., & Feng, J. (2009). The technology profile inventory: Construction, validation, and application. Computers in Human Behavior, 25(2), 458-465.
  • Teo, T. & Ursavaş Ö. F. (2012) Technology Acceptance of Pre-Service Teachers in Turkey: Cross-Cultural Model Validation Study. International Journal of Instructional Media, 39(3), 193-201.
  • Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312.
  • Teo, T. (2010). Examining the influence of subjective norm and facilitating conditions on the intention to use technology among pre-service teachers: a structural equation modeling of an extended technology acceptance model. The Asia-Pacific Education Researcher, 11(2), 253-262.
  • Teo, T. (2014). Unpacking teachers' acceptance of technology: Tests of measurement invariance and latent mean differences. Computers & Education, 75, 127-135.
  • Teo, T. ve van Schaik, P. (2009). Understanding Technology Acceptance in Pre-Service Teachers: A Structural-Equation Modeling Approach. The Asia-Pasific Education Researcher,18(1),47-66.
  • Teo, T., Lee, C. B. ve Chai, C.S. (2008).Understanding pre-service teachers' computer attitudes: applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2), 128-142.
  • Teo, T., Su-Luan, W. ve Sing, C. C. (2008). A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: an application of the Technology Acceptance Model (TAM). Educational Technology & Society, 11(4), 265-280.
  • Teo, T., Ursavaş, Ö. F. ve Bahçekapılı, E. (2012). An assessment of pre-service teachers’ technology acceptance in Turkey: A structural equation modeling approach. The Asia-Pacific Education Researcher, 21(1), 191-202.
  • Teo, T., Ursavaş, Ö. F., & Bahçekapılı, E. (2011) Efficiency of the Technology Acceptance Model (TAM) to explain pre-service teachers’ intention to use technology: A Turkish study. Campus-Wide Information Systems, 28(2), 93-101.
  • Terzis, V. ve Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032–1044.
  • Thompson, R. L., Higgins, C. A. ve Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.
  • Torkzadeh, G., & Van Dyke, T. P. (2002). Effects of training on Internet self-efficacy and computer user attitudes. Computers in Human Behavior, 18(5), 479-494.
  • Ursavaş Ö. F. (2013) Reconsidering the role of attitude in the TAM: An answer to Teo (2009) and Nistor and Heymann (2010), and Lopez-Bonilla and Lopez-Bonilla (2011). British Journal of Educational Technology, 44(1), E22-E25.
  • Ursavaş, Ö. F. (2014). Öğretmenlerin bilişim teknolojilerini kullanmaya yönelik davranışlarının modellenmesi. Yayınlanmamış Doktora Tezi. Gazi Üniversitesi, Eğitim Bilimleri Enstitüsü, Ankara.
  • Ursavaş, Ö. F., Şahin, S., & Mcilroy, D. (2014a). Türkiye’deki Öğretmen Adaylarının BİT Kullanımına Yönelik Davranışsal Niyetlerinin Belirlenmesinde Branşlarının Rolü. Education and Science, 39,136-153.
  • Ursavaş, Ö. F., Şahin, S., & Mcilroy, D. (2014b). Technology Acceptance Measure for Teachers: T-TAM. Journal of Theory and Practice in Education, 10(4), 885-917.
  • van Braak, J. (2001). Factors influencing the use of computer mediated communication by teachers in secondary schools. Computers and Education, 36(1), 41-57.
  • Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS quarterly, 24(1), 115-139.
  • 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.
  • Yuen, H. K. ve Ma, W. K. (2002). Gender differences in teacher computer acceptance. Journal of Technology and Teacher Education, 10(3), 365- 382.
  • Yukun Bao, Tao Xiong, Zhongyi Hu, Mboni Kibelloh (2013). Exploring Gender Differences on General and Specific Computer Self-efficacy in Mobile Learning Adoption. Journal of Educational Computing Research. 49(1).111-132.
There are 55 citations in total.

Details

Primary Language Turkish
Journal Section Makaleler
Authors

Ömer Faruk Ursavaş

Publication Date January 16, 2015
Submission Date January 16, 2015
Published in Issue Year 2015 Volume: 11 Issue: 1

Cite

APA Ursavaş, Ö. F. (2015). An examination of gender effect on pre-service teachers’ behavioural intentions to use ICT / Öğretmen adaylarının BİT kullanımına yönelik davranışsal niyetleri üzerindeki cinsiyet etkisinin incelenmesi. Eğitimde Kuram Ve Uygulama, 11(1), 68-88. https://doi.org/10.17244/eku.39571