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Year 2020, Volume 7, Issue 2, 1 - 14, 30.12.2020
https://doi.org/10.33200/ijcer.736876

Abstract

References

  • Ajjan, H., & Hartshorne, R. (2008). Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. The internet and higher education, 11(2), 71-80.
  • Altanopoulou, P., & Tselios, N. (2017). Assessing acceptance toward wiki technology in the context of higher education. International Review of Research in Open and Distance Learning, 18(6), 127–149.
  • Alkhayat, L., Ernest, J., & LaChenaye, J. (2020). Exploring Kuwaiti preservice early childhood teachers’ beliefs about using web 2.0 technologies. Early Childhood Education Journal, 1-11.
  • Arslan, K. (2019). Attitudes and perceptions of pedagogical formation physical education students about web 2.0 tools and factors for successful adaptation of these tools. European Journal of Education Studies, 6(6), 101-114.
  • Baas, P. (2010). Task-technology fit in the workplace (Affecting employee satisfaction and productivity). Rotterdam- Netherlands: (MSc Business Administration), Erasmus University.
  • Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214.
  • Bhattacherjee, A. (2001b). Understanding information systems continuance. An expectation–confirmation model. MIS Quarterly, 25(3), 351–370.
  • Baydaş, Ö., & Yilmaz, R. M. (2017). A Model for pre-service teachers’ intention to use interactive white boards in their future lessons. Journal of Higher Education and Science, 7(1), 59-66.
  • Butler, J. (2012). Grappling with change: Web 2.0 and teacher education. In D. Polly, C. Mims, & K. A. Persichitte (Eds.), Developing technology-rich teacher education programs: Key issues (pp. 135–150). Hershey, PA: IGI Global.
  • Cakir, R., Yukselturk, E., & Top, E. (2015). Pre-service and in-service teachers’ perceptions about using Web 2.0 in education. Participatory Educational Research, 2(2), 70-83.
  • Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web acceptance model (WAM): Moderating effects of user experience. Information & management, 44(4), 384-396.
  • Chen, J., Wang, M., Kirschner, P. A., & Tsai, C. C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88(6), 799-843.
  • Cheon, J., Song, J., Jones, D. R., & Nam, K. (2010). Influencing preservice teachers’ intention to adopt web 2.0 services. Journal of Digital Learning in Teacher Education, 27(2), 53–64.
  • 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.
  • Cilliers, L. (2017). Wiki acceptance by university students to improve collaboration in higher education. Innovations in Education and Teaching International, 54(5), 485–493.
  • Conole, G. (2010). Facilitating new forms of discourse for learning and teaching: harnessing the power of Web 2.0 practices. Open Learning: The Journal of Open, Distance and e-Learning, 25(2), 141-151.
  • Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). Massachusetts Institute of Technology.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.
  • Dillenbourg, P. (1999). Introduction: what do you mean by ‘‘collaborative learning’’? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (Advances in learning and instruction series) ( pp. 1 – 19). Amsterdam: Pergamon.
  • Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of instruction. In David H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 693-719). New York: Macmillan.
  • Esteban-Millat, I., Martínez-López, F. J., Pujol-Jover, M., Gázquez-Abad, J. C., & Alegret, A. (2018). An extension of the technology acceptance model for online learning environments. Interactive Learning Environments, 26(7), 895–910.
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th Edition). New York: McGraw-Hill.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
  • Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593.
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th Ed.). nj: Prentice-Hall.
  • Hew, K. F., & Cheung, W. S. (2013). Use of Web 2.0 technologies in K-12 and higher education: The search for evidence-based practice. Educational research review, 9, 47-64.
  • Huang, W. H. D., Hood, D. W., & Yoo, S. J. (2013). Gender divide and acceptance of collaborative Web 2.0 applications for learning in higher education. Internet and Higher Education, 16(1), 57–65.
  • Huang, Y. M. (2017). Exploring the intention to use cloud services in collaboration contexts among Taiwan’s private vocational students. Information Development, 33(1), 29–42.
  • Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & management, 45(1), 65-74.
  • Ifinedo, P. (2017). Examining students’ intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Computers in Human Behavior, 72, 189–199.
  • International Society for Technology in Education (2017). ISTE standards for educators. Retrieved 4th March 2020 from https://www.iste.org/standards/for-educators#startstandards
  • Jimoyiannis, A., Tsiotakis, P., Roussinos, D., & Siorenta, A. (2013). Preparing teachers to integrate web 2.0 in school practice: Toward a framework for pedagogy 2.0. Australasian Journal of Educational Technology, 29(2), 248–267.
  • Johnson, D. W., & Johnson, R. T. (1996). Cooperation and the use of technology. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 1017-1044). New York: Macmillan.
  • King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & management, 43(6), 740-755.
  • Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in human behavior, 19(3), 335-353.
  • Kul, Ü. & Çelik, S. (2018). Investigating changes in mathematics teachers’ intentions regarding web 2.0 technology integration. Acta Didactica Napocensia, 11(2), 89-104
  • Matthews, R. S., Cooper, J. L., Davidson, N., & Hawkes, P. (1995). Building bridges between cooperative and collaborative learning. Change, 27, 34–40.
  • Mcloughlin, C., & Lee, M. J. W. (2007). Social software and participatory learning : Pedagogical choices with technology affordances in the Web 2.0 era Introduction : Social trends and challenges. Paper presented at the Ascilite Singapore 2007. Retrieved from https://ascilite.org/conferences/singapore07/procs/mcloughlin.pdf
  • Moreno, V., Cavazotte, F., & Alves, I. (2017). Explaining university students’ effective use of e‐learning platforms. British Journal of Educational Technology, 48(4), 995-1009. OECD (2019). OECD Skills Outlook 2019: Thriving in a Digital World. OECD Publishing: Paris.
  • Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Educational Technology & Society, 12(3), 150–162.
  • Pence, H. E. (2007). Preparing for the real web generation. Journal of Educational Technology Systems, 35(3), 347−356.
  • Prensky, M. (2001). Digital natives, digital immigrants part 1. On the Horizon, 9(5), 1–6.
  • Redecker, C. (2009). Review of learning 2.0 practices: study on the impact of web 2.0 innovations of education and training in Europe. European Commission. Retrieved from https://publications.jrc.ec.europa.eu/repository/bitstream/JRC49108/jrc49108.pdf
  • Resta, P., & Laferrière, T. (2007). Technology in support of collaborative learning. Educational Psychology Review, 19(1), 65-83.
  • Sadaf, A., Newby, T. J., & Ertmer, P. A. (2012). Exploring factors that predict preservice teachers’ intentions to use web 2.0 technologies using decomposed theory of planned behavior. Journal of Research on Technology in Education, 45(2), 171–196.
  • Sadaf, A., Newby, T. J., & Ertmer, P. A. (2016). An investigation of the factors that influence preservice teachers' intentions and integration of web 2.0 tools. Educational Technology Research and Development, 64(1), 37–64.
  • Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306-328.
  • Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312.
  • 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.
  • Teo, T., Ursavaş, Ö. F., & Bahçekapili, E. (2012). An assessment of pre-service teachers' technology acceptance in Turkey: A structural equation modeling approach. Asia-Pacific Education Researcher, 21(1), 191-202.
  • Teo, T., Sang, G., Mei, B., & Hoi, C. K. W. (2019). Investigating pre-service teachers’ acceptance of Web 2.0 technologies in their future teaching: a Chinese perspective. Interactive Learning Environments, 27(4), 530–546.
  • UNESCO (2008). ICT competency standards for teachers: policy framework. Retrieved 4th March 2020 from https://unesdoc.unesco.org/ark:/48223/pf0000156210
  • Ursavaş, Ö. F., Şahin, S., & Mcilroy, D. (2014). The role of discipline in determining Turkish pre-service teachers' behavioral intentions to use ICT Education and Science, 39(175), 136 – 153.
  • Usoro, A., Echeng, R., & Majewski, G. (2014). A Model of Acceptance of Web 2.0 in learning in higher education: a case study of two cultures. E-Learning and Digital Media, 11(6), 644-653.
  • Valtonen, T., Kukkonen, J., Kontkanen, S., Sormunen, K., Dillon, P., & Sointu, E. (2015). The impact of authentic learning experiences with ICT on pre-service teachers’ intentions to use ICT for teaching and learning. Computers and Education, 81, 49–58.
  • Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342–365.
  • Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204.
  • Wang, C. S., & Huang, Y. M. (2016). Acceptance of cloud services in face-to-face computer-supported collaborative learning: a comparison between single-user mode and multi-user mode. Innovations in Education and Teaching International, 53(6), 637–648.
  • Wong, K. T., Russo, S., & McDowall, J. (2013). Understanding early childhood student teachers’ acceptance and use of interactive whiteboard. Campus-Wide Information Systems, 30(1), 4-16.
  • Yadegaridehkordi, E., Shuib, L., Nilashi, M., & Asadi, S. (2019). Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities. Education and Information Technologies, 24(1), 79–102.
  • Yilmaz, R. M., & Baydas, O. (2016). Pre-service teachers’ behavioral intention to make educational animated movies and their experiences. Computers in Human Behavior, 63, 41–49.
  • Yueh, H. P., Huang, J. Y., & Chang, C. (2015). Exploring factors affecting students’ continued Wiki use for individual and collaborative learning: An extended UTAUT perspective. Australasian Journal of Educational Technology, 31(1), 16–31.

Exploring the Effect of Collaborative Learning on Teacher Candidates’ Intentions to Use Web 2.0 Technologies

Year 2020, Volume 7, Issue 2, 1 - 14, 30.12.2020
https://doi.org/10.33200/ijcer.736876

Abstract

The purpose of this study was to examine teacher candidates’ pre and post intentions to use web 2.0 technologies for teaching before and after a collaborative learning process. An extended TAM was used in the current study. This study was designed as a one-group pretest-posttest design with 56 teacher candidates. In the experiment process, the instructor taught the design principles and how to use and design instructional materials with selected web 2.0 technologies. Then the teacher candidates worked in small groups to design the instructional materials with web 2.0 technologies. The data collection tool was administered before and after the experiment. Data were analyzed through partial least squares structural equation modeling. The results indicated that 4 of the 7 hypotheses were supported in the pre-acceptance model while all hypotheses were accepted in the post-acceptance model. The proposed model can be used as an appropriate framework for examining factors influencing teacher candidates’ intentions to use web 2.0 technologies for teaching.

References

  • Ajjan, H., & Hartshorne, R. (2008). Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. The internet and higher education, 11(2), 71-80.
  • Altanopoulou, P., & Tselios, N. (2017). Assessing acceptance toward wiki technology in the context of higher education. International Review of Research in Open and Distance Learning, 18(6), 127–149.
  • Alkhayat, L., Ernest, J., & LaChenaye, J. (2020). Exploring Kuwaiti preservice early childhood teachers’ beliefs about using web 2.0 technologies. Early Childhood Education Journal, 1-11.
  • Arslan, K. (2019). Attitudes and perceptions of pedagogical formation physical education students about web 2.0 tools and factors for successful adaptation of these tools. European Journal of Education Studies, 6(6), 101-114.
  • Baas, P. (2010). Task-technology fit in the workplace (Affecting employee satisfaction and productivity). Rotterdam- Netherlands: (MSc Business Administration), Erasmus University.
  • Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214.
  • Bhattacherjee, A. (2001b). Understanding information systems continuance. An expectation–confirmation model. MIS Quarterly, 25(3), 351–370.
  • Baydaş, Ö., & Yilmaz, R. M. (2017). A Model for pre-service teachers’ intention to use interactive white boards in their future lessons. Journal of Higher Education and Science, 7(1), 59-66.
  • Butler, J. (2012). Grappling with change: Web 2.0 and teacher education. In D. Polly, C. Mims, & K. A. Persichitte (Eds.), Developing technology-rich teacher education programs: Key issues (pp. 135–150). Hershey, PA: IGI Global.
  • Cakir, R., Yukselturk, E., & Top, E. (2015). Pre-service and in-service teachers’ perceptions about using Web 2.0 in education. Participatory Educational Research, 2(2), 70-83.
  • Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web acceptance model (WAM): Moderating effects of user experience. Information & management, 44(4), 384-396.
  • Chen, J., Wang, M., Kirschner, P. A., & Tsai, C. C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88(6), 799-843.
  • Cheon, J., Song, J., Jones, D. R., & Nam, K. (2010). Influencing preservice teachers’ intention to adopt web 2.0 services. Journal of Digital Learning in Teacher Education, 27(2), 53–64.
  • 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.
  • Cilliers, L. (2017). Wiki acceptance by university students to improve collaboration in higher education. Innovations in Education and Teaching International, 54(5), 485–493.
  • Conole, G. (2010). Facilitating new forms of discourse for learning and teaching: harnessing the power of Web 2.0 practices. Open Learning: The Journal of Open, Distance and e-Learning, 25(2), 141-151.
  • Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). Massachusetts Institute of Technology.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.
  • Dillenbourg, P. (1999). Introduction: what do you mean by ‘‘collaborative learning’’? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (Advances in learning and instruction series) ( pp. 1 – 19). Amsterdam: Pergamon.
  • Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of instruction. In David H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 693-719). New York: Macmillan.
  • Esteban-Millat, I., Martínez-López, F. J., Pujol-Jover, M., Gázquez-Abad, J. C., & Alegret, A. (2018). An extension of the technology acceptance model for online learning environments. Interactive Learning Environments, 26(7), 895–910.
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th Edition). New York: McGraw-Hill.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
  • Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593.
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th Ed.). nj: Prentice-Hall.
  • Hew, K. F., & Cheung, W. S. (2013). Use of Web 2.0 technologies in K-12 and higher education: The search for evidence-based practice. Educational research review, 9, 47-64.
  • Huang, W. H. D., Hood, D. W., & Yoo, S. J. (2013). Gender divide and acceptance of collaborative Web 2.0 applications for learning in higher education. Internet and Higher Education, 16(1), 57–65.
  • Huang, Y. M. (2017). Exploring the intention to use cloud services in collaboration contexts among Taiwan’s private vocational students. Information Development, 33(1), 29–42.
  • Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & management, 45(1), 65-74.
  • Ifinedo, P. (2017). Examining students’ intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Computers in Human Behavior, 72, 189–199.
  • International Society for Technology in Education (2017). ISTE standards for educators. Retrieved 4th March 2020 from https://www.iste.org/standards/for-educators#startstandards
  • Jimoyiannis, A., Tsiotakis, P., Roussinos, D., & Siorenta, A. (2013). Preparing teachers to integrate web 2.0 in school practice: Toward a framework for pedagogy 2.0. Australasian Journal of Educational Technology, 29(2), 248–267.
  • Johnson, D. W., & Johnson, R. T. (1996). Cooperation and the use of technology. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 1017-1044). New York: Macmillan.
  • King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & management, 43(6), 740-755.
  • Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in human behavior, 19(3), 335-353.
  • Kul, Ü. & Çelik, S. (2018). Investigating changes in mathematics teachers’ intentions regarding web 2.0 technology integration. Acta Didactica Napocensia, 11(2), 89-104
  • Matthews, R. S., Cooper, J. L., Davidson, N., & Hawkes, P. (1995). Building bridges between cooperative and collaborative learning. Change, 27, 34–40.
  • Mcloughlin, C., & Lee, M. J. W. (2007). Social software and participatory learning : Pedagogical choices with technology affordances in the Web 2.0 era Introduction : Social trends and challenges. Paper presented at the Ascilite Singapore 2007. Retrieved from https://ascilite.org/conferences/singapore07/procs/mcloughlin.pdf
  • Moreno, V., Cavazotte, F., & Alves, I. (2017). Explaining university students’ effective use of e‐learning platforms. British Journal of Educational Technology, 48(4), 995-1009. OECD (2019). OECD Skills Outlook 2019: Thriving in a Digital World. OECD Publishing: Paris.
  • Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Educational Technology & Society, 12(3), 150–162.
  • Pence, H. E. (2007). Preparing for the real web generation. Journal of Educational Technology Systems, 35(3), 347−356.
  • Prensky, M. (2001). Digital natives, digital immigrants part 1. On the Horizon, 9(5), 1–6.
  • Redecker, C. (2009). Review of learning 2.0 practices: study on the impact of web 2.0 innovations of education and training in Europe. European Commission. Retrieved from https://publications.jrc.ec.europa.eu/repository/bitstream/JRC49108/jrc49108.pdf
  • Resta, P., & Laferrière, T. (2007). Technology in support of collaborative learning. Educational Psychology Review, 19(1), 65-83.
  • Sadaf, A., Newby, T. J., & Ertmer, P. A. (2012). Exploring factors that predict preservice teachers’ intentions to use web 2.0 technologies using decomposed theory of planned behavior. Journal of Research on Technology in Education, 45(2), 171–196.
  • Sadaf, A., Newby, T. J., & Ertmer, P. A. (2016). An investigation of the factors that influence preservice teachers' intentions and integration of web 2.0 tools. Educational Technology Research and Development, 64(1), 37–64.
  • Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306-328.
  • Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312.
  • 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.
  • Teo, T., Ursavaş, Ö. F., & Bahçekapili, E. (2012). An assessment of pre-service teachers' technology acceptance in Turkey: A structural equation modeling approach. Asia-Pacific Education Researcher, 21(1), 191-202.
  • Teo, T., Sang, G., Mei, B., & Hoi, C. K. W. (2019). Investigating pre-service teachers’ acceptance of Web 2.0 technologies in their future teaching: a Chinese perspective. Interactive Learning Environments, 27(4), 530–546.
  • UNESCO (2008). ICT competency standards for teachers: policy framework. Retrieved 4th March 2020 from https://unesdoc.unesco.org/ark:/48223/pf0000156210
  • Ursavaş, Ö. F., Şahin, S., & Mcilroy, D. (2014). The role of discipline in determining Turkish pre-service teachers' behavioral intentions to use ICT Education and Science, 39(175), 136 – 153.
  • Usoro, A., Echeng, R., & Majewski, G. (2014). A Model of Acceptance of Web 2.0 in learning in higher education: a case study of two cultures. E-Learning and Digital Media, 11(6), 644-653.
  • Valtonen, T., Kukkonen, J., Kontkanen, S., Sormunen, K., Dillon, P., & Sointu, E. (2015). The impact of authentic learning experiences with ICT on pre-service teachers’ intentions to use ICT for teaching and learning. Computers and Education, 81, 49–58.
  • Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342–365.
  • Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204.
  • Wang, C. S., & Huang, Y. M. (2016). Acceptance of cloud services in face-to-face computer-supported collaborative learning: a comparison between single-user mode and multi-user mode. Innovations in Education and Teaching International, 53(6), 637–648.
  • Wong, K. T., Russo, S., & McDowall, J. (2013). Understanding early childhood student teachers’ acceptance and use of interactive whiteboard. Campus-Wide Information Systems, 30(1), 4-16.
  • Yadegaridehkordi, E., Shuib, L., Nilashi, M., & Asadi, S. (2019). Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities. Education and Information Technologies, 24(1), 79–102.
  • Yilmaz, R. M., & Baydas, O. (2016). Pre-service teachers’ behavioral intention to make educational animated movies and their experiences. Computers in Human Behavior, 63, 41–49.
  • Yueh, H. P., Huang, J. Y., & Chang, C. (2015). Exploring factors affecting students’ continued Wiki use for individual and collaborative learning: An extended UTAUT perspective. Australasian Journal of Educational Technology, 31(1), 16–31.

Details

Primary Language English
Subjects Social
Journal Section Articles
Authors

Erhan ÜNAL (Primary Author)
AFYON KOCATEPE UNIVERSITY, FACULTY OF EDUCATION
0000-0002-5349-4193
Türkiye

Publication Date December 30, 2020
Published in Issue Year 2020, Volume 7, Issue 2

Cite

APA Ünal, E. (2020). Exploring the Effect of Collaborative Learning on Teacher Candidates’ Intentions to Use Web 2.0 Technologies . International Journal of Contemporary Educational Research , 7 (2) , 1-14 . DOI: 10.33200/ijcer.736876

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