A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction

Mehmet Barıs Horzum; Ozlem Canan Gungoren

EN

A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction

Abstract

One of the applications applied most nowadays is web based instruction (WBI). Although there are many studies on WBI, no study which researched the relations between beliefs for WBI, WBI tools acceptance levels and web pedagogical content knowledge (WPCK) of science and technology pre-service teachers was found among these studies. The aim of this study is to examine this relation. In accordance with this aim, the study group of the study consisted of 363 pre-service teachers. The data collected from pre-service teachers under the research were collected with scales of belief, tools acceptance and WPCK towards WBI. 3 scales were used for the data collection in the research. The data were analyzed with structural equation modeling in the research. As a result of the research, behavioral and contextual beliefs in WBI beliefs were medium level. Perceived usefulness, ease of use, perceived attitude and intention positively affect WBI tools acceptance levels of pre-service teachers. When the relation between beliefs, tools acceptance levels and web pedagogical content knowledge of science and technology education pre-service teachers towards WBI is analyzed, it is seen that beliefs towards WBI affect acceptance levels of WBI tools and WBI tools acceptance levels affect web pedagogical content knowledge.

Keywords

Science And Technology Preservice Teacher, Web Based Instruction Belief, Web Based Instruction Tools Acceptence, Web Pedagogical Content Knowledge.

References

Adams, W. K., Alhadlaq, H., Malley, C. V., Perkins, K. K., Olson, J., Alshaya, F., Alabdulkareem, S. & Wieman, C. E. (2012). Making on-line science course materials easily translatable and accessible worldwide: challenges and solutions. Journal of
Science Education and Technology, 21(1), 1–10. Allen, I. E., & Seaman, J. (2006). Making the grade online education in the United
States, 2006. The Sloan Consortium (SLOAN-C). Retrieved March 17, 2012, from www.sloan-c.org.
Allen, I. E., & Seaman, J. (2010). Learning on Demand Online Education in the United States, 2009. The Sloan Consortium (SLOAN-C). Retrieved March 17, 2012, fromhttp://sloanconsortium.org/publications/survey/pdf/learningondemand.pdf.
Annetta, L. A., & Minogue, J. (2004). The effect teaching experience has on perceived effectiveness of ınteractive television as a distance education model for elementary school science teacher’s professional development: another digital divide?. Journal of Science Education and Technology, 13(4), 485-494.
Arbaugh, J.B. (2005). Is there an optimal design for on-line MBA courses? Academy of Management Learning and Education, 4(2), 135-149.
Armitage, C. J. & Conner, M. (2001). Effcacy of the Theory of Planned Behaviour:
A meta-analytic review. British Journal of Social Psychology, 40, 471–499. Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: predicting satisfaction with online training. Journal of Computer Assisted Learning, , 260–270.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control and the theory of planned behavior. Journal of Applied Social Psycnology, 32, 1–20.

Ajzen, I. (2011). The theory of planned behavior: Reactions and reflections.
Psychology& Health, 26(9), 1113-1127.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254.
Boitshwarelo, B. (2009). Exploring blended learning for science teacher professional development in an African context. International Review of Research in Open and Distance Learning, 10(4). Retrieved March 17, 2012, from http://www.irrodl.org/index.php/irrodl/article/view/687/1339.
Boone, W.J. (1996). Advanced distance education technology and hands-on science.
Journal of Science Education and Technology, 5(1), 33-46. Campbell, P. B., & Storo, J. (1996). Reducing the distance: Equity issues in distance learning in public education. Journal of Science Education and Technology, 5(4), 295.
Chang, Y. H., Chang, C. Y., & Tseng, Y. H. (2010). Trends of science education research: an automatic content analysis. Journal of Science Education and Technology, 19, 315-331.
Crippen, K. J. (2003). Rethinking course assessment: Creating accountability with web-based tools. Journal of Science Education and Technology, 12(4), 431-438.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of
Man-Machine Studies, 38(3), 475-487. 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), 1003.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York: Psychology Press (Taylor & Francis).
Fives, H., & Buehl, M. M. (2008). What do teachers believe? Developing a framework for examining beliefs about teachers' knowledge and ability.
Contemporary Educational Psychology, 33(2), 134-176. Gong, M., Xu, Y., & Yu, Y. (2004). An enhanced technology acceptance model for web-based learning. Journal of Information Systems Education, 15(4), 365-374.
Haney, J.J., Czerniak, M.C. & Lumpe, A.T. (1998). Teacher beliefs and intentions regarding the implementation of science education reform strands. Journal of
Research in Science Teaching, 33(9), 971–993. Harris, J., Mishra, P., & Koehler, M. J. (2009). Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed. Journal of Research on Technology in Education- JRTE, 41(4), 393-416.
Hermans, C. M., Haytko, D. L., & Mott-Stenerson, B. (2009). Student satisfaction in web-enhanced learning environments. Journal of Instructional Pedagogies, 1, 1-19.
Horton, W. (2000). Designing web-based training: How to teach anyone anything anywhere anytime. New York: Wiley.
Horzum, M. B. (2011). Web pedagojik içerik bilgisi ölçeği’nin türkçeye uyarlaması
Adaptation of web pedagogical content knowledge survey to Turkish]. İlköğretim Online [Elementary Education Online], 10(1), 257-272. Horzum, M. B. (2012). The effect of web based instruction on students’ web pedagogical content knowledge, course achievement and general course satisfaction. Cukurova University Faculty of Education Journal, 41(1), 36-51.
Hunt, D. L. (1999). Web-based training. In W. J. Rothwell & K. J. Sensenig (Eds.),
The Sourcebook For Self-Directed Learning (pp. 121-145). Amherst, MA: HRD Press. Jackson, M. D. (1998). A distance-education chemistry course for nonmajors.
Journal of Science Education and Technology, 7(2), 163-170. Jong, D., & Wang, T. S. (2009). Student acceptance of web-based learning system.
Proceedings of the 2009 International Symposium on Web Information Systems and Applications (WISA’09) (pp. 533-553). Nanchang, People Republic of China.
Kao, C. P., & Tsai, C. C. (2009). Teachers’ attitudes toward web-based professional development, with relation to Internet self-efficacy and beliefs about web-based learning. Computers & Education, 53, 66-73.
Kao, C. P., Wu, Y. T., & Tsai, C. C. (2009). Elementary school teachers’ motivation toward web-based Professional development, and the relationship with Internet self-efficacy and belief about web-based learning. Teaching and Teacher Education, 27, 406-415.
Kao, C., Wu, Y. T., & Tsai, C.C. (2011). Elementary school teachers’ motivation toward web-based professional development, and the relationship with Internet self-efficacy and belief about web-based learning. Teaching and Teacher Education, , 406-415.
Kahn, B.H. (1997). Web-based instruction (WBI): What is it and why is it? In B. H.
Kahn (Ed.), Web-Based Instruction (pp. 5-23). Englewood-Cliffs, NJ: Educational Technology Publications, Inc. King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model.
Information & Managemement, 43,740-755. Koehler, M.J., & Mishra, P. (2009). What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education. 9(1).
Retrieved March 17, 2012,http://www.citejournal.org/vol9/iss1/general/article1.cfm
Kollias, V., Mamalougos, N., Vamvakoussi, X., Lakkala, M., & Vosniadou, S. (2005).
Teachers’ attitudes to and beliefs about web-based collaborative learning environments in the context of an international implementation. Computers & Education, 45, 295-315. Kumar, D.D., & Altschuld, J.W. (2002). Complementary approaches to evaluation of technology in science education. Journal of Science Education and Technology, (2), 179-191.
Lederer, A. L., Maupin, D. J., Sena, M.P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29, 269–282.
Lee, M. H. & Tsai, C.C. (2010). Exploring teachers’ perceived self efficacy and technological pedagogical content knowledge with respect to educational use of the World Wide Web. Instructional Science, 38(1), 1-21.
Lee, M. H., Tsai, C. C. & Chang, C. Y. (2008). Exploring teachers’ self-efficacy toward the web pedagogical content knowledge in Taiwan. Annual meeting of the american educational research association. New York, 24-28 Mart, 2008. Retrieved
March 17, 2012, from http://www.ntnu.edu.tw/acad/rep/r97/a2/a201-1.doc
Lertlum, W., & Papasratorn, B. (2006). Factors influencing rote learner's intention to use WBL: Developing country study. International Journal of Electrical and Computer Engineering, 1(1), 61-66.
Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e- learning technology acceptance. Computers & Education, 52, 599-697.
Lu, J., Yu, L. C. S, Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206.
Lynch, M. M. (2002). The online educator: a guide to creating the virtual classroom.
London: Routledge Falmer Taylor & Francis Group. Ma, O., & Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End User Computing, 16(1), 59-72.
Martins, L. L., & Kellermanns, F. W. (2004). A model of business school students’ acceptance of a Web-based course management system. Academy of Management
Learning and Education, 3, 7-26. Masrom, M. (2007). Technology acceptance model and e-learning. 12th
International Conference on Education, Sultan Hassanal Bolkiah Institute of Education Universiti Brunei Darussalam. 21-24 May 2007. Retrieved March 17, , from http://eprints.utm.my/5482/1/MaslinMasrom2006_Techn.pdf
Mishra, P. & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Norton, L., Richardson, J. T. E, Hartley, J., Newstead, S. & Mayes, J. (2005).
Teachers’ beliefs and intentions concerning teaching in higher education. Higher Education, 50, 537-571. 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. Russell, M., Bebell, D., O’Dwyer, L., & O’Connor, K. (2003). Examining teacher technology use: implications for preservice and inservice teacher preparation.
Journal of Teacher Education, 54(4), 297-310. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
Smarkola, C. (2011). A mixed-methodological technology adoption study. In T. Teo (Ed.),
Technology acceptance in education: Research and issues. Rotterdam: Sense Publishers Sun, D., & Looi, C. K. (2012). Designing a web-based science learning environment for model- based collaborative inquiry. Journal of Science Education and Technology. Retrieved April 17, , http://www.springerlink.com/content/x21t25416446t170/fulltext.pdf?MUD=MP
Venkatesh, V., & Davis, F. D. (2000). The theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Waheed, M. (2009). A study of teacher’s acceptance of elearnıng technology: TAM as the core model. eGovshare. Retrieved March 17, 2012, from http://edem.todaie.gov.tr/yd39_STUDY_OF_TEACHER%E2%80%99S_ACCEPTANCE_OF_eLEARNING_T
ECHNOLOGY__TAM_AS_THE_CORE_MODEL.pdf. Yang, F. Y., & Tsai, C. C. (2008). Investigating university student preferences and beliefs about learning in the web-based context. Computers & Education, 50, 1284–1303.
Yang, F. Y., & Chang, C. C. (2009). Examining high-school students' preferences toward learning environments, personal beliefs and concept learning in web-based contexts. Computers & Education, 52, 848-857.
Yi, M. Y., & Hwang, Y. (2003). Predictingthe use of web-based information systems: Self- efficacy, enjoyment, learning goal orientation, and the technology acceptance model.
International Journal of Human-Computer Studies, 59, 431-449.

Details

Primary Language

English

Subjects

-

Journal Section

-

Authors

Mehmet Barıs Horzum This is me

Ozlem Canan Gungoren This is me

Publication Date

September 1, 2012

Submission Date

February 27, 2015

Acceptance Date

-

Published in Issue

Year 2012 Volume: 13 Number: 3

IZ

https://izlik.org/JA48CG22RK

APA

Horzum, M. B., & Gungoren, O. C. (2012). A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction. Turkish Online Journal of Distance Education, 13(3), 50-69. https://izlik.org/JA48CG22RK

AMA

1.Horzum MB, Gungoren OC. A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction. TOJDE. 2012;13(3):50-69. https://izlik.org/JA48CG22RK

Chicago

Horzum, Mehmet Barıs, and Ozlem Canan Gungoren. 2012. “A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction”. Turkish Online Journal of Distance Education 13 (3): 50-69. https://izlik.org/JA48CG22RK.

EndNote

Horzum MB, Gungoren OC (September 1, 2012) A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction. Turkish Online Journal of Distance Education 13 3 50–69.

IEEE

[1]M. B. Horzum and O. C. Gungoren, “A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction”, TOJDE, vol. 13, no. 3, pp. 50–69, Sept. 2012, [Online]. Available: https://izlik.org/JA48CG22RK

ISNAD

Horzum, Mehmet Barıs - Gungoren, Ozlem Canan. “A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction”. Turkish Online Journal of Distance Education 13/3 (September 1, 2012): 50-69. https://izlik.org/JA48CG22RK.

JAMA

1.Horzum MB, Gungoren OC. A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction. TOJDE. 2012;13:50–69.

MLA

Horzum, Mehmet Barıs, and Ozlem Canan Gungoren. “A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction”. Turkish Online Journal of Distance Education, vol. 13, no. 3, Sept. 2012, pp. 50-69, https://izlik.org/JA48CG22RK.

Vancouver

1.Mehmet Barıs Horzum, Ozlem Canan Gungoren. A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction. TOJDE [Internet]. 2012 Sep. 1;13(3):50-69. Available from: https://izlik.org/JA48CG22RK

A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers Towards Web Based Instruction

Abstract

Keywords

Abstract

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

IZ

Cite

A Model For Beliefs, Tool Acceptance Levels And Web Pedagogical Content Knowledge Of Science And Technology Preservice Teachers  Towards Web Based Instruction