Pre-Service Computer Teachers’ Tendencies Towards the Use of Mobile Technologies: A Technology Acceptance Model Perspective

Ünal Çakıroğlu; Seyfullah Gökoğlu; Mücahit Öztürk

doi:10.1515/eurodl-2017-0011

Pre-Service Computer Teachers’ Tendencies Towards the Use of Mobile Technologies: A Technology Acceptance Model Perspective

European Journal of Open, Distance and E-Learning

Volume 20 (2017): Issue 1

By: Ünal Çakıroğlu, Seyfullah Gökoğlu and Mücahit Öztürk

Open Access

|Jan 2018

Abstract

Drawing on the Technology Acceptance Model (TAM), this exploratory study examines the preservice teachers’ adoption of mobile technologies through the factors of current use, instructionaluse and future use in their teaching practices. Participants were 466 pre-service computer teachers enrolled at a public university in Turkey. A questionnaire developed by the researchers was used to collect data. Results indicated that the current use and instructional use factors had a strong positive correlation and also there was a similar correlation with the factor of future use and current use. Relationships between current, instructional, and future use of mobile technologies explained within the context of perceived usefulness, ease of use, and behavioural intention constructs of the TAM.

Soyut

Teknoloji Kabul Modelini (TKM) temele alınarak gerçekleştirilen bu keşfedici araştırmada, öğretmen adaylarının mobil teknolojileri benimseme durumları mevcut kullanım, öğretimsel kullanım ve gelecekteki öğretim uygulamalarındaki kullanım durumları çerçevesinde incelenmiştir. Araştırmanın katılımcılarını Türkiye’deki bir üniversitede öğrenim gören 466 bilişim teknolojileri öğretmen adayı oluşturmaktadır. Veri toplama aracı olarak araştırmacılar tarafından geliştirilen bir anket kullanılmıştır. Araştırma bulguları mevcut kullanım ve öğretimsel kullanım faktörleri arasında yüksek düzeyde olumlu bir ilişki olduğunu; benzer şekilde mevcut kullanım ile gelecekteki kullanım faktörleri arasında da benzer bir ilişki düzeyi olduğunu göstermektedir. Mobil teknolojilerin mevcut, öğretimsel ve gelecekteki kullanım durumları arasındaki ilişki TKM’nin algılanan fayda, kullanım kolaylığı ve davranışsal niyet gibi temel bileşenleri çerçevesinde açıklanmıştır.

References

1. Acarli, D. S., & Sağlam, Y. (2015). Investigation of pre-service teachers’ intentions to use of social media in teaching activities within the framework of technology acceptance model. Procedia-Social and Behavioral Sciences, 176, 709-713.
Search in Google Scholar Back to article
2. Aktaş, S. (2007). An application on technology acceptance model and accountants’ use of information technology. (Unpublished master’s thesis). Gebze Institute of Technology, Turkey.
Search in Google Scholar Back to article
3. Attewell, J., Savill-Smith, C., Douch, R., & Parker, G. (2010). Modernising education and training: Mobilising technology for learning. London: Regent Arcade House.
Search in Google Scholar Back to article
4. Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human relations, 45(7), 659-686.
Search in Google Scholar Back to article
5. Baydas, O., & Göktaş, Y. (2016). Influential factors on pre-service teachers’ intentions to use ICT in future lessons. Computers in Human Behavior, 56, 170-178.
Search in Google Scholar Back to article
6. Behera, S. (2013). M-learning: A new learning paradigm. International Journal on New Trends in Education & Their Implications, 4(2), 24-34.
Search in Google Scholar Back to article
7. Cacho, R. M. (2017). Student teachers’ smartphone academic uses and preferences: Perspectives for mobile-aided pedagogy. Proceedings of the International Conference on ICT and Knowledge Engineering, 57-61. doi:10.1109/ICTKE.2016.7804099
Open DOI Search in Google Scholar Back to article
8. Camilleri, V., & Montebello, M. (2011, May). Virtual World Presence for Pre-service Teachers: Does the TAM Model Apply? Proceedings of the Games and Virtual Worlds for Serious Applications (VS-GAMES), 2011 Third International Conference on, 156-159. IEEE.
Search in Google Scholar Back to article
9. Chen, F. H., Looi, C. K., & Chen, W. (2009). Integrating technology in the classroom: a visual conceptualization of teachers’ knowledge, goals and beliefs. Journal of Computer Assisted Learning, 25(5), 470-488.
Search in Google Scholar Back to article
10. Chih-Yung, T., Chih-Chiang, W., & Ming-Te, L. (2011). Using the technology acceptance model to analyze ease of use of a mobile communication system. Social Behavior & Personality: An International Journal, 39(1), 65-69.
Search in Google Scholar Back to article
11. Creswell, J. W. (2005). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (2nd ed.). Upper Saddle River, N.J.: Pearson Merrill Prentice Hall.
Search in Google Scholar Back to article
12. Darren Pullen, J. F., Swabey, K., Abadooz, M., & Sing, T. K. R. (2015). Pre-service teachers’ acceptance and use of mobile learning in Malaysia. Australian Educational Computing, 30(1).
Search in Google Scholar Back to article
13. 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.
Search in Google Scholar Back to article
14. Dexter, S., Doering, A. H., & Riedel, E. S. (2006). Content area specific technology integration: A model for educating teachers. Journal of Technology and Teacher Education, 14(2), 325.
Search in Google Scholar Back to article
15. Edmunds, R., Thorpe, M., & Conole, G. (2012). Student attitudes towards and use of ICT in course study, work and social activity: A technology acceptance model approach. British Journal of Educational Technology, 43(1), 71-84.
Search in Google Scholar Back to article
16. Escobar-Rodriguez, T., & Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58(4), 1085-1093.
Search in Google Scholar Back to article
17. Frias-Martinez, V., Virseda, J, & Gomero, A. (2012, September). Mobilizing education: Evaluation of a mobile learning tool in a low-income school. Paper presented at the 14th International Conference on Human-Computer Interaction with Mobile Devices and Services, San Francisco, USA.
Search in Google Scholar Back to article
18. Fulantelli, G., Taibi, D., & Arrigo, M. (2015). A framework to support educational decision making in mobile learning. Computers in Human Behavior, 47, 50-59.
Search in Google Scholar Back to article
19. Georgiev, T., Georgieva, E., & Smrikarov, A. (2004, June). M-learning-a new stage of е-learning. Paper presented at the International Conference on Computer Systems and Technologies, Rousse, Bulgaria.
Search in Google Scholar Back to article
20. Goktas, Y., Yildirim, S., & Yildirim, Z. (2009). Main barriers and possible enablers of ICTs integration into pre-service teacher education programs. Educational Technology & Society, 12(1), 193-204.
Search in Google Scholar Back to article
21. Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343-367.
Search in Google Scholar Back to article
22. Hu, P., Clark, T. H., & Ma, W. W. (2003). Examining technology acceptance by school teachers: A longitudinal study. Information & Management, 41(2), 227-241.
Search in Google Scholar Back to article
23. Jaradat, M. I. R. (2013). Applying the technology acceptance model to the introduction of mobile voting. International Journal of Mobile Learning and Organisation, 7(1), 29-47.
Search in Google Scholar Back to article
24. Joo, Y. J., Lee, H. W., & Ham, Y. (2014). Integrating user interface and personal innovativeness into the TAM for mobile learning in Cyber University. Journal of Computing in Higher Education, 26(2), 143-158.
Search in Google Scholar Back to article
25. Kafyulilo, A. (2014). Access, use and perceptions of teachers and students towards mobile phones as a tool for teaching and learning in Tanzania. Education & Information Technologies, 19(1), 115-127.
Search in Google Scholar Back to article
26. Keller, C. (2005). Virtual learning environments: Three implementation perspectives. Learning, Media & Technology, 30(3), 299-311.
Search in Google Scholar Back to article
27. Kim, D., Chun, H., & Lee, H. (2014). Determining the factors that influence college students’ adoption of smartphones. Journal of the Association for information Science and Technology, 65(3), 578-588.
Search in Google Scholar Back to article
28. Kriek, J., & Stols, G. (2010) Teachers’ beliefs and their intention to use interactive simulations in their classrooms. South African Journal of Education, 30(3), 439-456.
Search in Google Scholar Back to article
29. Koca, M. (2006). Examining teachers? Use of information and communication technology according to variables of unified model of information and communication technology. (Unpublished master’s thesis). Hacettepe University, Turkey.
Search in Google Scholar Back to article
30. Kuo, K. M., Liu, C. F., & Ma, C. C. (2013). An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC medical informatics and decision making, 13(1), 88.
Search in Google Scholar Back to article
31. Kuşkonmaz, H. (2011). Determining teacher’s perception of mobile learning at secondary schools. (Unpublished master’s thesis). Bahçeşehir University, Turkey.
Search in Google Scholar Back to article
32. Lee, M. K., Cheung, C. M., & Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information & management, 42(8), 1095-1104.
Search in Google Scholar Back to article
33. Ma, W. W., Andersson, R. R., & 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.
Search in Google Scholar Back to article
34. Menzi, N., Önal, N., & Çalışkan, E. (2012). Investigating educational researchers’ views of using mobile technologies for educational purposes based on technology acceptance model. Ege Journal of Education, 13(1), 40-55.
Search in Google Scholar Back to article
35. Mun, Y. Y., & Hwang, Y. (2003). Predicting the use of web-based information systems: selfefficacy, enjoyment, learning goal orientation, and the technology acceptance model. International journal of human-computer studies, 59(4), 431-449.
Search in Google Scholar Back to article
36. Murray, O. T., & Olcese, N. R. (2011). Teaching and learning with iPads, ready or not? TechTrends, 55(6), 42-48.
Search in Google Scholar Back to article
37. Nistor, N. (2014). When technology acceptance models won’t work: Non-significant intention-behavior effects. Computers in Human Behavior, 34, 299-300.
Search in Google Scholar Back to article
38. Park, S., Nam, M., & Cha, S. (2012). University students’ behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4), 592-605.
Search in Google Scholar Back to article
39. Phuangthong, D., & Malisawan, D. (2005, August). A study of behavioral intention for 3G mobile internet technology: Preliminary research on mobile learning. Paper presented at the 2nd International Conference on eLearning for Knowledge-Based Society, Bangkok, Thailand.
Search in Google Scholar Back to article
40. Saadé, R., Nebebe, F., & Tan, W. (2007). Viability of the “Technology Acceptance Model” in multimedia learning environments: A comparative study. Journal of Knowledge & Learning Objects, 3(1), 175-184.
Search in Google Scholar Back to article
41. Sánchez-Prieto, J. C., Migueláñez, S. O., & García-Peñalvo, F. J. (2014). ICTs integration in education: mobile learning and the technology acceptance model (TAM). Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality, 683-687. ACM.
Search in Google Scholar Back to article
42. Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2016). Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers. Computers in Human Behavior, 55.
Search in Google Scholar Back to article
43. Teo, T. (2012). Examining the intention to use technology among pre-service teachers: An integration of the technology acceptance model and theory of planned behavior. Interactive Learning Environments, 20(1), 3-18.
Search in Google Scholar Back to article
44. Turan, B. (2011). The research of the usage of information and communication technologies via technology acceptance model and an application on elementary school teachers. (Unpublished master’s thesis). Bilecik Şeyh Edebali University, Turkey.
Search in Google Scholar Back to article
45. Uzunboylu, H., & Ozdamli, F. (2011). Teacher perception for m-learning: Scale development and teachers’ perceptions. Journal of Computer Assisted Learning, 27(6), 544-556.
Search in Google Scholar Back to article
46. Valtonen, T. (2011). An insight into collaborative learning with ICT: Teachers’ and students’ perspectives. University of Eastern Finland.
Search in Google Scholar Back to article
47. 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 & Education, 81, 49-58.
Search in Google Scholar Back to article
48. Virvou, M., & Alepis, E. (2005). Mobile educational features in authoring tools for personalised tutoring. Computers & Education, 44, 53-68.
Search in Google Scholar Back to article
49. Wang, R., Wiesemes, R., & Gibbons, C. (2012). Developing digital fluency through ubiquitous mobile devices: Findings from a small-scale study. Computers & Education, 58(1), 570-578.
Search in Google Scholar Back to article
50. Wang, Y., Wu, M., & Wang, H. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92-118.
Search in Google Scholar Back to article
51. Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
Search in Google Scholar Back to article
52. Yamakawa, P., Delgado, C., Díaz, E., Garayar, E., & Laguna, H. (2013). Factors influencing the use of mobile technologies in a university environment: A case from Latin America. International Journal of Information and Communication Technology Education (IJICTE), 9(2), 24-38.
Search in Google Scholar Back to article
53. Yong-Wee, S., Siong-Hoe, L., Kung-Keat, T., Check-Yee, L., &Parumo, S. (2010). Prediction of user acceptance and adoption of smart phone for learning with technology acceptance model. Journal of Applied Sciences, 10(20), 2395-2402.
Search in Google Scholar Back to article
54. Yuen, A. H., & Ma, W. W. (2008). Exploring teacher acceptance of e-learning technology. Asia-Pacific Journal of Teacher Education, 36(3), 229-243.
Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.1515/eurodl-2017-0011 | Journal eISSN: 1027-5207

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Language: English

Page range: 176 - 191

Published on: Jan 23, 2018

Published by: EDEN Digital Learning Europe

In partnership with: Paradigm Publishing Services

Keywords:

mobile technologies,

pre-service computer teachers,

technology acceptance model,

future tendencies

© 2018 Ünal Çakıroğlu, Seyfullah Gökoğlu, Mücahit Öztürk, published by EDEN Digital Learning Europe
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 20 (2017): Issue 1