Research Article

Using UTAUT model to assess the factors influencing the use of ICT in Ghanaian pre-tertiary mathematics education

Sampson Owusu Bandoh 1 , Emmanuel Akweittey 1 , Ebenezer Kwesi Lotey 1 * , Joseph Frank Gordon 1 , Ebenezer Appiagyei 1
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1 Department of Mathematics Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, GHANA* Corresponding Author
Journal of Digital Educational Technology, 4(1), 2024, ep2407, https://doi.org/10.30935/jdet/14297
Published: 27 February 2024
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ABSTRACT

As the demand for acquiring Information communication and technology has increased rapidly due to the exponential growth of technological advancement in all human endeavor, researchers are also developing theories and/or models that could be used to describe and prognosticate humans’ espousal and use of these technologies as they are being released in the markets. The present study adapted one of the powerful models for information and communication technology (ICT) integration (thus, unified theory of acceptance and technology use) to assess pre-tertiary mathematics facilitators’ intentions and actual use of ICT for mathematics instructions in Ghana. This study adopts a quantitative research approach with a questionnaire as a survey instrument for collecting 185 valid data from both junior and senior high schools’ mathematics facilitators. Descriptive statistics and an enter multiple regression were deployed to validate the proposed research questions. Using SPPS v.23 as a statistical software for analyzing the data, the result reveals that, performance expectancy, and effort expectancy had a positive and significant effect on mathematics facilitators’ intentions toward ICT adoption. Moreover, social influence was significant but had a negative impact on facilitators intentions. The impact of mathematics facilitators’ intention to use ICT and the facilitating conditions (FCs) within the school environment was also a positive and significant predictor of facilitators’ ICT use behavior. It was concluded from the findings that FCs were the better predictor for mathematics teachers’ ICT use behavior than intention. Hence, the researchers recommended that more government expenditure must be allocated to infrastructures that would improve the use of ICT as well as frequent ICT training must be undertaken to enrich teachers’ knowledge in the affordance of using ICT in mathematics classrooms.

CITATION (APA)

Bandoh, S. O., Akweittey, E., Lotey, E. K., Gordon, J. F., & Appiagyei, E. (2024). Using UTAUT model to assess the factors influencing the use of ICT in Ghanaian pre-tertiary mathematics education. Journal of Digital Educational Technology, 4(1), ep2407. https://doi.org/10.30935/jdet/14297

REFERENCES

  1. Agyei, D. D., & Voogt, J. (2011). ICT use in the teaching of mathematics: Implications for professional development of pre-service teachers in Ghana. Education and Information Technologies, 16(4), 423-439. https://doi.org/10.1007/s10639-010-9141-9
  2. Aliyu, A. A., Bello, M. U., Kasim, R., & Martin, D. (2014). Positivist and non-positivist paradigm in social science research: Conflicting paradigms or perfect partners? Journal of Management and Sustainability, 4(3), 79-95. https://doi.org/10.5539/jms.v4n3p79
  3. Al-zboon, H. S., Gasaymeh, A. M., & Al-Rsa’i, M. S. (2021). The attitudes of science and mathematics teachers toward the integration of information and communication technology (ICT) in their educational practice: The application of the unified theory of acceptance and use of technology (UTAUT). World Journal of Education, 11(1), 75-85. https://doi.org/10.5430/wje.v11n1p75
  4. Aydin, M. K., & Gurol, M. (2019). A systematic review of critical factors regarding ICT use in teaching and learning. International Journal of Progressive Education, 15(4), 108-129. https://doi.org/10.29329/ijpe.2019.203.9
  5. Beglar, D., & Nemoto, T. (2014). Developing Likert-scale questionnaires. In Proceedings of the JALT2013 Conference.
  6. Birch, A., & Irvine, V. (2009). Preservice teachers’ acceptance of ICT integration in the classroom: Applying UTAUT model. Educational Media International, 46(4), 295-315. https://doi.org/10.1080/09523980903387506
  7. Budiharso, T., & Tarman, B. (2020). Improving quality education through better working conditions of academic institutes. Journal of Ethnic and Cultural Studies, 7(1), 99-115. https://doi.org/10.29333/ejecs/306
  8. Chen, J. L. (2011). The effects of education compatibility and technological expectancy on e-learning acceptance. Computers and Education, 57(2), 1501-1511. https://doi.org/10.1016/j.compedu.2011.02.009
  9. Christensen, L. (2015). Research methods, design, and analysis. Pearson.
  10. Cimperman, M., Makovec Brenčič, M., & Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior-applying an extended UTAUT model. International Journal of Medical Informatics, 90, 22-31. https://doi.org/10.1016/j.ijmedinf.2016.03.002
  11. Das, K. (2019a). Role of ICT for better mathematics teaching. Shanlax International Journal of Education, 7(4), 19-28. https://doi.org/10.34293/education.v7i4.641
  12. Foutsitzi, S., & Caridakis, G. (2019). ICT in education: Benefits, challenges and new directions. In Proceedings of the 10th International Conference on Information, Intelligence, Systems and Applications. https://doi.org/10.1109/IISA.2019.8900666
  13. Graham, M. A., Stols, G., & Kapp, R. (2020). Teacher practice and integration of ict: Why are or aren’t south african teachers using icts in their classrooms. International Journal of Instruction, 13(2), 749-766. https://doi.org/10.29333/iji.2020.13251a
  14. Harrison, R., Meyer, L., Rawstorne, P., Razee, H., Chitkara, U., Mears, S., & Balasooriya, C. (2022). Evaluating and enhancing quality in higher education teaching practice: A meta-review. Studies in Higher Education, 47(1), 80-96. https://doi.org/10.1080/03075079.2020.1730315
  15. Ince-Muslu, B., & Erduran, A. (2020). A suggestion of a framework: Conceptualization of the factors that affect technology integration in mathematics education. International Electronic Journal of Mathematics Education, 16(1), em0617. https://doi.org/10.29333/iejme/9292
  16. Jefferson, F., & Paul, J. (2019). A comparative analysis of student performance in an online vs. face-to-face environmental science course from 2009 to 2016. Frontiers in Computer Science, 7.
  17. Jehlička, V., & Rejsek, O. (2018). A multidisciplinary approach to teaching mathematics and information and communication technology. EURASIA Journal of Mathematics, Science and Technology Education, 14(5), 1705-1705. https://doi.org/10.29333/EJMSTE/85109
  18. Khambari, M. N. M., Luan, W. S., & Ayub, A. F. M. (2010). Technology in mathematics teaching: The pros and cons. Procedia-Social and Behavioral Sciences, 8, 555-560. https://doi.org/10.1016/j.sbspro.2010.12.077
  19. Khlaif, Z. (2018). Teachers’ perceptions of factors affecting their adoption and acceptance of mobile technology in K-12 settings. Computers in the Schools, 35(1), 49-67. https://doi.org/10.1080/07380569.2018.1428001
  20. Kivunja, C., & Kuyini, A. B. (2017). Understanding and applying research paradigms in educational contexts. International Journal of Higher Education, 6(5), 26-41. https://doi.org/10.5430/ijhe.v6n5p26
  21. Kuhn, T. S. (1962). The structure of scientific revolutions. University of Chicago Press.
  22. Kul, U., Celik, S., & Aksu, Z. (2018). The impact of educational material use on mathematics achievement: A meta-analysis. International Journal of Instruction, 11(4), 303-324. https://doi.org/10.12973/iji.2018.11420a
  23. Kumar Jaiswal, S. (2017). Role of parental involvement and some strategies that promote parental involvement. Journal of International Academic Research for Multidisciplinary, 3(2), 95.
  24. Lee, B. C., & Xie, J. (2018). How do aging adults adopt and use a new technology? New approach to understand aging service technology adoption. Communications in Computer and Information Science, 851, 161-166. https://doi.org/10.1007/978-3-319-92279-9_22
  25. Lewis, C. C., Fretwell, C. E., Ryan, J., & Parham, J. B. (2013). Faculty use of established and emerging technologies in higher education: A unified theory of acceptance and use of technology perspective. International Journal of Higher Education, 2(2), 22-34. https://doi.org/10.5430/ijhe.v2n2p22
  26. Lotey, E. K., Arthur, Y. D., Gordon, J. F., & Adu-Obeng, B. (2023). Modeling basic schoolteachers acceptance of instructional technology in advancing mathematical pedagogy in Ghana. Contemporary Mathematics and Science Education, 4(1), ep23006. https://doi.org/10.30935/conmaths/12811
  27. Luan, W. S., & Teo, T. (2011). Student teachers’ acceptance of computer technology: An application of the technology acceptance model (TAM). In T. Teo (Ed.), Technology acceptance in education (pp. 43-61). Springer. https://doi.org/10.1007/978-94-6091-487-4_3
  28. Luhamya, A., Bakkabulindi, F. E. K., & Muyinda, P. B. (2017). Integration of ICT in teaching and learning: A review of theories. Makerere Journal of Higher Education, 9(1), 21. https://doi.org/10.4314/majohe.v9i1.2
  29. Mackenzie, N & Knipe, S. (2006). Research dilemmas: Paradigms, methods and methodology. Issues in Educational Research, 16(2), 193-205.
  30. Mandailina, V., Saddam, S., Ibrahim, M., & Syaharuddin, S. (2019). UTAUT: Analysis of usage level of Android applications as learning media in Indonesian educational institutions. International Journal of Education and Curriculum Application, 2(3), 16. https://doi.org/10.31764/ijeca.v2i3.2080
  31. Mayer, R. E. (2019). Thirty years of research on online learning. Applied Cognitive Psychology, 33(2), 152-159. https://doi.org/10.1002/acp.3482
  32. McGehee, J., & Griffith, L. K. (2020). Technology enhances student learning across the curriculum. Mathematics Teaching in the Middle School, 9(6), 344-349. https://doi.org/10.5951/mtms.9.6.0344
  33. Mustajab, D., Bauw, A., Rasyid, A., Irawan, A., Akbar, M. A., & Hamid, M. A. (2020). Working from home phenomenon as an effort to prevent COVID-19 attacks and its impacts on work productivity. The International Journal of Applied Business, 4(1), 13. https://doi.org/10.20473/tijab.v4.i1.2020.13-21
  34. National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. School Science and Mathematics, 47(8), 868-279.
  35. Owusu-Fordjour, C., Koomson, K., & Hanson, D. (2020). The impact of COVID-19 on learning–The perspective of the Ghanaian student. European Journal of Education Studies, 7(3), 88-101.
  36. Perienen, A. (2020). Frameworks for ICT integration in mathematics education–A teacher’s perspective. EURASIA Journal of Mathematics, Science and Technology Education, 16(6), em1845. https://doi.org/10.29333/EJMSTE/7803
  37. Raj Joshi, D. (2017). Influence of ICT in mathematics teaching. International Journal for Innovative Research in Multidisciplinary Field, 3(1), 7-11.
  38. Raman, A., & Rathakrishnan, M. (2018). Frog VLE: Teachers’ technology acceptance using utaut model. International Journal of Mechanical Engineering and Technology, 9(3), 529-538.
  39. Ruiz, M. J. S., Molina, R. I. R., Amaris, R. R. A., & Raby, N. D. L. (2022). Types of competencies of human talent supported by ICT: Definitions, elements, and contributions. Procedia Computer Science, 210(C), 368-372. https://doi.org/10.1016/j.procs.2022.10.166
  40. Saal, P. E., Graham, M. A., & van Ryneveld, L. (2020). Integrating educational technology in mathematics education in economically disadvantaged areas in South Africa. Computers in the Schools, 37(4), 253-268. https://doi.org/10.1080/07380569.2020.1830254
  41. Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers and Education, 128, 13-35. https://doi.org/10.1016/j.compedu.2018.09.009
  42. Shah, S. N. A., Khan, A. U., Khan, B. U., Khan, T., & Xuehe, Z. (2021). Framework for teachers’ acceptance of information and communication technology in Pakistan: Application of the extended UTAUT model. Journal of Public Affairs, 21(1), e2090. https://doi.org/10.1002/pa.2090
  43. Sievertsen, H. H., Gino, F., & Piovesan, M. (2016). Cognitive fatigue influences students’ performance on standardized tests. Proceedings of the National Academy of Sciences of the United States of America, 113(10), 2621-2624. https://doi.org/10.1073/pnas.1516947113
  44. Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273-1296. https://doi.org/10.1007/s11165-016-9602-2
  45. Tomasik, M. J., Helbling, L. A., & Moser, U. (2021). Educational gains of in-person vs. distance learning in primary and secondary schools: A natural experiment during the COVID-19 pandemic school closures in Switzerland. International Journal of Psychology, 56(4), 566-576. https://doi.org/10.1002/ijop.12728
  46. Tyas, E. H., & Naibaho, L. (2021). Hots learning model improves the quality of education. International Journal of Research, 9(1), 176-182. https://doi.org/10.29121/granthaalayah.v9.i1.2021.3100
  47. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
  48. Verger, A., Fontdevila, C., & Parcerisa, L. (2019). Reforming governance through policy instruments: How and to what extent standards, tests and accountability in education spread worldwide. Discourse, 40(2), 248-270. https://doi.org/10.1080/01596306.2019.1569882
  49. Vyas, L., & Butakhieo, N. (2021). The impact of working from home during COVID-19 on work and life domains: An exploratory study on Hong Kong. Policy Design and Practice, 4(1), 59-76. https://doi.org/10.1080/25741292.2020.1863560
  50. Wijaya, T. T., Cao, Y., Weinhandl, R., Yusron, E., & Lavicza, Z. (2022). Applying UTAUT model to understand factors affecting micro-lecture usage by mathematics teachers in China. Mathematics, 10(7), 1008. https://doi.org/10.3390/math10071008
  51. Yuen, A. H. K., & Ma, W. W. K. (2008). Exploring teacher acceptance of e-learning technology. Asia-Pacific Journal of Teacher Education, 36(3), 229-243. https://doi.org/10.1080/13598660802232779
  52. Zakaria, N. A., & Khalid, F. (2016). The benefits and constraints of the use of information and communication technology (ICT) in teaching mathematics. Creative Education, 07(11), 1537-1544. https://doi.org/10.4236/ce.2016.711158