Nowadays, teachers opt for presenting students with various, often unnecessary, technological tools to compensate for their lack of preparation for the classes. The research is critical to understanding how to use technology effectively and beneficially to students for fostering a comfortable learning environment and encouraging outstanding academic performance. Having settled the question and the purpose of the problem, it is of utmost importance to proceed to formulate null and alternative hypotheses that would play a pivotal role in producing reliable findings.
It is fair to assume that teachers do not use technology in classes to compensate for the insufficient preparation for teaching the required material (null statistical assumption). Naturally, statistical tests are needed to test this hypothesis and consider other reasons for tutors employing technology; otherwise, it would be regarded as false. However, the alternative assumption, in this case, would be that tutors decide to involve technology-related tasks or presentations because of the inability to teach the student due to the prior lack of preparation for the classes. The alpha significance level in this research is 5% to avoid Type I error (supporting the alternative hypothesis instead of the null when the latter is true).
Consequently, providing that the study generates valid and reliable findings, it can help the teaching field immensely. To be more exact, teachers might be held accountable for not high-quality teaching methods they employ in their classes because of insufficient preparation. Besides, this research would be the basis for further exploration of the practical and productive ways of implementing technology means to the classes to improve students’ understanding and academic performance.
The importance of researching this matter is immense to ensure adequate education in educational establishments. Yet it is evident that sometimes teachers do not put effort into proper technological integration and rather use the means as a paper substitute (Emre, 2019). What is more, educators often opt to use technology in class as busy work, which mostly happens because of the tutors’ inability to teach the material (Fu et al., 2020; Xu et al., 2019). In other words, instead of preparing for the lessons, tutors might turn on unhelpful Youtube videos (often without watching them beforehand) to keep the students busy (Bawack et al., 2020). All in all, the poor technology implementation into the learning environment is not only useless but does not compensate for productive learning experiences that can be achieved when teachers put effort into preparing for the classes (Nelson et al., 2019). Besides, inadequate technology use does not lead to students investigating and diving into content by opting for practical discussions, projects, and scientific work within the class.
The theoretical framework of the study is to be primarily based on exploring the theories concerning poor technological integration as a result of the concept misunderstanding. However, Emre (2019) argued that the main reason for the ineffective use of technology in the classroom is not only due to the inability to understand the notion but because of viewing it as a tool to compensate for one’s incompetence. Naturally, these theories have to be further investigated to test the hypotheses considering the alpha significance level. Yet exploration of the misconception of technological integration is of utmost importance to set the basis for fundamental research and avoid Type I error (and II) to achieve valid and reliable results.
References
Bawack, R. E., & Kala Kamdjoug, J. R. (2020). The role of digital information use on student performance and collaboration in marginal universities. International Journal of Information Management, 54, 102179. Web.
Dinc, E. (2019). Prospective Teachers’ Perceptions of Barriers to Technology Integration in Education. Contemporary Educational Technology, 10(4), 381–398. Web.
Fu, S., Li, H., Liu, Y., Pirkkalainen, H., & Salo, M. (2020). Social media overload, exhaustion, and use discontinuance: Examining the effects of information overload, system feature overload, and social overload. Information Processing &Amp; Management, 57(6), 102307. Web.
Nelson, M. J., Voithofer, R., & Cheng, S. L. (2019). Mediating factors that influence the technology integration practices of teacher educators. Computers &Amp; Education, 128, 330–344. Web.
Xu, X., Wang, J., Peng, H., & Wu, R. (2019). Prediction of academic performance associated with internet usage behaviors using machine learning algorithms. Computers in Human Behavior, 98, 166–173. Web.