Examination of Primary School Teacher Candidates' Views on Distance Education: A Mixed-Method Study

Büşra Nur Turan, Rabia Asal Özkan
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Abstract

This study aimed to gather prospective primary school teachers' opinions on distance education and ascertain whether these opinions varied based on different variables. A mixed-methods approach was employed to obtain more reliable results, with the sequential explanatory design being utilized in the study. The research sample comprised 233 teacher candidates from Erciyes University's Ziya Eren Faculty of Education during the 2020-2021 academic year who participated in distance education amidst the COVID-19 pandemic. The Distance Education Students' Views of Distance Education Scale, developed by Yıldırım, Yıldırım, Çelik, and Karaman (2014), served as a quantitative data collection instrument. Qualitative data were gathered online via a structured interview form. Descriptive statistics such as percentages, frequencies, and arithmetic means were used to analyze the quantitative data. Since the data exhibited a normal distribution, t-tests and ANOVAs were conducted. The Qualitative data analysis involved using the descriptive analysis method for the semi-structured interview responses. The findings of the study revealed that the opinions of primary school teacher candidates regarding distance education did not significantly differ based on gender or home internet access. However, significant differences were identified in relation to class level and duration of internet usage. Based on these results, recommendations were provided, such as enhancing distance education infrastructure within universities.
小学教师考生远程教育观测评:一种混合方法研究
本研究旨在收集未来小学教师对远程教育的意见,并确定这些意见是否因不同的变量而有所不同。为了获得更可靠的结果,我们采用了混合方法,研究中采用了顺序解释设计。研究样本包括埃尔西耶斯大学Ziya Eren教育学院2020-2021学年的233名教师候选人,他们在COVID-19大流行期间参加了远程教育。由Yıldırım, Yıldırım, Çelik和Karaman(2014)开发的远程教育学生对远程教育的看法量表作为定量数据收集工具。定性数据通过结构化访谈表格在线收集。使用描述性统计如百分比、频率和算术平均数来分析定量数据。由于数据呈正态分布,因此进行t检验和方差分析。定性数据分析涉及使用描述性分析方法对半结构化访谈的回应。本研究结果显示,小学教师候选人对远程教育的看法并没有因性别或家庭上网而有显著差异。然而,在班级水平和互联网使用时间方面存在显著差异。根据这些结果,提出了建议,例如加强大学内部的远程教育基础设施。
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