检查在土耳其最有成就的大学的最新英语硕士论文和博士论文的抽象组成部分

Pınar GÜLER URHAN
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摘要

本研究的目的是研究土耳其10个英语教学部门的硕士论文和博士论文的最新摘要,以观察英语教学领域摘要部分的最新趋势。一篇写得好的摘要的组成部分是研究范式、样本、样本大小、方法、样本类型、研究设计、数据收集工具和数据分析技术。对“YÖK Ulusal Tez Merkezi”(国家论文中心)上最新的10篇硕士论文和10篇博士论文的摘要进行了综述,并从这些成分的可获得性方面进行了分析。这10所大学是从2020-2021年大学学业成绩排名(URAP)中选出的。采用标准抽样。本非互动定性研究采用描述性文献分析。以建构主义的观点来解释摘要中特定元素的存在与缺失。MS Excel是用于分析的程序。结果显示,所有学生都没有表达研究范式,但都表达了他们使用的数据收集工具。所有博士生都说明了他们的样本是谁,但没有说明实施的抽样类型。虽然大多数硕士生指定了他们的样本,但只有少数人指定了他们使用的样本类型。两组的可用样本量完全相同。博士生命名研究设计多于硕士生。然而,硕士生在他们的摘要中提到了更多的抽样策略、方法和数据分析。
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Examining the Abstract Components of the Latest ELT M.A. Theses and PhD Dissertations of the Most Accomplished Universities in Turkey
The purpose of this study is to examine the latest abstracts of M.A. theses and PhD dissertations of 10 ELT departments in Turkey so as to observe the latest tendency in the abstract components of the ELT field. The components of a well written abstract are research paradigms, samples, sample size, method, sample type, research design, data collection tools, and data analysis techniques. The abstracts of the latest 10 MA theses and 10 PhD dissertations available in “YÖK Ulusal Tez Merkezi” (National Thesis Center) were reviewed and analyzed in terms of the availability of these components. These 10 universities were selected from the top achievers determined by University Ranking by Academic Performance (URAP) in 2020-2021. Criterion sampling was employed. This non-interactive qualitative study utilized descriptive document analysis. A constructivist view was taken to interpret the presence and absence of specific element in the abstracts. MS Excel was the program used for analysis. The results showed that none of the students expressed research paradigms but all expressed data collection tools they used. All PhD students stated who their samples were but type of sampling implemented was not stated. While most of the MA students specified their samples, only a couple specified type of sampling they used. The availability of sample size was exactly the same for both groups. PhD students named research designs more than MA students. Yet, MA students named more sampling strategies, methods, and data analysis in their abstracts.
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