Purpose: This study assessed the effects on the Listening Comprehension of Different Non-native English Accents on Chinese Learners of English. The study aimed to determine, first of all, the reaction of Chinese learners of English to different non-native English accents. Second, it sought to investigate the differences in the difficulties that Chinese learners of English face while listening to English spoken with accents native (Chinese English accent) or non-native. Third, the study attempted to find out the relationship between English spoken with the native Chinese accent and/or non-native English accents and listening comprehension.
Methodology/Approach/Design: The sample included 16 participants majoring in International Education of Chinese Language. They were selected randomly for the study. Both quantitative and qualitative approaches were employed to collect and analyze data.
Results: The findings revealed that non-native English accent plays a more important role than the native English accents in listening and comprehension. The findings also revealed a listening comprehension advantage for test-takers who are familiar with accents, in this case, the Chinese non-native English accent.
Practical Implications: For a better understanding of the teaching and learning process of English as a foreign language, learners or listeners need to assess the influence of non-native accents on their listening comprehension to find better ways in improving their listening skills. This study contributes significantly to this field.
Originality/Value: This study employed multi non-native accent including African English accents. It attempted to contribute significant value in this field as most of the teachers who teach English globally are non-native English Speakers and they, in essence, have considerable influence on the learners’ listening comprehension.
Open source software (OSS) is currently a widely adopted approach to developing and distributing software. Many commercial companies are using OSS components as part of their product development. For instance, more than 58% of web servers are using an OSS web server, Apache. For effective adoption of OSS, fundamental knowledge of project development is needed. This often calls for reliable prediction models to simulate project evolution and to envision project future. These models provide help in supporting preventive maintenance and building quality software. This chapter reports on a systematic literature survey aimed at the identification and structuring of research that offers prediction models and techniques in analysing OSS projects. The study outcome provides insight into what constitutes the main contributions of the field, identifies gaps and opportunities, and distils several important future research directions. This chapter extends the authors' earlier journal article and offers the following improvements: broader study period, enhanced discussion, and synthesis of reported results.
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