While research on students’ perceptions of code-switching in EFL classrooms has proliferated over the past several decades, limited research has been conducted to understand students’ perceptions with different levels of language proficiency in English. Drawing on both quantitative and qualitative data collected from students with different English proficiency levels, the present research reports students’ perceptions of teacher code-switching in EFL speaking classrooms in Chinese tertiary context. The quantitative data collected from questionnaires show that students do not favor total immersion. Students believe that English should be the medium of instruction for activities and their opinions show mixed results under the circumstances of teaching grammar and usage of English. Mixed opinions are also found in terms of teacher switching to Chinese to give administrative information and test information. The qualitative data in the questionnaire suggest that students prefer Chinese teacher of English owning to better understanding, and they attribute their levels of English as the deciding factor of their preferences. No statistical differences achieved regarding the perceptions from Level One and Level Two students. Findings suggest that the systematic and effective use of learner’s L1 is beneficial for language teaching in speaking classrooms, and L1 can be regarded as a powerful tool to develop effective teaching approaches for English language teachers.

No abstract

We propose an O(N • M ) sorting algorithm by Machine Learning method, which shows a huge potential sorting big data. This sorting algorithm can be applied to parallel sorting and is suitable for GPU or TPU acceleration. Furthermore, we discuss the application of this algorithm to sparse hash table.

No abstract