Raising students' awareness of cross-cultural contrastive rhetoric in English writing via an e-learning course

This study investigated the potential impact of e-learning on raising overseas students' cultural awareness and explored the possibility of creating an interactive learning environment for them to improve their English academic writing. The study was based on a comparison of Chinese and English rhetoric in academic writing, including a comparison of Chinese students' writings in Chinese with native English speakers' writings in English and Chinese students' writings in English with the help of an e-course and Chinese students' writings in English without the help of an e-course. Five features of contrastive rhetoric were used as criteria for the comparison. The experimental results show that the group using the e-course was successful in learning about defined aspects of English rhetoric in academic writing, reaching a level of performance that equalled that of native English speakers. Data analysis also revealed that e-learning resources helped students to compare rhetorical styles across cultures and that the interactive learning environment was effective in improving overseas students' English academic writing

Redesigning the European Union’s trade policy strategy towards China

The European Union’s recent trade policy strategy towards China, which focuses on bilateral market access and involves a strong U S-style confrontational stance, is ineffective and short-sighted. Today there exists no genuine dialogue between China and the EU on crucial commercial issues. This paper calls for foresightedness in the European Union’s policies towards China. It reviews the EU’s strategy and proposes concrete policy options that will allow it to more effectively promote its commercial interests in China, by focusing on topics that will draw support from Chinese interests and bring greater economic benefits for both parties. In trade in goods, the paper proposes a “small bargain”, involving the granting of market economy status to China in antidumping, in exchange for China’s improvement of its WTO tariff schedule implementation. In its “behind-the-border” rules agenda, the proposed EU-China Partnership and Cooperation Agreement could develop a truly “grand bargain” involving a strong reduction of China’s highest barriers on inward FDI in services, better access by China to the EU’s services markets, joint procedures to address China’s Sovereign Wealth Funds’ and EU’s norms and standards. It would also involve an important scaling down of Europe’s requests in issues such as intellectual property rights. More broadly, the EU should review its current trade policy strategy based on bilateral deals and re-focus its trade policy on the WTO. The paper finally argues that EU should also adopt a truly global approach in its trade policy towards China. This means involving not only the United States and Japan, but also successful medium-sized industrial and emerging economies

Analysis and Detection of Information Types of Open Source Software Issue Discussions

Most modern Issue Tracking Systems (ITSs) for open source software (OSS) projects allow users to add comments to issues. Over time, these comments accumulate into discussion threads embedded with rich information about the software project, which can potentially satisfy the diverse needs of OSS stakeholders. However, discovering and retrieving relevant information from the discussion threads is a challenging task, especially when the discussions are lengthy and the number of issues in ITSs are vast. In this paper, we address this challenge by identifying the information types presented in OSS issue discussions. Through qualitative content analysis of 15 complex issue threads across three projects hosted on GitHub, we uncovered 16 information types and created a labeled corpus containing 4656 sentences. Our investigation of supervised, automated classification techniques indicated that, when prior knowledge about the issue is available, Random Forest can effectively detect most sentence types using conversational features such as the sentence length and its position. When classifying sentences from new issues, Logistic Regression can yield satisfactory performance using textual features for certain information types, while falling short on others. Our work represents a nontrivial first step towards tools and techniques for identifying and obtaining the rich information recorded in the ITSs to support various software engineering activities and to satisfy the diverse needs of OSS stakeholders.Comment: 41st ACM/IEEE International Conference on Software Engineering (ICSE2019