English Reading Teaching in Senior High School from the Perspective of Deep Learning

The introduction of the concept of deep learning has led to a change in the way of learning, and a new teaching concept has been constructed from the aspects of learning content and overall understanding. In English, students must construct a comprehensive, detailed and systematic knowledge structure when reading and master language under the premise of deep thinking, and then absorb and internalize it through dialectical thinking. Practice shows that the combination of deep learning and senior high school English reading teaching conforms to the law of English teaching development, and is also an effective strategy to optimize and upgrade English reading teaching. Therefore, on the basis of summarizing the connotation and characteristics of deep learning, the author put forward targeted suggestions according to the existing problems

Adapting to a New Chinese Environment: The Case of Foreign Invested Enterprises in China

After undergoing economic reform for more than two decades, China’s GDP is growing around 10% annually and has been moving forward in rapid steps to becoming the world’s next economic giant. Its attraction to foreign investment has also kept in a strong momentum. Being faced with a vast market with tremendous potential, more and more foreign companies and investors are considering whether and how to translate this potential growth into gains and get the lion’s share. In terms of the number and scale, foreign invested enterprises (FIEs) have been expanding rapidly. Up to 2006, there are 594,000 registered FIEs in China with US$700 billion assets.1 They hire 28 million Chinese employees, which is one tenth of the total non-agricultural population. Meanwhile, most of the investors who have taken the plunge in China have gained great returns. In 2006, 21.1% of the taxes collected nationwide was from the FIEs, and the average return of the mutual fund that invests in China has increased about 15% over the past three years.

WeSolv: MBA Job Analysis

WeSolv is a startup that focuses on bringing the most qualified candidates to prospective hiring companies by designing and utilizing case challenges to accurately assess the candidates’ skill sets. The case challenges consist of several activities (presentations, research, etc.) that the candidates must execute, which measure their fit for potential jobs. For the past academic year, the company has provided information on how to obtain insight on their system metrics and to better understand the process of choosing their assessing skills. Since desired skills in candidates are fluid throughout time, the company needs to constantly ensure that they have the right information to stay aligned with the current markets. The research project consists of utilizing public resources (LinkedIn, Indeed, Glass Door, etc.) to identify the overall preferred skills for selective MBA jobs. During the business project, the company has benefited from the research performed and the integration of the constantly shifting new job market information. The biggest impact this research served was the discovery of new skills that align with the shifting desire in the job market, and the confirmation of suitable skills identified from the past.https://digitalcommons.imsa.edu/intern_reports_2020/1020/thumbnail.jp