Content Writer Screening MCQs


This test evaluates the candidate’s technical content understanding, conceptualizing and writing skills. The content writing profile requires reading of technical research papers, understanding and summarizing them. At this web page, one research paper is embedded. You need to generate the MCQ answers and summary of the paper as instructed below.  The research paper summary within 700-800 words needs to be submitted along with answers to the below questions for each paper. Kindly avoid plagiarism too.

There are a few rules to make reading easy and fast. You have to take these points into consideration during the test.

  1. while reading the research paper, the following questions should be answered in 1-2 sentences:

    • what is the problem targeted in the paper

    • what is the key contribution in terms of the solution to the problem statement

    • what is the outcome of the work contributed in the paper

    • The idea conception of other existing works. Any common attribute or extension of methodology or common dataset etc.

  2. Critically summarize the answers to these questions into 2-3 lines and link them with the previous paper’s similar summary

  3. In the end, summarize the whole work carried out from the perspective of the existing research gaps

Ways to analyze the paper and answer these questions quickly

Normally, a research paper consists of many sections like abstract, introduction, related work/background, proposed work, results and conclusion. You need to analyze only these sections to get the answers to the above questions:

  1. Abstract: Normally, can answer the targeted problem in the paper

  2. The last two paragraphs of the introduction: highlight the major contribution

  3. Conclusion: The paper outcome or results achieved.

Research Paper to Read

MCQ Questions & Summary Form

    1. What is the proposed method utilized in the paper?

    2. What is the problem addressed in the proposed model?

    3. What are the three important steps proposed to enhance the resilience of power grids?

    4. What is the difference between model predictive control and stochastic programming?

    5. How does the proposed DRL framework overcome the scalability issue in the presence of multiple decision-making agents?

    6. What is the State parameter set used in this reinforcement learning problem?

    7. What is the reward function used in this reinforcement learning problem?

    8. What is the average operation cost of the IRC model in the 123-bus network for the one hundred hurricane-induced outage scenarios?

    9. Which system did the proposed IRC model outperform in the simulation on the IEEE 123-bus test feeder?