The COVID-19 pandemic has necessitated a shift to online assessments, posing significant challenges for teachers in fairly evaluating student performance. The absence of invigilation has led to widespread cheating, with students copying answers from the Internet or top-ranked peers. This paper addresses these issues by proposing guidelines and techniques for fair student assessment without invigilation. The research begins with an analysis of traditional assessment methods and their limitations in the context of unmonitored online exams. It then explores various online examination frameworks, including multiple-choice questions, short-answer questions, and interactive simulations. The study identifies key weaknesses in current online assessment practices and highlights the potential of advanced online examination frameworks. By implementing the suggested techniques, educators can improve the reliability and fairness of online assessments, ensuring a more accurate evaluation of students' knowledge. This article serves as a valuable resource for educators, instructional designers, and e-learning professionals seeking to enhance the efficacy of online assessments.

In the field of natural language processing, simple sentence has a great importance; especially for multiple choice question generation, automatic text summarization, opinion mining, machine translation and information retrieval etc. Most of these tasks use simple sentences and include a sentence simplification module as pre-processing or post-processing task. But dedicated tasks for sentence simplification are hardly found. Here we have proposed a novel system for generating simple sentences from complex and compound sentences. Our proposed system is an initiative for simplifying sentence by converting complex and compound sentences into simple ones. Along with this the system classifies the simple sentences of an input corpus from other types of sentences. To generate simple sentences from complex and compound sentences we have proposed a novel algorithm which takes the dependency parsing of the input text and produce simple sentences as output. The experimental result demonstrates that the proposed technique is a promising one.