Question Generation (QG) is proposed as a shared-task evaluation campaign for evaluating Natural Language Generation (NLG) research. QG is a subclass of NLG that plays an important role in learning environments, information seeking, and other applications. We describe a possible evaluation framework for standardized evaluation of QG that can be used for black-box evaluation, for finer-grained e...

We review three approaches to mesh generation that are based on analyzing and accounting for the geometric structure of the domain. In the rst approach, due to Armstrong, the domain is partitioned into subdomains based on the medial-axis transform, a tool for analyzing spatial structures. In the second approach, due to Cox, the design history de nes a geometric structure of the domain. The desi...

From the analysis of recent researches automatic question generation using deep learning techniques, we examined papers between 2022 and early 2023 from examination research on production techniques. Our study comes after survey report that broadens earlier evaluations AQG content surfaced late 2014 2019. We researched works were included, looking at things like (1) framework for (2) generating...

Abstract Learning through the internet becomes popular that facilitates learners to learn anything, anytime, anywhere from web resources. Assessment is most important in any learning system. An assessment system can find self-learning gaps of and improve progress learning. The manual question generation takes much time labor. Therefore, automatic resources primary task an automated This paper p...

Automatic Question Generation (AQG) is a research trend that enables teachers to create assessments with greater efficiency in right set of questions from the study material. Today's educational institutions require powerful tool correctly assess learner’s mastery concepts learned through materials. Objective type are an excellent method assessing learner's topic understanding learning process,...