Question generation (QG) is to generate natural and grammatical questions that can be answered by a specific answer for given context. Previous sequence-to-sequence models suffer from problem asking high-quality requires commonsense knowledge as backgrounds, which in most cases not learned directly training data, resulting unsatisfactory deprived of knowledge. In this paper, we propose multi-ta...

Question Generation (QG) is an essential component of the automatic intelligent tutoring systems, which aims to generate high-quality questions for facilitating reading practice and assessments. However, existing QG technologies encounter several key issues concerning biased unnatural language sources datasets are mainly obtained from Web (e.g. SQuAD). In this paper, we propose innovative Exami...

The present study examined possible memory and metacomprehension benefits of using a combined question self-generation and answering technique, relative to rereading, as a study strategy for expository passages. In the 2 question self-generation and answering conditions (detail or conceptual questions), participants were prompted on how to generate questions of a particular type (detail or conc...