A generating technique and knowledge representation of multiple-answer problems for learning with solving knowledge

摘要

BackgroundErroneous answers in multiple-answer problems not only make the correct answer harder to determine but also indicate why the correct choice is suitable and the erroneous one a mistake when compared to the correct answer. However, it is insufficient to simply create erroneous answers for this purpose: explanations of these answers are also required. Preexisting studies examining functions for generating erroneous answers and their explanations based on this approach are abundant. Nevertheless, a major bottleneck has formed in this research body concerning the related specialized knowledge descriptions that are required for the generation function.