Automatic generation of exercises on passive transformation in Portuguese

Abstract

Technology plays a very important role in education and Intelligent Computer-Assisted Language Learning (iCALL) has emerged as a complementary or even alternative method to the conventional language teaching practices. The automatic generation (and correction) of language exercises based on real texts extracted from corpora constitutes a non-trivial challenge to iCALL tutorial systems, and may involve the use of sophisticated Natural Language Processing tools and large-scale linguistic resources. This paper presents the main issues related to the automatic generation of exercises on the Passive transformation, a commonly occurring type of exercises in language textbooks, but also a very complex topic of Portuguese grammar. The paper describes the methods used to produce a large batch of passive-active sentence pairs, where the active sentence was automatically generated from naturally occurring passive sentences, taken from a large-sized, publicly available, corpus. Sentence pairs are ranked by difficulty level. A sample of randomly selected sentence pairs (40 from difficult level, 100 from medium, and 100 from easy level) was manually evaluated by an expert. Results are presented and error analysis is performed. The sentence pairs can be used as prime and correct answer for iCALL systems.