NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Coppola, Cristina; Mollo, Monica; Pacelli, Tiziana – European Journal of Psychology of Education, 2019
This paper presents a Vygotskian research device that focuses on collaborative activities based on the manipulation of linguistic objects in a primary school classroom, with 8-9-year-old children. Through social exchanges among the different points of view, the children were engaged in a dynamic process of building and negotiating mathematical…
Descriptors: Language Skills, Elementary School Students, Semantics, Syntax
Peer reviewed Peer reviewed
Direct linkDirect link
Krahmer, Emiel; Koolen, Ruud; Theune, Mariet – Cognitive Science, 2012
In a recent article published in this journal (van Deemter, Gatt, van der Sluis, & Power, 2012), the authors criticize the Incremental Algorithm (a well-known algorithm for the generation of referring expressions due to Dale & Reiter, 1995, also in this journal) because of its strong reliance on a pre-determined, domain-dependent Preference Order.…
Descriptors: Natural Language Processing, Mathematics, Computational Linguistics
Peer reviewed Peer reviewed
Direct linkDirect link
van Deemter, Kees; Gatt, Albert; van der Sluis, Ielka; Power, Richard – Cognitive Science, 2012
A substantial amount of recent work in natural language generation has focused on the generation of "one-shot" referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We…
Descriptors: Natural Language Processing, Mathematics, Computational Linguistics
Barker-Plummer, Dave; Dale, Robert; Cox, Richard; Romanczuk, Alex – International Educational Data Mining Society, 2012
We have assembled a large corpus of student submissions to an automatic grading system, where the subject matter involves the translation of natural language sentences into propositional logic. Of the 2.3 million translation instances in the corpus, 286,000 (approximately 12%) are categorized as being in error. We want to understand the nature of…
Descriptors: Logical Thinking, Grading, Natural Language Processing, Translation