Conceptual Knowledge

An interlingua is a notation for representing the content of a text that abstracts away from the characteristics of the language itself and focuses on the meaning (semantics) alone. Interlinguas are typically used as pivot representations in machine translation, allowing the contents of a source text to be generated in many different target languages. Because of the complexities involved, few interlinguas are more than demonstration prototypes, and only one has been used in a commercial MT system. In this article, we define the components of an interlingua and the principal issues faced by designers and builders of interlinguas and interlingua MT systems, illustrating with examples from operational systems and research prototypes. We discuss current efforts to annotate texts with interlingua-based information.

Despite the essential role of food in our lives, we have little understanding of the way our knowledge about food is organized in the brain. At birth, human infants exhibit very few food preferences, and do not yet know much about what is edible and what is not. A multisensory learning development will eventually turn young infants into omnivore adults, for whom deciding what to eat becomes an effortful task. Recognizing food constitutes an essential step in this decisional process. In this paper we examine how concepts about food are represented in the human brain. More specifically, we first analyze how brain-damaged patients recognize natural and manufactured food, and then examine these patterns in the light of the sensory-functional hypothesis and the domain-specific hypothesis. Secondly, we discuss how concepts of food are represented depending on whether we embrace the embodied view or the disembodied view. We conclude that research on food recognition and on the organization of knowledge about food must also take into account some aspects specific to food category, the relevance of which has not been sufficiently recognized and investigated to date.

We report on a fuzzy logic-based language understanding system applied to speech recognition. This system acquires conceptual knowledge from corpus data and organizes such knowledge into fuzzy logic inference rules. The system parses speech recognition results into conceptual structures in a robust manner, and thus is able to tolerate noise caused by speech recognition errors. We discuss the fuzzy inference rule learning method and explain its organization. Experimental results that demonstrate the ability of the system to deal with complex speech input instances are reported

Early exposure to science may have a lifelong effect on children’s attitudes towards science and their motivation to learn science in later life. Out-of-class environments can play a significant role in creating favourable attitudes, while contributing to conceptual learning. Educational science theatre is one form of an out-of-class environment, which has received little research attention. This study aims to describe affective and cognitive learning outcomes of watching such a play and to point to connections between theatrical elements and specific outcomes. “Atom Surprise” is a play portraying several concepts on the topic of matter. A mixed methods approach was adopted to investigate the knowledge and attitudes of children (grades 1–6) from two different school settings who watched the play. Data were gathered using questionnaires and in-depth interviews. Analysis suggested that in both schools children’s knowledge on the topic of matter increased after the play with younger children gaining more conceptual knowledge than their older peers. In the public school girls showed greater gains in conceptual knowledge than boys. No significant changes in students’ general attitudes towards science were found, however, students demonstrated positive changes towards science learning. Theatrical elements that seemed to be important in children’s recollection of the play were the narrative, props and stage effects, and characters. In the children’s memory, science was intertwined with the theatrical elements. Nonetheless, children could distinguish well between scientific facts and the fictive narrative.

This article presents a case study of the development of second language (L2) sociopragmatic knowledge in an intermediate-level US university learner of French, Jane (a pseudonym), who participated in a one-hour concept-based instruction (CBI) tutorial. Grounded in a Vygotskian perspective on developmental education, this research focuses on the teaching of scientific, or theoretical, concepts as a way of mediating language learners’ developing understanding of and ability to use the L2 for meaning-making purposes. The focus of the present study is on sociopragmatic concepts related to the choice between French second-person pronouns, TU and VOUS. An in-depth moment-to-moment, microgenetic analysis traces how changes in Jane's cognitive functioning (i.e., conceptual knowledge) arose in and through her engagement in the CBI tutorial, which included collaboration with an expert tutor as well as access to such mediating artifacts as written concept explanations and pedagogical diagrams.► Sociopragmatic concepts can be taught to second language learners. ► Verbalization facilitates appropriation of concepts. ► Concepts help learners establish personally meaningful understandings of pragmatics.

Problem solving theory and practice suggest that thinking is more important to solving problems than knowledge and that it is possible to teach thinking in situations where little or no knowledge of the problem is needed. Such an assumption has led problem solving advocates to champion content-less heuristics as the primary element of problem solving while relegating the knowledge base and the application of concepts or transfer to secondary status. In the following theoretical analysis, it will be argued that the knowledge base and transfer of knowledge—not the content-less heuristic—are the most essential elements of problem solving.

In academic texts, use of cohesive devices contributes to text coherence between sentences, thereby facilitating comprehension and learning (Hall et al., 2014; Ozuru et al., 2009; Yuniartiah et al., 2018). Because English scientific texts are multimodal, encompassing orthographic texts and images (i.e., multisemiotic), a study of salient multimodal textual and logical cohesive relations is necessary, as is investigating how students use these multimodal texts to extend conceptual and logical meaning-making relations-in other words, how pictorial representations are integrated with verbal texts to construct what Lemke (2005) calls "a system of organizational relations defining wholes and parts of those wholes" (p. 94). Halliday and Hasan (2014) define cohesive relation as "the semantic relation between an element in the text and some other element that is crucial to the interpretation of it" (p. 8). In the study of textual and logical features in tertiary contexts, applications of Systemic Functional Multimodal Discourse Analysis (SF-MDA) of cohesive devices have previously been confined to business studies (