Usage-based Grammar Learning as Insight Problem Solving

Trabajo presentado en la EAPCogSci 2015, EuroAsianPacific Joint Conference on Cognitive Science (4th European Conference on Cognitive Science y 11th International Conference on Cognitive Science), celebrada en Turín del 25 al 27 de septiembre de 2015.We report on computational experiments in which a learning agent incrementally acquires grammar from a tutoring agent through situated embodied interactions. The learner is able to detect impasses in routine language processing, such as missing a grammatical construction to integrate a word in the rest of the sentence structure, to move to a meta-level to repair these impasses, primarily based on semantics, and to then expand or restructure his grammar using insights gained from repairs. The paper proposes a cognitive architecture able to support this kind of insight learning and tests it on a grammar learning task.The research reported here has been funded by an ICREA Research fellowship to LS and a Marie Curie Integration Grant EVOLAN. The project has received further funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 308943, which is the FET-OPEN Insight project.Peer reviewe

Learning science: Sociocultural Dimensions of Intellectual Engagement

This paper takes a sociocultural perspective as it addresses the problem of engaging all students in learning science, in contrast to a companion (ASERA ’02) paper where I address the issue in relation to psychological issues, both papers arising from the same set of research studies in science education. In both cases I am asserting that the interaction between the teacher and student is critical in either engaging or alienating students, and, in this paper will address the language aspects of the relationship. Seen in the light of sociocultural, including sociolinguistic, theories, my research findings imply that `science literacy’ could usefully be reconceptualised as the learning of a discourse, or as the learning of a literacy or language—as literacy or language teachers might define these. This paper addresses the development of science literacy as a process of situated learning within a meaningful social context, what Lemke (1995) called an "ecosocial system". From this perspective, learning science is the learning of a discourse. This includes becoming familiar with genres but not in isolation from meaningful community practice. I conclude that if science is seen as a distinct discourse practice, then this has implications for the learning and teaching of science and for teacher education

Comparative assessment of young learners' foreign language competence in three Eastern European countries

This paper concerns teacher practices in, and beliefs about, the assessment of young learners' progress in English in three Eastern European countries (Slovenia, Croatia, and the Czech Republic). The central part of the paper focuses on an international project involving empirical research into assessment of young learners' foreign language competence in Slovenia, Croatia and the Czech Republic. With the help of an adapted questionnaire, we collected data from a non-random sample of primary and foreign language teachers who teach foreign languages at the primary level in these countries. The research shows that English as a foreign language is taught mostly by young teachers either primary specialists or foreign language teachers. These teachers most frequently use oral assessment/interviews or self-developed tests. Other more authentic types of assessment, such as language portfolios, are rarely used. The teachers most frequently assess speaking and listening skills, and they use assessment involving vocabulary the most frequently of all. However, there are significant differences in practice among the three countries

Text reconstruction activities and teaching language forms

Even though there is a broad consensus that teaching language forms is facilitative or even necessary in some contexts, there are still disagreements concerning, among other things, how formal aspects of the target language should be taught. One important area of controversy is whether pedagogic intervention should be input-oriented, emphasizing comprehension of the form- meaning mappings represented by specific linguistic features or output-based, requiring learners to produce these features accurately in gradually more communicative activities. The present paper focuses on the latter of these two options and, basing on the claims of Swain‘s (1985, 1995) output hypothesis, it aims to demonstrates how text-reconstruction activities in which learners collaboratively produce written output trigger noticing, hypothesis-testing and metalinguistic reflection on language use. It presents a psycholinguistic and sociolinguistic rationale for the use of such tasks, discusses the types of such activities, provides an overview of research projects investigating their application and, finally, offers a set of implications for classroom use as well as suggestions for further research in this area

Overfitting in Synthesis: Theory and Practice (Extended Version)

In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatically generate a program belonging to a grammar of possible implementations that meets a logical specification. We investigate a common limitation across state-of-the-art SyGuS tools that perform counterexample-guided inductive synthesis (CEGIS). We empirically observe that as the expressiveness of the provided grammar increases, the performance of these tools degrades significantly. We claim that this degradation is not only due to a larger search space, but also due to overfitting. We formally define this phenomenon and prove no-free-lunch theorems for SyGuS, which reveal a fundamental tradeoff between synthesizer performance and grammar expressiveness. A standard approach to mitigate overfitting in machine learning is to run multiple learners with varying expressiveness in parallel. We demonstrate that this insight can immediately benefit existing SyGuS tools. We also propose a novel single-threaded technique called hybrid enumeration that interleaves different grammars and outperforms the winner of the 2018 SyGuS competition (Inv track), solving more problems and achieving a $5\times$ mean speedup.Comment: 24 pages (5 pages of appendices), 7 figures, includes proofs of theorem

Ontology-driven conceptual modeling: A'systematic literature mapping and review

All rights reserved. Ontology-driven conceptual modeling (ODCM) is still a relatively new research domain in the field of information systems and there is still much discussion on how the research in ODCM should be performed and what the focus of this research should be. Therefore, this article aims to critically survey the existing literature in order to assess the kind of research that has been performed over the years, analyze the nature of the research contributions and establish its current state of the art by positioning, evaluating and interpreting relevant research to date that is related to ODCM. To understand and identify any gaps and research opportunities, our literature study is composed of both a systematic mapping study and a systematic review study. The mapping study aims at structuring and classifying the area that is being investigated in order to give a general overview of the research that has been performed in the field. A review study on the other hand is a more thorough and rigorous inquiry and provides recommendations based on the strength of the found evidence. Our results indicate that there are several research gaps that should be addressed and we further composed several research opportunities that are possible areas for future research

Grounding semantics in robots for Visual Question Answering

In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning

Information, knowledge and the context of interaction

Representing knowledge as information content alone is insufficient in providing us with an understanding of the world around us. A combination of context as well as reasoning of the information content is fundamental to representing knowledge, within information –based systems. The field of knowledge representation and knowledge management has thus far been concerned with providing structures and theories that can lead to some form of qualified intelligent reasoning, and contextualised information. By drawing upon previous research and applying and extending concepts of Semiotics and Symbiosis from the interaction design school of thought, this paper presents a conceptual framework for establishing the interplay between knowledge and users of knowledge via information systems constructs. Subsequently, by drawing upon notions of interfaces to knowledge, a conceptual framework which describes the relationship between the semiotic, symbiotic and interface to knowledge presented, along with a discussion of contemporary issues common to the field of knowledge management is developed