Grammar constitutes one of the core components of a language. It is thus problematic that a gap can be found between steering documents and teacher practices in Sweden. The steering documents provide minimal guidance for teachers regarding grammar instruction, which leads to teachers instead relying on their own beliefs to determine their practices. This qualitative study uses semi-structured interviews to examine to what degree the beliefs and practices in relation to English grammar instruction of four teachers in the southern part of Sweden align with three theoretical approaches to grammar teaching from the reviewed research: focus on formS (FonFs), focus on meaning and focus on form (FonF). The results are characterized by individuality in both teachers’ beliefs and practices, but can also be seen to be fundamentally similar in that, for each teacher, the steering documents provide minimal guidance, and factors such as context and the centrality of the learner in grammar instruction are important. All teachers show tendencies toward the three theoretical approaches, but their actual alignment shifts and varies depending on context. We conclude that the absence of direction from the steering documents has the potential to result in disparate and fractured grammar instruction that can negatively impact the learner. This is therefore an important area that should be further researched to ensure that teachers receive sufficient guidance for providing English grammar instruction.

This thesis investigates fundamental questions surrounding the phenomenon of control, with an emphasis on control in Turkish, as well as the behaviour of control verbs in non-infinitival environments, which have received little attention previously. I focus solely on the cases of obligatory control (OC) which constitute the only kind of control that is conditioned by the matrix verb alone. This approach is couched in Combinatory Categorial Grammar (CCG) where the control verb projects the necessary syntactic and semantic information. In particular, I argue that the control behaviour is an entailment associated with the verb itself, and that variable, split and partial control are instances of OC. Hence, no special mechanism/structure is needed to account for their interpretation. As to the syntactic and semantic status of the complement, I maintain that the complement is a bare VP in syntax and denotes a property in semantics. Building upon the conclusions reached about OC, I attempt to account for additional complementation patterns of OC verbs. I argue that here too the matrix verb has a crucial role in ruling in and out possible complement types. Finally, I note that control involves much more than just figuring out the reference of the &ldquo / unexpressed&rdquo / subject of the complement, and I furthermore propose that the additional frames of an OC verb provide important clues as to its lexical meaning, which are argued to be relevant for the acquisition of control.

Both grammar and corrective feedback (CF) are important for second language acquisition, though they are not mentioned explicitly in the Swedish upper secondary school curriculum. Moreover, it is not clear which type of CF is most effective in grammar acquisition. This paper aims to consolidate, compare and contrast the findings of several articles examining the effect of CF on grammar acquisition. Two databases were used to find articles applicable to answering the research question. After excluding those that did not meet the criteria, nine articles were used in the end. Although the findings show that CF is effective for grammar acquisition in general, they do not show any type of CF to be superior to another. The factors identified as affecting the results of the studies are target structure, method, language proficiency and L1. Through the studies analyzed, it is not possible to establish the long-term effects of the various types of CF. Nevertheless, the findings suggest that oral meta-linguistic explanation (ME) is beneficial for teachers due to its time-efficiency. In conclusion, CF, being shown to facilitate grammar acquisition for L2 learners in general, has positive effects on English learning in the Swedish classroom. However, more research is needed in order to establish its effectiveness long-term and on a more detailed level.

Notre étude porte sur l’observation de connaissances linguistiques et métalinguistiques chez les adultes francophones apprenant l’Espagnol Langue Étrangère (ELE). Ces connaissances constituent la compétence grammaticale que les apprenants construisent au fur et à mesure qu’ils s’approprient la L2.Dans le but d’observer ces connaissances au stade intermédiaire d’apprentissage — c’est-à-dire au niveau seuil (B1) établi par le Cadre Commun de Référence pour les Langues (Conseil de l’Europe, 2001) —, nous avons procédé à une étude expérimentale auprès de 30 adultes francophones. Notre démarche comporte 2 tâches d’expérimentation : une tâche de décision et une tâche de production orale. La tâche de décision repose sur un test de jugement de grammaticalité : on demande aux participants d’évaluer, dans un temps limité, un corpus des phrases (exposées les unes après les autres, à la fois à l’écrit et à l’oral) dont certaines contenaient une erreur. Le corpus de phrases présenté à nouveau sur papier, on demande ensuite aux participants de donner un jugement définitif (sans mesure de temps de réponse), à partir duquel, s’ils jugent une phrase incorrecte, ils doivent indiquer où se situe l’erreur et l’expliquer. Quant à la tâche de production orale, il a été demandé aux participants de produire un discours descriptif et narratif en L2 espagnol à l’aide d’un stimulus visuel (bande dessinée). Les résultats de nos tâches expérimentales nous ont permis de recueillir des données sur le temps de réponse, sur la capacité de jugement de phrases, sur le type de discours employé pour expliquer l’erreur et sur les structures syntaxiques utilisées spontanément en production orale.Ces données sont analysées et discutées en vue de fournir des pistes sur la capacité des adultes francophones apprenant l’ELE à détecter des erreurs en langue cible et à en expliciter les règles transgressées ; sur les problèmes qu’ils retrouvent dans leur appropriation du système grammatical de l’espagnol ; et sur les connaissances dont ils se servent pour analyser et produire les structures de la langue objet. En outre, les résultats obtenus nous permettent à notre tour d’envisager autrement l’apprentissage de la grammaire de l’espagnol et d’avancer la perspective d’un modèle d’enseignement adapté aux capacités métacognitives et métalinguistiques de l’apprenant francophone. / The framework of our study is focused on the assessment of linguistic and metalinguistic knowledge of francophone adults learning Spanish as a foreign language. This knowledge constitutes the basis of grammatical competence built by learners as they develop skills in the target language.Our aim is the observation of linguistic and metalinguistic knowledge used by francophone adult learners of Spanish as a second language (L2). Thus, we designed and directed an experimental study to 30 French-speakers with a threshold-level in Spanish, based on the Common European Framework of Reference for Languages (Council of Europe, 2001). Our approach consisted of two experimental tasks: A decision making task and a task of oral production. The first task was conducted with a grammaticality judgement test in which participants had to evaluate, in a limited response time, a corpus of 36 sentences (presented one after the other, at both written and oral). The second task was conducted with the definitive confirmation of judgments about the corpus. Participants were thus asked to give a final judgement about the correctness of sentences (without measuring response time). If they judged a sentence as incorrect, they have to specify the error and explain it. As for the oral production task, the participants were asked to produce a descriptive and narrative speech in Spanish by using visual stimuli (a comic strip). The results achieved allowed us to collect data on the response time, on the sentences judgment ability, on the type of speech used to explain the error and on syntactical structures used spontaneously in oral speech. Those data were analyzed and discussed with the aim of providing insights on the capacity of francophone adults learning Spanish as a foreign language for detecting and explaining errors in the target language; on their difficulties in acquiring the Spanish grammatical system; and on their knowledge to analyze and produce structures in target language.The results enabled us to reconsider the learning of Spanish grammar otherwise with a view to teaching models adapted to the metacognitive and metalinguistic skills of francophone learners.

A longitudinal study lasting 3.5 years was conducted to investigate complex grammar development, focusing on acquisition of the passive and type 3 conditionals, and its relationship with a number of domain-general, domain-specific and environmental factors. 128 children (M = 5 years 10 months) were tested at the beginning and towards the end of each school year starting from Year 1. The administered measures included established tests of fluid intelligence, short-term and working memory, seriation, grammar, vocabulary, literacy and arithmetic, plus newly-developed tests of passive and conditional sentence acquisition, and arithmetic word problem solving. It was demonstrated that grammar acquisition is not complete even when children start Year 4 of primary school (M = 8 years 7 months), when the current study was completed. At that time, 32% of children have not acquired type 3 conditionals and 89% showed no understanding of centre-embedded sentences. However, only 3% showed no passive sentence acquisition. Fluid intelligence, verbal STM and WM, ability to seriate, vocabulary and parental education level were all found to contribute to individual differences in complex grammar acquisition, independently of age differences and, where relevant, independently of non-verbal ability. There were differences between the passives and the conditionals in their relationship to these variables. Complex grammar development was found to be a significant predictor of reading comprehension, spelling and arithmetic performance, independently of age, non-verbal ability, verbal STM and WM. The findings demonstrate the inter-relatedness of higher cognitive functions, particularly domain-general with domain-specific ones. Modularity in its strictest sense (informational encapsulation, functional isolation) is not present in normally developing brains. Educational applications of the results are discussed.

linguagem é uma marca da humanidade e da consciência, sendo a conversação (ou diálogo) uma das maneiras de comunicacão mais fundamentais que aprendemos quando crianças. Por isso uma forma de fazer um computador mais atrativo para interação com usuários é usando linguagem natural. Dos sistemas com algum grau de capacidade de linguagem desenvolvidos, o chatterbot Eliza é, provavelmente, o primeiro sistema com foco em diálogo. Com o objetivo de tornar a interação mais interessante e útil para o usuário há outras aplicações alem de chatterbots, como agentes conversacionais. Estes agentes geralmente possuem, em algum grau, propriedades como: corpo (com estados cognitivos, incluindo crenças, desejos e intenções ou objetivos); incorporação interativa no mundo real ou virtual (incluindo percepções de eventos, comunicação, habilidade de manipular o mundo e comunicar com outros agentes); e comportamento similar ao humano (incluindo habilidades afetivas). Este tipo de agente tem sido chamado de diversos nomes como agentes animados ou agentes conversacionais incorporados. Um sistema de diálogo possui seis componentes básicos. (1) O componente de reconhecimento de fala que é responsável por traduzir a fala do usuário em texto. (2) O componente de entendimento de linguagem natural que produz uma representação semântica adequada para diálogos, normalmente utilizando gramáticas e ontologias. (3) O gerenciador de tarefa que escolhe os conceitos a serem expressos ao usuário. (4) O componente de geração de linguagem natural que define como expressar estes conceitos em palavras. (5) O gerenciador de diálogo controla a estrutura do diálogo. (6) O sintetizador de voz é responsável por traduzir a resposta do agente em fala. No entanto, não há consenso sobre os recursos necessários para desenvolver agentes conversacionais e a dificuldade envolvida nisso (especialmente em línguas com poucos recursos disponíveis). Este trabalho foca na influência dos componentes de linguagem natural (entendimento e gerência de diálogo) e analisa em especial o uso de sistemas de análise sintática (parser) como parte do desenvolvimento de agentes conversacionais com habilidades de linguagem mais flexível. Este trabalho analisa quais os recursos do analisador sintático contribuem para agentes conversacionais e aborda como os desenvolver, tendo como língua alvo o português (uma língua com poucos recursos disponíveis). Para isto, analisamos as abordagens de entendimento de linguagem natural e identificamos as abordagens de análise sintática que oferecem um bom desempenho. Baseados nesta análise, desenvolvemos um protótipo para avaliar o impacto do uso de analisador sintático em um agente conversacional. / Language is a mark of humanity and conscience, with the conversation (or dialogue) as one of the most fundamental manners of communication that we learn as children. Therefore one way to make a computer more attractive for interaction with users is through the use of natural language. Among the systems with some degree of language capabilities developed, the Eliza chatterbot is probably the first with a focus on dialogue. In order to make the interaction more interesting and useful to the user there are other approaches besides chatterbots, like conversational agents. These agents generally have, to some degree, properties like: a body (with cognitive states, including beliefs, desires and intentions or objectives); an interactive incorporation in the real or virtual world (including perception of events, communication, ability to manipulate the world and communicate with others); and behavior similar to a human (including affective abilities). This type of agents has been called by several terms, including animated agents or embedded conversational agents (ECA). A dialogue system has six basic components. (1) The speech recognition component is responsible for translating the user’s speech into text. (2) The Natural Language Understanding component produces a semantic representation suitable for dialogues, usually using grammars and ontologies. (3) The Task Manager chooses the concepts to be expressed to the user. (4) The Natural Language Generation component defines how to express these concepts in words. (5) The dialog manager controls the structure of the dialogue. (6) The synthesizer is responsible for translating the agents answer into speech. However, there is no consensus about the necessary resources for developing conversational agents and the difficulties involved (especially in resource-poor languages). This work focuses on the influence of natural language components (dialogue understander and manager) and analyses, in particular the use of parsing systems as part of developing conversational agents with more flexible language capabilities. This work analyses what kind of parsing resources contributes to conversational agents and discusses how to develop them targeting Portuguese, which is a resource-poor language. To do so we analyze approaches to the understanding of natural language, and identify parsing approaches that offer good performance, based on which we develop a prototype to evaluate the impact of using a parser in a conversational agent.

linguagem é uma marca da humanidade e da consciência, sendo a conversação (ou diálogo) uma das maneiras de comunicacão mais fundamentais que aprendemos quando crianças. Por isso uma forma de fazer um computador mais atrativo para interação com usuários é usando linguagem natural. Dos sistemas com algum grau de capacidade de linguagem desenvolvidos, o chatterbot Eliza é, provavelmente, o primeiro sistema com foco em diálogo. Com o objetivo de tornar a interação mais interessante e útil para o usuário há outras aplicações alem de chatterbots, como agentes conversacionais. Estes agentes geralmente possuem, em algum grau, propriedades como: corpo (com estados cognitivos, incluindo crenças, desejos e intenções ou objetivos); incorporação interativa no mundo real ou virtual (incluindo percepções de eventos, comunicação, habilidade de manipular o mundo e comunicar com outros agentes); e comportamento similar ao humano (incluindo habilidades afetivas). Este tipo de agente tem sido chamado de diversos nomes como agentes animados ou agentes conversacionais incorporados. Um sistema de diálogo possui seis componentes básicos. (1) O componente de reconhecimento de fala que é responsável por traduzir a fala do usuário em texto. (2) O componente de entendimento de linguagem natural que produz uma representação semântica adequada para diálogos, normalmente utilizando gramáticas e ontologias. (3) O gerenciador de tarefa que escolhe os conceitos a serem expressos ao usuário. (4) O componente de geração de linguagem natural que define como expressar estes conceitos em palavras. (5) O gerenciador de diálogo controla a estrutura do diálogo. (6) O sintetizador de voz é responsável por traduzir a resposta do agente em fala. No entanto, não há consenso sobre os recursos necessários para desenvolver agentes conversacionais e a dificuldade envolvida nisso (especialmente em línguas com poucos recursos disponíveis). Este trabalho foca na influência dos componentes de linguagem natural (entendimento e gerência de diálogo) e analisa em especial o uso de sistemas de análise sintática (parser) como parte do desenvolvimento de agentes conversacionais com habilidades de linguagem mais flexível. Este trabalho analisa quais os recursos do analisador sintático contribuem para agentes conversacionais e aborda como os desenvolver, tendo como língua alvo o português (uma língua com poucos recursos disponíveis). Para isto, analisamos as abordagens de entendimento de linguagem natural e identificamos as abordagens de análise sintática que oferecem um bom desempenho. Baseados nesta análise, desenvolvemos um protótipo para avaliar o impacto do uso de analisador sintático em um agente conversacional. / Language is a mark of humanity and conscience, with the conversation (or dialogue) as one of the most fundamental manners of communication that we learn as children. Therefore one way to make a computer more attractive for interaction with users is through the use of natural language. Among the systems with some degree of language capabilities developed, the Eliza chatterbot is probably the first with a focus on dialogue. In order to make the interaction more interesting and useful to the user there are other approaches besides chatterbots, like conversational agents. These agents generally have, to some degree, properties like: a body (with cognitive states, including beliefs, desires and intentions or objectives); an interactive incorporation in the real or virtual world (including perception of events, communication, ability to manipulate the world and communicate with others); and behavior similar to a human (including affective abilities). This type of agents has been called by several terms, including animated agents or embedded conversational agents (ECA). A dialogue system has six basic components. (1) The speech recognition component is responsible for translating the user’s speech into text. (2) The Natural Language Understanding component produces a semantic representation suitable for dialogues, usually using grammars and ontologies. (3) The Task Manager chooses the concepts to be expressed to the user. (4) The Natural Language Generation component defines how to express these concepts in words. (5) The dialog manager controls the structure of the dialogue. (6) The synthesizer is responsible for translating the agents answer into speech. However, there is no consensus about the necessary resources for developing conversational agents and the difficulties involved (especially in resource-poor languages). This work focuses on the influence of natural language components (dialogue understander and manager) and analyses, in particular the use of parsing systems as part of developing conversational agents with more flexible language capabilities. This work analyses what kind of parsing resources contributes to conversational agents and discusses how to develop them targeting Portuguese, which is a resource-poor language. To do so we analyze approaches to the understanding of natural language, and identify parsing approaches that offer good performance, based on which we develop a prototype to evaluate the impact of using a parser in a conversational agent.

linguagem é uma marca da humanidade e da consciência, sendo a conversação (ou diálogo) uma das maneiras de comunicacão mais fundamentais que aprendemos quando crianças. Por isso uma forma de fazer um computador mais atrativo para interação com usuários é usando linguagem natural. Dos sistemas com algum grau de capacidade de linguagem desenvolvidos, o chatterbot Eliza é, provavelmente, o primeiro sistema com foco em diálogo. Com o objetivo de tornar a interação mais interessante e útil para o usuário há outras aplicações alem de chatterbots, como agentes conversacionais. Estes agentes geralmente possuem, em algum grau, propriedades como: corpo (com estados cognitivos, incluindo crenças, desejos e intenções ou objetivos); incorporação interativa no mundo real ou virtual (incluindo percepções de eventos, comunicação, habilidade de manipular o mundo e comunicar com outros agentes); e comportamento similar ao humano (incluindo habilidades afetivas). Este tipo de agente tem sido chamado de diversos nomes como agentes animados ou agentes conversacionais incorporados. Um sistema de diálogo possui seis componentes básicos. (1) O componente de reconhecimento de fala que é responsável por traduzir a fala do usuário em texto. (2) O componente de entendimento de linguagem natural que produz uma representação semântica adequada para diálogos, normalmente utilizando gramáticas e ontologias. (3) O gerenciador de tarefa que escolhe os conceitos a serem expressos ao usuário. (4) O componente de geração de linguagem natural que define como expressar estes conceitos em palavras. (5) O gerenciador de diálogo controla a estrutura do diálogo. (6) O sintetizador de voz é responsável por traduzir a resposta do agente em fala. No entanto, não há consenso sobre os recursos necessários para desenvolver agentes conversacionais e a dificuldade envolvida nisso (especialmente em línguas com poucos recursos disponíveis). Este trabalho foca na influência dos componentes de linguagem natural (entendimento e gerência de diálogo) e analisa em especial o uso de sistemas de análise sintática (parser) como parte do desenvolvimento de agentes conversacionais com habilidades de linguagem mais flexível. Este trabalho analisa quais os recursos do analisador sintático contribuem para agentes conversacionais e aborda como os desenvolver, tendo como língua alvo o português (uma língua com poucos recursos disponíveis). Para isto, analisamos as abordagens de entendimento de linguagem natural e identificamos as abordagens de análise sintática que oferecem um bom desempenho. Baseados nesta análise, desenvolvemos um protótipo para avaliar o impacto do uso de analisador sintático em um agente conversacional. / Language is a mark of humanity and conscience, with the conversation (or dialogue) as one of the most fundamental manners of communication that we learn as children. Therefore one way to make a computer more attractive for interaction with users is through the use of natural language. Among the systems with some degree of language capabilities developed, the Eliza chatterbot is probably the first with a focus on dialogue. In order to make the interaction more interesting and useful to the user there are other approaches besides chatterbots, like conversational agents. These agents generally have, to some degree, properties like: a body (with cognitive states, including beliefs, desires and intentions or objectives); an interactive incorporation in the real or virtual world (including perception of events, communication, ability to manipulate the world and communicate with others); and behavior similar to a human (including affective abilities). This type of agents has been called by several terms, including animated agents or embedded conversational agents (ECA). A dialogue system has six basic components. (1) The speech recognition component is responsible for translating the user’s speech into text. (2) The Natural Language Understanding component produces a semantic representation suitable for dialogues, usually using grammars and ontologies. (3) The Task Manager chooses the concepts to be expressed to the user. (4) The Natural Language Generation component defines how to express these concepts in words. (5) The dialog manager controls the structure of the dialogue. (6) The synthesizer is responsible for translating the agents answer into speech. However, there is no consensus about the necessary resources for developing conversational agents and the difficulties involved (especially in resource-poor languages). This work focuses on the influence of natural language components (dialogue understander and manager) and analyses, in particular the use of parsing systems as part of developing conversational agents with more flexible language capabilities. This work analyses what kind of parsing resources contributes to conversational agents and discusses how to develop them targeting Portuguese, which is a resource-poor language. To do so we analyze approaches to the understanding of natural language, and identify parsing approaches that offer good performance, based on which we develop a prototype to evaluate the impact of using a parser in a conversational agent.

This diploma thesis deals with the comparison of adjectives in Russian and English languages from a linguodidactic point of view. The theoretical part is based on the general linguistic knowledge of this particular part of speech and explains the rules for the comparison of adjectives in both languages. Furthermore, the theoretical part also provides linguodidactic context of acquiring this grammatical phenomenon. The practical part is devoted to the analysis of pedagogical documents and textbooks used for teaching Russian and English languages. The last chapter of the thesis shows the results of a research focused on testing pupils attending secondary schools. The aim here is to prove the knowledge of comparative and superlative forms of adjectives in Russian and English languages on the basis of a written test. KEY WORDS: adjectives, comparison, language teaching methodology, grammar acquisition of a foreign language, Russian language, English language, testing of pupils

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