Historically, English language arts educators have strongly disagreed about the role of grammar instruction in students’ literacy development (Weaver, 1996; Mulroy, 2003), and despite the importance of teachers’ beliefs and the continuing controversy over grammar instruction, few studies have explored teachers’ beliefs about the role of grammar instruction in English language arts education. The purpose of this qualitative, interpretive research was to investigate six middle school English language arts teachers’ beliefs and practices related to grammar and the teaching of grammar. Social constructivism (Fosnot & Perry, 2005) and phenomenology (Schutz, 1967; Seidman, 1998) served as theoretical frameworks for the study. Four questions guided the research: (1) What are teachers’ definitions of “grammar” as related to the teaching of English language arts? (2) What are teachers’ beliefs about “grammar” and the teaching of grammar in English language arts? (3) What are teachers’ reported sources of knowledge for grammar and the teaching of grammar in English language arts? (4) How does a professional development course on grammar instruction influence teachers’ beliefs? Data collection and analysis for this study occurred over a ten-month period. Data sources included an open-ended questionnaire; three in-depth, phenomenological interviews with each teacher (Seidman, 1998) before, during, and after the professional learning course; teacher artifacts and emails; field notes and transcriptions from videotaped course sessions; and a researcher’s log. Constant comparison (Glaser & Strauss, 1967) was used to analyze data, and richly descriptive participant portraits (Merriam & Assoc., 2002) report the findings. Trustworthiness and rigor have been established through adherence to guidelines for establishing credibility, confirmability, dependability, and transferability (Lincoln & Guba, 1985). The participants defined grammar in terms of rules, correctness, communication, and in relationships with various forms of literacy. They believed that students gain power through a mastery of Standard American English, grammar instruction is necessary to bolster students’ performance on standardized tests, and both traditional and innovative methods for teaching grammar are valuable. They found the collaborative professional learning course to be worthwhile and useful for developing innovative approaches to grammar instruction. Finally, they reported a need for more easily accessible Internet resources for teaching grammar.

The English subject in Swedish upper-secondary school aims to develop students’ holistic communicative ability, giving students opportunities to produce meaningful texts with confidence. The syllabus further proposes that this ability includes knowledge of the language’s grammatical structures since being aware of grammatical structures and options helps students to write in varied and effective ways. This prompts teachers to consider how to teach grammar to help improve students’ writing. Research, presented in this essay, shows that traditional grammar teaching with focus on rules and errors is ineffective and could rather make students shy away from grammar and writing. Instead, this essay suggests a playful and contextualised view of grammar instruction, developed by Constance Weaver, in which grammatical features are taught in conjunction with writing, enhancing texts and making them rhetorically efficient. Weaver’s approach to grammar includes presenting opportunities in which students can experiment with and explore ways to express themselves. This inspired the research question: what exercises can promote a playful attitude toward grammar to improve students’ writing? In order to investigate this question, three grammar and writing exercises were analysed with a criteria-based materials analysis. The criteria are based on research in the fields of English language learning, grammar instruction theory, rhetorical grammar theory and theory of playfulness. Results of the analysis suggest that the three exercises have the potential to promote playfulness toward grammar as well as improve students’ writing, as they could reduce anxiety and encourage risk-taking. However, teaching grammar with playful exercises may not be enough to benefit students: the overall course design and contingent teaching should promote a playful attitude.

We present an algorithm for deciding whether an arbitrary proper probabilistic context-free grammar is consistent, i.e., whether the probability that a derivation terminates is one. Our procedure has time complexity $\\\\mathcal O(n^3)$ in the unit-cost model of computation. Moreover, we develop a novel characterization of consistent probabilistic context-free grammars. A simple corollary of our result is that training methods for probabilistic context-free grammars that are based on maximum-likelihood estimation always yield consistent grammars.

Combinatory categorial grammar (CCG) is a mildly-context sensitive formalism that is well-established in computational linguistics. At the basis of the grammar are a lexicon and a rule system: The lexicon assigns syntactic categories to the symbols of a given input string, and the rule system specifies how adjacent categories can be combined, yielding a derivation tree whose nodes are labeled by categories. In this thesis, we focus on composition rules, which are present in all variants of the grammar. Vijay-Shanker and Weir famously show that CCG can generate the same class of string languages as tree-adjoining grammar, linear indexed grammar, and head grammar. Their equivalence proof relies on two particular features of the grammar: ε-entries, which are lexicon entries for the empty word, and rule restrictions, which allow to restrict the rule set on a per-grammar basis. However, modern variants of CCG tend to avoid these features. This raises the question how this changes the generative and computational power of CCG. Another important feature is the rule degree, which determines how complex a certain category involved in a rule application may be. The goal of this thesis is to shed light on the effects that changing these features has. When modeling natural language, one is not only interested in the acceptability of a sentence, but also in its underlying structure. Therefore, we study the sets of constituency trees that CCG can generate, which are obtained by relabeling sets of derivation trees. We first provide a new proof of an analogous result by Buszkowski, showing that when only application rules are allowed, a proper subset of regular tree languages can be generated by CCG. Then, we show that when composition of first degree is included, CCG can generate exactly the regular tree languages. On the other hand, pure CCG, which allows all rules up to some degree, is shown to not even generate all local tree languages. Our main result on the generative capacity of CCG is its strong equivalence to tree-adjoining grammar. This means that these formalisms can generate the same class of tree languages. This is even the case when only composition rules of second degree and no ε-entries are used, showing that a CCG with these properties already has its full expressive power. Our constructions also provide an effective procedure for the removal of ε-entries. Regarding computational complexity, ε-entries and high rule degrees are in fact problematic. Kuhlmann, Satta, and Jonsson studied the universal recognition problem for CCG, which asks whether some given string is generated by some given grammar, considering both as part of the input. They prove that this problem is EXPTIME-complete if ε-entries are included, and NP-complete if not. We refine this result and show that the runtime is exponential only in the maximum rule degree of the grammar. Hence, when the rule degree is bounded by a constant, parsing becomes polynomial in the grammar size. This also holds when substitution rules are included in the rule system.

This thesis considers the problem of assigning a sentence its syntactic structure, which may be discontinuous. It proposes a class of models based on probabilistic grammars that are obtained by the automatic refinement of a given grammar. Different strategies for parsing with a refined grammar are developed. The induction, refinement, and application of two types of grammars (linear context-free rewriting systems and hybrid grammars) are evaluated empirically on two German and one Dutch corpus.