Understanding teacher collaboration in disadvantaged urban primary schools: uncovering practices that foster professional learning communities

This study is set in the context of disadvantaged urban primary schools in Ireland. It inquires into the collaborative practices of primary teachers exploring how class teachers and support teachers develop ways of working together in an effort to improve the literacy and numeracy levels of their student. Traditionally teachers have worked in isolation and therefore ‘collaboration’ as a practice has been slow to permeate the historically embedded assumption of how a teacher should work. This study aims to answer the following questions. 1). What are the dynamics of teacher collaboration in disadvantaged urban primary schools? 2). In what ways are teacher collaboration and teacher learning related? 3). In what ways does teacher collaboration influence students’ opportunities for learning? In answering these research questions, this study aims to contribute to the body of knowledge pertaining to teacher learning through collaboration. Though current policy and literature advocate and make a case for the development of collaborative teaching practices, key studies have identified gaps in the research literature in relation to the impact of teacher collaboration in schools. This study seeks to address some of those gaps by establishing how schools develop a collaborative environment and how teaching practices are enacted in such a setting. It seeks to determine what skills, relationships, structures and conditions are most important in developing collaborative environments that foster the development of professional learning communities (PLCs). This study uses a mixed method research design involving a postal survey, four snap-shot case studies and one in depth case study in an effort to establish if collaborative practice is a feasible practice resulting in worthwhile benefits for both teachers and students.

Practical programming for static average-case analysis: the MOQA investigation

This work considers the static calculation of a program’s average-case time. The number of systems that currently tackle this research problem is quite small due to the difficulties inherent in average-case analysis. While each of these systems make a pertinent contribution, and are individually discussed in this work, only one of them forms the basis of this research. That particular system is known as MOQA. The MOQA system consists of the MOQA language and the MOQA static analysis tool. Its technique for statically determining average-case behaviour centres on maintaining strict control over both the data structure type and the labeling distribution. This research develops and evaluates the MOQA language implementation, and adds to the functions already available in this language. Furthermore, the theory that backs MOQA is generalised and the range of data structures for which the MOQA static analysis tool can determine average-case behaviour is increased. Also, some of the MOQA applications and extensions suggested in other works are logically examined here. For example, the accuracy of classifying the MOQA language as reversible is investigated, along with the feasibility of incorporating duplicate labels into the MOQA theory. Finally, the analyses that take place during the course of this research reveal some of the MOQA strengths and weaknesses. This thesis aims to be pragmatic when evaluating the current MOQA theory, the advancements set forth in the following work and the benefits of MOQA when compared to similar systems. Succinctly, this work’s significant expansion of the MOQA theory is accompanied by a realistic assessment of MOQA’s accomplishments and a serious deliberation of the opportunities available to MOQA in the future.