This paper describes the development of the AntConc corpus analysis toolkit, originally designed for use in a technical writing course at Osaka University, Japan, but now adopted in institutions throughout the world as an easy-to-use, freeware, multiplatform alternative to the many commercial concordance programs. First, I will explain how the software was originally tailored to the needs of students in the Osaka writing course and later to a general audience through the requests and feedback from teachers and students around the world. Then, I will give an overview of tools in the most recent version of AntConc and explain their value using examples from the classroom. Finally, I will discuss some of the software's limitations and future developments, and suggest applications in professional communication

When faced with the tasks of reading and writing a complex technical paper, many nonnative scientists and engineers who have a solid background in English grammar and vocabulary lack an adequate knowledge of commonly used structural patterns at the discourse level. In this paper, we propose a novel computer software tool that can assist these people in the understanding and construction of technical papers, by automatically identifying the structure of writing in different fields and disciplines. The system is tested using research article abstracts and is shown to be a fast, accurate, and useful aid in the reading and writing process.

Previous researchers have given conflicting views as to what makes a "good" research article (RA) title. In this paper, characteristic features of research article titles, including length, punctuation usage, word frequency, and preposition usage are investigated using a corpus of 600 research articles from the six journals of the IEEE Computer Society. Results show, while some of the intuitive observations made in the literature about title writing are accurate for computer science journals, other observations have ignored the effects of discipline and field variation. Subsequently, these observations are either unjustified or misleading.

A standard model for describing the structure of research article introductions, the CARS (Create A Research Space) model, is evaluated in terms of how well it can be applied to 12 articles which have received "best paper" awards in the field of software engineering. The results indicate that, although the model adequately describes the main framework of the introductions, a number of important features are not accounted for, in particular: an extensive review of background literature, the inclusion of many definitions and examples, and an evaluation of the research in terms of application or novelty of the results.