A Typology of State Financial Aid Grant Programs Using Latent Class Analysis

Research in Higher Education - State financial aid grant programs are commonly categorized as either need-based, merit-based, or both, but their initial eligibility requirements include many more...     

A New Approach to Quality Assurance for Higher Education

This article describes the Engineering Professors' Conference (EPC) approach to quality assurance for Higher Education Institutions, which is currently the only formalized alternative to British Standard 5750 'Quality Systems'. The EPC approach is based on principles of quality assurance and Total Quality Management which have been developed in industry. These ideas are briefly outlined, and an opinion expressed on the interpretation and application of BSS7S0 for HE. The EPC model is explained, illustrated with example elements taken from the EPC Specification and Guidelines for Quality Assurance in Higher Education. A top-down approach to the development of an institutional quality system is described, based on a quality policy statement. Areas of activity which have an important impact on the quality of education are identified, emphasising the quality assurance requirements of academic departments. Supporting and administrative quality system requirements are also described, as these also play an important role in the quality of education. Formal quality procedures and documentation in key areas are proposed.     

A Corpus-Based Learning Method of Compound Noun Indexing Rules for Korean

In Korean information retrieval, compound nouns play an important role in improving precision in search experiments. There are two major approaches to compound noun indexing in Korean: statistical and linguistic. Each method, however, has its own shortcomings, such as limitations when indexing diverse types of compound nouns, over-generation of compound nouns, and data sparseness in training. In this paper, we propose a corpus-based learning method, which can index diverse types of compound nouns using rules automatically extracted from a large corpus. The automatic learning method is more portable and requires less human effort, although it exhibits a performance level similar to the manual-linguistic approach. We also present a new filtering method to solve the problems of compound noun over-generation and data sparseness.