Search results

The Bryant University Mathematics Department has been collecting math placement scores and admissions data for all incoming freshmen for many years. In the past, the authors have used these data mainly for placement in first-year classes and more recently to invite the most mathematically talented students to become mathematics majors. The purpose of this paper is to use the same data source to predict persistence in declared majors for all incoming students.

In order to categorize the students, the authors use cluster analysis, one of the tools of data mining, to see if students in particular majors share similar strengths based on the available data. The authors follow up this analysis by running a multivariate analysis of variance (MANOVA) to confirm that the means of the clusters are significantly different.

The cluster analysis resulted in five distinct clusters, which were confirmed by the results of the MANOVA. The authors also found how many students in each cluster persisted in their chosen major.

These results will help to improve counseling and proper placement of incoming freshmen. They will also be helpful in long-range planning of upper-level courses. Retention of students in their majors is an important concern for colleges and universities as it relates to planning issues, such as scheduling classes, particularly for upper classmen. This could also affect departmental requirements, such as the size of the faculty.

This article summarises what the Department of Health's (2005) Delivering Race Equality (DRE) agenda in mental health services set out to achieve and the background to this. The article then provides commentary on the Central and North West London NHS Foundation Trust's experiences while acting as one of the 18 focused implementation sites (FIS) created as part of the Department of Health's five‐year Delivering Race Equality Action Plan and highlights the recommendations that developed out of this work and have national application.

Purpose — We assert that researchers developing new web interaction tools should consider an array of user motives beyond query-based information retrieval. This chapter reports on two probes used to investigate user activities that go beyond search as traditionally conceived.

Design/methodology — This chapter reviews research on user experiences with search engines and general web use. It then describes the design and case study of cards and pebbles, two search engine-based probes developed to help elicit new concepts for web-based experiences.

Findings — Participants reflect on their experiences with the probes and offer ideas regarding how to incrementally shift the traditional search paradigm and conceive of the web in new ways.

Implications/value — This investigation serves as a starting point by offering criteria that should be considered when designing new ‘beyond search’ tools.

Purpose — The purpose of this chapter is to give an overview of the context of Web search and search engine related research, as well as to introduce the reader to the sections and chapters of the book.

Methodology/approach — We review literature dealing with various aspects of search engines, with special emphasis on emerging areas of Web searching, search engine evaluation going beyond traditional methods and new perspectives on Web searching.

Findings — The approaches to studying Web search engines are manifold. Given the importance of Web search engines for knowledge acquisition, research from different perspectives needs to be integrated into a more cohesive perspective.

Research limitations/implications — The chapter suggests a basis for research in the field and also introduces further research directions.

Originality/value of paper — The chapter gives a concise overview of the topics dealt within the book and also shows directions for researchers interested in Web search engines.