Student experiences of the relationship between teaching and research consultancy: the case of a new university

The relationship between research and teaching in higher education has been the subject of much academic inquiry and research activity over the last decade and a half. The majority of these investigations have been conducted from the perspective of the academic teacher and researcher, but recently there has been a growth of interest in asking about the nature of the student learning experience in relation to research, and this study adds to what is known about the way students understand and experience (staff) research. Firstly, it may be argued that learning through teaching and research is the primary function of higher education. Secondly, the integration of research with teaching finds a resonance with the enhancement of learning through inquiry that it promotes. The rise in interest in academic scholarship an.d professional and pedagogic development has also promoted new approaches to academic work, where the division between research and teaching is seen as simplistic, and overlooking critical linkages. So the nexus is complex and not necessarily one-way, with teaching having an equal share in the balance. The research uses a mixed-method approach over two stages of data collection. Initially an electronic questionnaire survey is conducted to obtain an appropriate sample population of students and to determine the aspects of the student learning experience to be tested further in the subsequent smallgroup discussions. These discussion groups build on the questionnaire to explore the issues it raises, and allow students the chance to develop and articulate their experiences of and beliefs about, teaching and research. Nearly 200 students figure in the questionnaire survey and 17 are included in I the subsequent small-group discussions. There are both undergraduates and postgraduates at each stage of the data collection. The research takes place in a single new university and is the first to ask students explicitly about consultancy, seen as a complement to previous investigations specifically into research. From the research undertaken it can be concluded first that students are generally positive about research and consultancy. There are disciplinary differences in the findings which support the findings of previous studentcentred research, as well as variations between levels of study. lt is argued that the negative consequences of research and consultancy can be largely resolved through readdressing staff-student relationships and effective management of the relationship between teaching and research at departmental level. A model of student learning is proposed which responds to the main findings of this current research by reconceptualising the relationship between academic staff and students The relationship between research and teaching is central to this model

Automating Mission Scheduling for Space-Based Observatories

In this paper we describe the use of our planning and scheduling framework, HSTS, to reduce the complexity of science mission planning. This work is part of an overall project to enable a small team of scientists to control the operations of a spacecraft. The present process is highly labor intensive. Users (scientists and operators) rely on a non-codified understanding of the different spacecraft subsystems and of their operating constraints. They use a variety of software tools to support their decision making process. This paper considers the types of decision making that need to be supported/automated, the nature of the domain constraints and the capabilities needed to address them successfully, and the nature of external software systems with which the core planning/scheduling engine needs to interact. HSTS has been applied to science scheduling for EUVE and Cassini and is being adapted to support autonomous spacecraft operations in the New Millennium initiative

The CICT Earth Science Systems Analysis Model

Contents include the following: Computing Information and Communications Technology (CICT) Systems Analysis. Our modeling approach: a 3-part schematic investment model of technology change, impact assessment and prioritization. A whirlwind tour of our model. Lessons learned

The research-teaching nexus: A case study of students' awareness, experiences and perceptions of research

This paper presents a case study of students' awareness, experiences and perceptions of research in a 'new' university in the UK. The findings are based on a questionnaire of almost 200 students and five small group interviews. Many of the students participating in this research perceived clear benefits to their learning from staff research, including being taught by enthusiastic staff, enhanced staff credibility, and the reflected glory of being taught by well-known researchers. However, they also perceived disadvantages, particularly with regard to staff availability, and did not believe that staff research should take priority over their needs as learners. They recognised that their awareness of the nature of research and the development of research skills increased most when they were actively involved in undertaking research projects. Several students also perceived benefits for future employment from their participation in research activities. The questionnaire has been used by several other universities around the world to benchmark their practices. © 2010 Taylor & Francis

Student experiences of the relationship\ud between teaching\ud and research consultancy: the case of a new\ud university

The relationship between research and teaching in higher education has\ud been the subject of much academic inquiry and research activity over the last\ud decade and a half. The majority of these investigations have been conducted\ud from the perspective of the academic teacher and researcher, but recently\ud there has been a growth of interest in asking about the nature of the student\ud learning experience in relation to research, and this study adds to what is\ud known about the way students understand and experience (staff) research.\ud Firstly, it may be argued that learning through teaching and research is the\ud primary function of higher education. Secondly, the integration of research\ud with teaching finds a resonance with the enhancement of learning through\ud inquiry that it promotes. The rise in interest in academic scholarship an.d\ud professional and pedagogic development has also promoted new approaches\ud to academic work, where the division between research and teaching is seen\ud as simplistic, and overlooking critical linkages. So the nexus is complex and\ud not necessarily one-way, with teaching having an equal share in the balance.\ud The research uses a mixed-method approach over two stages of data\ud collection. Initially an electronic questionnaire survey is conducted to obtain\ud an appropriate sample population of students and to determine the aspects of\ud the student learning experience to be tested further in the subsequent smallgroup\ud discussions. These discussion groups build on the questionnaire to\ud explore the issues it raises, and allow students the chance to develop and\ud articulate their experiences of and beliefs about, teaching and research.\ud Nearly 200 students figure in the questionnaire survey and 17 are included in\ud I\ud the subsequent small-group discussions. There are both undergraduates and\ud postgraduates at each stage of the data collection. The research takes place\ud in a single new university and is the first to ask students explicitly about\ud consultancy, seen as a complement to previous investigations specifically into\ud research.\ud From the research undertaken it can be concluded first that students are\ud generally positive about research and consultancy. There are disciplinary\ud differences in the findings which support the findings of previous studentcentred\ud research, as well as variations between levels of study. lt is argued\ud that the negative consequences of research and consultancy can be largely\ud resolved through readdressing staff-student relationships and effective\ud management of the relationship between teaching and research at\ud departmental level. A model of student learning is proposed which responds\ud to the main findings of this current research by reconceptualising the\ud relationship between academic staff and students The relationship between\ud research and teaching is central to this model

Using Induction to Refine Information Retrieval Strategies

Conceptual information retrieval systems use structured document indices, domain knowledge and a set of heuristic retrieval strategies to match user queries with a set of indices describing the document's content. Such retrieval strategies increase the set of relevant documents retrieved (increase recall), but at the expense of returning additional irrelevant documents (decrease precision). Usually in conceptual information retrieval systems this tradeoff is managed by hand and with difficulty. This paper discusses ways of managing this tradeoff by the application of standard induction algorithms to refine the retrieval strategies in an engineering design domain. We gathered examples of query/retrieval pairs during the system's operation using feedback from a user on the retrieved information. We then fed these examples to the induction algorithm and generated decision trees that refine the existing set of retrieval strategies. We found that (1) induction improved the precision on a set of queries generated by another user, without a significant loss in recall, and (2) in an interactive mode, the decision trees pointed out flaws in the retrieval and indexing knowledge and suggested ways to refine the retrieval strategies. 1

Increasing levels of assistance in refinement of knowledge-based retrieval systems

This paper is concerned with the task of incrementally acquiring and refining the knowledge and algorithms of a knowledge-based system in order to improve its performance over time. In particular, we present the design of DE-KART, a tool whose goal is to provide increasing levels of assistance in acquiring and refining indexing and retrieval knowledge for a knowledge-based retrieval system. DE-KART starts with knowledge that has been entered manually, and increases its level of assistance in acquiring and refining that knowledge, both in terms of the increased level of automation in interacting with users, and in terms of the increased generality of the knowledge. DE-KART is at the intersection of machine learning and knowledge acquisition: it is a first step towards a system which moves along a continuum from interactive knowledge acquisition to increasingly automated machine learning as it acquires more knowledge and experience