Clinical assessment instruments validated for nursing practice in the Italian context: a systematic review of the literature

Aims. With the aim to identify the instruments validated for Italian nursing practice, a systematic review of the literature was undertaken.Results. A total of 101 instruments emerged. The majority (89; 88.1%) were developed in other countries; the remaining (14; 13.9%) were developed and validated in the Ital-ian context. The instruments were developed to measure patient’s problems (63/101; 62.4%), outcomes (27/101; 26.7%), risks (4/101; 4%) and others issues (7/101; 6.9%). The majority of participants involved in the validation processes were younger adults (49; 48.5%), older adults (40; 39.5%), children (4; 4%), adolescents (3; 3%), and children/adolescents (1; 1%). The instruments were structured primarily in the form of questionnaires (61; 60.4%), as a grid for direct observation (27; 26.7%) or in other forms (12; 11.9%). Among the 101 instruments emerged, there were 1 to 7 validation measures documented with on average 3.2 (95% CI 2.86-3.54) for each instrument.Conclusions. Developing validation studies giving priority to those instruments widely adopted in the clinical nursing practice is recommended.  

Semantic services in e-learning: an argumentation case study

This paper outlines an e-Learning services architecture offering semantic-based services to students and tutors, in particular ways to browse and obtain information through web services. Services could include registration, authentication, tutoring systems, smart question answering for students’ queries, automated marking systems and a student essay service. These services – which might be added incrementally to the portal – could be integrated with various ontologies such as ontologies of educational organisations, students and courses. In this paper, we describe a few scenarios in the e-learning domain and illustrate the role of a few services. We also describe in some detail a service doing semantic annotation of argumentation in student essays for allowing visualization of argumentation and providing useful feedback to student

Automatic extraction of knowledge from student essays

This paper presents a characterisation of argumentation in student essays and analyses patterns for extracting knowledge from them. Having analysed their complexity in light of the kinds of logic that may be used in an automatic argumentation extraction system, the main characteristic of these patterns appears to be the polymorphism of the pattern variables. Therefore, systems that learn patterns automatically ought to be able to generate many-sorted logic formulae, so that polymorphic types may be associated to the extraction slots (or – equivalently – to a Logic Formulae). An analysis of existing (pattern learning) systems was carried out to gauge the possibility of using them within our framework. However, we concluded that none of the existing systems can handle our requirements. Finally, we present our vision of an agent-based student portal as the front-end of a system that can locate argumentation links in a student essay and integrates with related educational services

Diagrammatic Representations of Online Discussions: Maximising Communication and Learning Potential By Supporting User Tasks Without Forcing Their Choice

Online discussions have been around for a quarter of a century (USENET) and have recently become more popular and ubiquitous thanks to newsgroup archives (e.g. Google ™ Groups) and the availability of web interfaces. E-learning initiatives (e.g. Ikarus 2004 Online Seminar) invariably include discussion components, due to the perceived importance of online discussions in e-learning. Compared to face-to-face meetings, asynchronous discussions have the advantages of convenient “any time, any place ” access, allowing the development of parallel discussions and providing permanent written records. Their main disadvantage is that of creating “overload ” in discussion participants (Erickson and Kellogg 2000, Jarrett et al. 2003, Newman 2002, Smith and Fiore 2001, Xiong and Donath 1999). In fact, they require users to carry out costly operations to “make sense of ” and track the current state of a discussion, whether this is a “new ” discussion (“overview ” task) or just new developments in a discussion they have previously participated in (“catch up ” task). It is known that external representations (ERs) such as diagrams play facilitatory roles in inference, problem-solving and understanding by reducing working memory load, serving as retrieval cues for long memory and promoting discovery and inference (Larking and Simon 1987, Suwa and Tversky 2002). ERs may thus help alleviate cognitive load in users of online discussions

Genre Analysis and the Automated Extraction of Arguments from

A full understanding of text is out of reach of current human language technology. However, a shallow Natural Language Processing (NLP) approach can be used to provide automated help in the assessment of essays: our approach uses genre, cue phrases and a set of patterns. Cue phrases, with their associated semantics, are used in conjunction with patterns to identify categories of argumentation partly derived from research in metadiscourse in the academic paper genre. In this paper, we describe an approach for automated extraction of arguments from student essays as a basis for their assessment in a formative as well as a summative sense. We introduce our own essay argumentation schema and show how we arrived at this categorisation. We also introduce “student essay viewer”, a tool that allows tutors and students to visualise argumentation in a student essay and may therefore be useful in aiding assessment and providing feedback to students

Analysing tutor feedback to students: first steps towards constructing an electronic monitoring system

Virtual Learning Environments provide the possibility of offering additional support to tutors, monitors and students in writing and grading essays and reports. They enable monitors to focus on the assignments that need most attention. This paper reports the findings from phase one of a feasibility study to assist the monitoring of student essays. It analyses tutor comments from electronically marked assignments and investigates how they match the mark awarded to each essay by the tutor. This involved carrying out a category analysis of the tutors' feedback to the students using Bales's 'interactional categories' as a theoretical basis. The advantage of this category system is that it distinguishes between task-orientated contributions, and the 'socio-emotive' element used by tutors to maintain student motivation. This reveals both how the tutor makes recommendations to improve the assignment content, and how they provide emotional support to students. Bales's analysis was presented to a group of tutors who felt an electronic feedback system based on this model would help them to get the right balance of responses to their students. These findings provide a modest start to designing a model of feedback for tutors of distance education students. Future work will entail refining these categories and testing this model with a larger sample from a different subject domain

An Agent-Based Approach to Mailing List Knowledge Management

The widespread use of computers and of the internet have brought about human information overload, particularly in the areas of internet searches and email management. This has made Knowledge Management a necessity, particularly in a business context. Agent technology -- with its metaphor of agent as assistant -- has shown promise in the area of information overload and is therefore a good candidate for Knowledge Management solutions. This paper illustrates a mailing list Knowledge Management tool that is centred around the concept of a mailing list assistant. We envisage this system as the first step towards a comprehensive agentbased Knowledge Management solution

Genre analysis and the automated extraction of arguments from student essays

Genre analysis and the automated extraction of arguments from student essay

MnM: semi-automatic ontology population from text

Ontologies can play a very important role in information systems. They can support various information system processes, particularly information acquisition and integration. Ontologies themselves need to be designed, built and maintained. An important part of the ontology engineering cycle is the ability to keep a handcrafted ontology up to date. Therefore, we have developed a tool called MnM that helps during the ontology maintenance process. MnM extracts information from texts and populates an ontology. It uses NLP (Natural Language Processing), Information Extraction and Machine Learning technologies. In particular, MnM was tested using an electronic newsletter consisting of news articles describing events happening in the Knowledge Media Institute (KMi). MnM could constitute an important part of an ontology-driven information system, with its integrated web-based ontology editor and provision of open APIs to link to ontology servers and to integrate with information extraction tools

Automating information processing tasks: an agent-based architecture

This paper describes an agent-based architecture designed to provide automation support for users who perform information processing tasks using a collection of distributed and disparate software tools and on-line resources. The architecture extends previous work on agent-based software interoperability. The unique features of the information processing domain compared to distributed information retrieval are discussed and a novel extension of hierarchical task network (HTN) planning to support this domain is presented.Unpublished[1] M. R. Genesereth and S. P. Ketchpel. Software agents. Communications of the ACM, 37(7):48–53, July 1994. [2] Foundation for Intelligent Physical Agents homepage. http://drogo.cselt.stet.it/fipa/, 1998. [3] FIPA 97 specification documents. http://drogo.cselt.stet.it/fipa/spec/fipa97/fipa97.htm, 1997. [4] S. J. S. Cranefield and M. K. Purvis. Agent-based integration of general-purpose tools. In Proceedings of the Workshop on Intelligent Information Agents, Fourth International Conference on Information and Knowledge Management, December 1995. [5] S. J. S. Cranefield and M. K. Purvis. An agent-based architecture for software tool coordination. In L. Cavedon, A.S. Rao, and W. Wobcke, editors, Intelligent Agent Systems: Theoretical and Practical Issues, number 1209 in Lecture Notes in Artificial Intelligence, pages 44–58. Springer, 1997. [6] A. C. Díaz, S.J.S. Cranefield, and M. K. Purvis. Planning and matchmaking in a multi-agent system for software integration. Mathematical Modelling and Scientific Computing, 8, 1997. [7] D. Kuokka and L. Harada. Matchmaking for information agents. In Proceedings of the 14th International Joint Conference on Artificial Intelligence, volume 1, pages 672–678, 1995. [8] Amzi! Inc. WWW home page. http://www.amzi.com/. [9] Java beans specification. http://java.sun.com/beans/docs/spec.html. [10] JATLite Web pages, Center for Design Research, Stanford University. http://java.stanford.edu/, 1997. [11] Knowledge Interchange Format specification. Working Draft, ANSI X3T2 Ad Hoc Group on KIF, March 1995. http://logic.stanford.edu/kif/specification.html. [12] S. Kambhampati. A comparative analysis of partial order planning and task reduction planning. SIGART Bulletin, 6(1):16–25, 1995. [13] URC working web, Advanced Computing Laboratory, Los Alamos National Laboratory. http://www.acl.lanl.gov/URC/, November 1995. [14] J. Ambros-Ingerson and S. Steel. Integrating planning, execution and monitoring. In Proceedings of the 7th National Conference on Artificial Intelligence (AAAI-88), pages 735–740, 1988. [15] P.J. Hayes. The frame problem and related problems in artificial intelligence. In J.E. Allen, J. Hendler, and A. Tate, editors, Readings in Planning, pages 588–595. Morgan Kaufmann, 1990. [16] G. Wiederhold, editor. Intelligent Integration of Information. Kluwer Academic Publishers, 1996. (a special double issue of the Journal of Intelligent Information Systems, vol. 6(2–3), June 1996). [17] M. H. Huhns and M. P. Singh, editors. Readings in Agents. Morgan Kaufmann, 1998. [18] K. Golden, O. Etzioni, and D. Weld. Omnipotence without omniscience: Efficient sensor management for planning. In Proceedings of the 12th National Conference on Artificial Intelligence (AAAI-94), pages 1048–1054, 1994. [19] C. A. Knoblock. Planning, executing, sensing, and replanning for information gathering. In Proceedings of the 14th International Joint Conference on Artificial Intelligence, volume 2, pages 1686–1693, 1995. [20] C. Kwok and D. Weld. Planning to gather information. In Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-96), 1996. [21] M. Williamson, K. Decker, and K. Sycara. Unified information and control flow in hierarchical task networks. In Proceedings of the AAAI-96 Workshop on Theories of Planning, Action, and Control, 1996. [22] C. A. Knoblock and J. L. Ambite. Agents for information gathering. In J. Bradshaw, editor, Software Agents. AAAI/MIT Press, 1997