Is it RIP for the IEP? The future of individual education plans in an era of accountability

This article presents a brief overview of the development of the Individual Education Plan (IEP) and prompts teachers to question its use and relevance in an era of accountability in Australian schools. Many Australian teachers do not realise that the IEP was adopted from the United States where is was legislated practice based on that country's Human Rights Legislation. It is not included in the Australian policy context. Though not embedded in the legislation of many other countries, it became a process and a product synonymous with the education of students with disability worldwide. In the era of standards-based education and curriculum for all, the relevance of the IEP process and product has been questioned or re-imaged in some Australian schools. The story of one school leader, Violet, is presented here as an example.

Beyond competencies : using a capability framework in developing practice standards for advanced practice nursing

AIM This paper presents a discussion on the application of a capability framework for advanced practice nursing standards/competencies. BACKGROUND There is acceptance that competencies are useful and necessary for definition and education of practice-based professions. Competencies have been described as appropriate for practice in stable environments with familiar problems. Increasingly competencies are being designed for use in the health sector for advanced practice such as the nurse practitioner role. Nurse practitioners work in environments and roles that are dynamic and unpredictable necessitating attributes and skills to practice at advanced and extended levels in both familiar and unfamiliar clinical situations. Capability has been described as the combination of skills, knowledge, values and self-esteem which enables individuals to manage change, be flexible and move beyond competency. DESIGN A discussion paper exploring 'capability' as a framework for advanced nursing practice standards. DATA SOURCES Data were sourced from electronic databases as described in the background section. IMPLICATIONS FOR NURSING As advanced practice nursing becomes more established and formalized, novel ways of teaching and assessing the practice of experienced clinicians beyond competency are imperative for the changing context of health services. CONCLUSION Leading researchers into capability in health care state that traditional education and training in health disciplines concentrates mainly on developing competence. To ensure that healthcare delivery keeps pace with increasing demand and a continuously changing context there is a need to embrace capability as a framework for advanced practice and education.

A stakeholder analysis of one institution’s assuring learning experience – is the promise and the practice worth the price?

Universities around the world are rushing to implement assurance of learning policies and practices with varying degrees of success. One School investigated its own policy and practice development through the eyes of its key stakeholders to identify whether the practice was worth the price. Findings indicate that although the key stakeholders considered different needs and viewed their experiences differently, value did abound and was in the eye of the beholder.

Relevance feature discovery for text mining

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of large scale terms and data patterns. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, there has been often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences; yet, how to effectively use large scale patterns remains a hard problem in text mining. To make a breakthrough in this challenging issue, this paper presents an innovative model for relevance feature discovery. It discovers both positive and negative patterns in text documents as higher level features and deploys them over low-level features (terms). It also classifies terms into categories and updates term weights based on their specificity and their distributions in patterns. Substantial experiments using this model on RCV1, TREC topics and Reuters-21578 show that the proposed model significantly outperforms both the state-of-the-art term-based methods and the pattern based methods.