Co-creation of a student-implemented allied health service in a First Nations remote community of East Arnhem Land, Australia

Objectives: To co-create a culturally responsive student-implemented allied health service in a First Nations remote community and to determine the feasibility and acceptability of the service. Design: Co-creation involved a pragmatic iterative process, based on participatory action research approaches. Feasibility and acceptability were determined using a mixed-method pre/postdesign. Setting: The service was in Nhulunbuy, Yirrkala and surrounding remote First Nations communities of East Arnhem Land, Northern Territory, Australia. Participants: Co-creation of the service was facilitated by the Northern Australia Research Network, guided by Indigenous Allied Health Australia leadership, with East Arnhem local community organisations and community members. Co-creation of the day-to-day service model involved local cultural consultants, service users and their families, staff of community organisations, students, supervisors, placement coordinators and a site administrator. Findings: A reciprocal learning service model was co-created in which culturally responsive practice was embedded. The service was feasible and acceptable: it was delivered as intended; resources were adequate; the service management system was workable; and the service was acceptable. Health outcome measures, however, were not appropriate to demonstrate impact, particularly through the lens of the people of East Arnhem. Recommendations for the service included: continuing the reciprocal learning service model in the long term; expanding to include all age groups; and connecting with visiting and community-based services. Conclusion: The co-created service was feasible and acceptable. To demonstrate the impact of the service, measures of health service impact that are important to First Nations people living in remote communities of northern Australia are required

The Faculty Notebook, September 1999

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost

Strategic problem-solving: A state of the art

Strategic problem-solving is a relevant skill in business, widely used to identify problems and find inherent solutions to stop, avoid, or mitigate such problems. The literature revolving around problem-solving has been enriched over the years with several theories and approaches. Problem-solving is critical in helping maintain a successful business and looking at problems as objectively and modestly as possible. This systematic literature review aims to summarize the current state of the art on the topic of strategic problem-solving. To this end, a bibliometric analysis based on data retrieved from the Web of Science database is performed, and results are reported in this article. The analysis allowed us to identify five different clusters on the theme of problem-solving, namely, product development and open innovation, organization and firm-customer relationship, creative process and resilience, learning, skills, and work environment, and partnership negotiation/cooperation and the role of supply chain and quality management. These clusters are distinct yet complementary to each other, a trait that was possible to observe when common top papers from each cluster were selected for further discussion. Finally, a shift in the topics of research from past to present was observed which might be related to the emergence of new theories and the turnover of authors. The growing number of recent publications reveals the value of this article and suggests that problem-solving will always have room for improvement.info:eu-repo/semantics/acceptedVersio

Concept mapping: A dynamic, individualized and qualitative method for eliciting meaning

The purpose of this theoretical article is to explore the use of concept mapping as a qualitative research method that is represented as a form of multimodal communication. This framework strives to move mapping beyond quantitative analysis by inserting art and humanness into the process. This proposed framework provides a means to highlight the ways in which people learn, understand, and interpret the world around them. Three categories for understanding have been identified by the authors to help individuals create, interpret, and understand qualitative concept maps. These categories include the following: Voice: Tri-directional Voice and Mutual Absorption; Detail in the Parts & Recognition of the Whole: Uniqueness, Aesthetic Distance and Emplacement; and Sensory Experience: Intellectual + Emotional Investment and Humanness. Each of these categories is interconnected, and informs each other in a dialectical way, therefore creating a piece of visual data with which the participant, researcher and audience can interact

Architecture handbook 2006

2006 handbook for the faculty of Architectur

Architecture handbook 2006

2006 handbook for the faculty of Architectur

Thrive: Success Strategies for the Modern-Day Faculty Member

The THRIVE collection is intended to help faculty thrive in their roles as educators, scholars, researchers, and clinicians. Each section contains a variety of thought-provoking topics that are designed to be easily digested, guide personal reflection, and put into action. Please use the THRIVE collection to help: Individuals study topics on their own, whenever and wherever they want Peer-mentoring or other learning communities study topics in small groups Leaders and planners strategically insert faculty development into existing meetings Faculty identify campus experts for additional learning, grand rounds, etc. If you have questions or want additional information on a topic, simply contact the article author or email [email protected]://digitalcommons.unmc.edu/facdev_books/1000/thumbnail.jp

Content Recommendation Through Linked Data

Nowadays, people can easily obtain a huge amount of information from the Web, but often they have no criteria to discern it. This issue is known as information overload. Recommender systems are software tools to suggest interesting items to users and can help them to deal with a vast amount of information. Linked Data is a set of best practices to publish data on the Web, and it is the basis of the Web of Data, an interconnected global dataspace. This thesis discusses how to discover information useful for the user from the vast amount of structured data, and notably Linked Data available on the Web. The work addresses this issue by considering three research questions: how to exploit existing relationships between resources published on the Web to provide recommendations to users; how to represent the user and his context to generate better recommendations for the current situation; and how to effectively visualize the recommended resources and their relationships. To address the first question, the thesis proposes a new algorithm based on Linked Data which exploits existing relationships between resources to recommend related resources. The algorithm was integrated into a framework to deploy and evaluate Linked Data based recommendation algorithms. In fact, a related problem is how to compare them and how to evaluate their performance when applied to a given dataset. The user evaluation showed that our algorithm improves the rate of new recommendations, while maintaining a satisfying prediction accuracy. To represent the user and their context, this thesis presents the Recommender System Context ontology, which is exploited in a new context-aware approach that can be used with existing recommendation algorithms. The evaluation showed that this method can significantly improve the prediction accuracy. As regards the problem of effectively visualizing the recommended resources and their relationships, this thesis proposes a visualization framework for DBpedia (the Linked Data version of Wikipedia) and mobile devices, which is designed to be extended to other datasets. In summary, this thesis shows how it is possible to exploit structured data available on the Web to recommend useful resources to users. Linked Data were successfully exploited in recommender systems. Various proposed approaches were implemented and applied to use cases of Telecom Italia