Dataset Information

Innovative Assessment That Combines Collaborative and Self-Directed Learning With Integration and Application of Knowledge: Teamwork Group Projects.

ABSTRACT:

Introduction

There is a worldwide focus on the early development of collaborative skills in medical students as reflected in the design of the medicine program at the University of New South Wales, Australia. Integral to the success of student-centered curricula, is early development of students' self-directed and collaborative learning skills. The purpose of this innovative assessment is to develop and assess students' skills in self-directed and collaborative learning while they concurrently engage with stage-appropriate content knowledge.

Methods

The educational design of the group projects allows junior medical students to work collaboratively to develop a deep understanding of the concepts and principles of a clinical scenario. Students are required to integrate and apply knowledge from different disciplines and share their learning with a wider peer group through appropriate peer teaching strategies. Two variants of these group projects are described in this resource, and generic versions of student and assessor instructions are included as Appendices A and B.

Results

Feedback on the projects collected over the last 7 years has been positive. Students begin to see the relevance and benefits of learning together and appreciate the impact this has on the quality of their learning. They also begin to appreciate the relevance of collaborative skills to their future practice as doctors.

Discussion

The group projects are based on well-established educational principles, and the templates provided in the appendices can be adapted by other medical educators.

SUBMITTER: Balasooriya C

PROVIDER: S-EPMC6464407 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Publications

Innovative Assessment That Combines Collaborative and Self-Directed Learning With Integration and Application of Knowledge: Teamwork Group Projects.

Balasooriya Chinthaka C Olupeliyawa Asela A Iqbal Maha Pervaz MP

MedEdPORTAL : the journal of teaching and learning resources 20160916

<h4>Introduction</h4>There is a worldwide focus on the early development of collaborative skills in medical students as reflected in the design of the medicine program at the University of New South Wales, Australia. Integral to the success of student-centered curricula, is early development of students' self-directed and collaborative learning skills. The purpose of this innovative assessment is to develop and assess students' skills in self-directed and collaborative learning while they concur ...[more]

PMID: 31008230

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Project description:BackgroundActive engagement in research by healthcare organisations and clinicians is associated with improvements in healthcare performance. Barriers to research engagement by clinician allied health (AH) professionals include competing priorities from high clinical workloads, lack of research skills and confidence, and lack of supportive research relationships. Collaboration with universities on joint clinical research projects is well recognised as a means of building health service research capacity. Research projects undertaken by students as part of their qualifying degree represent one such opportunity. However, there are few reports evaluating these collaborations from the health service perspective.MethodsA qualitative study using semi-structured interviews and thematic analysis to explore the experiences of AH professionals in the co-supervision of students completing research placements as part of their professional degree course.ResultsFourteen health service employees from six allied health disciplines described collaborations on research projects with 24 students from four different universities. Student placements and projects varied widely in length of placement, extent of collaboration, supervision structure and study design. Three overarching themes were identified in the AH professional co-supervision experience: 1) Professional growth; 2) Mismatch with expectations; and 3) Focus on the student. Project outcomes were categorised from the health system perspective. These were 1) Healthcare performance improvements, including local increases in staff clinical practice knowledge and wider contributions to the evidence base; 2) Research capacity gains within the health service, including research knowledge and skill development, collaborative linkages and opportunity for future research; and 3) Staff-centred outcomes including increased job satisfaction.ConclusionsThis study demonstrates the potential for AH professional supervision of students on research placements to contribute to healthcare performance improvements and research capacity gains within health services, alongside providing personal benefits for the AH professionals involved. Early consultation with a health service-employed research specialist may support health professional and student learning, team collaboration and project coordination for these student projects.

Project description:The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems.

Project description:BackgroundGetting research into policy and practice in healthcare is a recognised, world-wide concern. As an attempt to bridge the gap between research and practice, research funders are requesting more interdisciplinary and collaborative research, while actual experiences of such processes have been less studied. Accordingly, the purpose of this study was to gain more knowledge on the interdisciplinary, collaborative and partnership research process by investigating researchers' experiences of and approaches to the process, based on their participation in an inventive national research programme. The programme aimed to boost collaborative and partnership research and build learning structures, while improving ways to lead, manage and develop practices in Swedish health and social services.MethodsInterviews conducted with project leaders and/or lead researchers and documentation from 20 projects were analysed using directed and conventional content analysis.ResultsCollaborative approaches were achieved by design, e.g. action research, or by involving practitioners from several levels of the healthcare system in various parts of the research process. The use of dual roles as researcher/clinician or practitioner/PhD student or the use of education designed especially for practitioners or 'student researchers' were other approaches. The collaborative process constituted the area for the main lessons learned as well as the main problems. Difficulties concerned handling complexity and conflicts between different expectations and demands in the practitioner's and researcher's contexts, and dealing with human resource issues and group interactions when forming collaborative and interdisciplinary research teams. The handling of such challenges required time, resources, knowledge, interactive learning and skilled project management.ConclusionsCollaborative approaches are important in the study of complex phenomena. Results from this study show that allocated time, arenas for interactions and skills in project management and communication are needed during research collaboration to ensure support and build trust and understanding with involved practitioners at several levels in the healthcare system. For researchers, dealing with this complexity takes time and energy from the scientific process. For practitioners, this puts demands on understanding a research process and how it fits with on-going organisational agendas and activities and allocating time. Some of the identified factors may be overlooked by funders and involved stakeholders when designing, performing and evaluating interdisciplinary, collaborative and partnership research.

Dataset Information

Innovative Assessment That Combines Collaborative and Self-Directed Learning With Integration and Application of Knowledge: Teamwork Group Projects.

Introduction

Methods

Results

Discussion

Publications

Innovative Assessment That Combines Collaborative and Self-Directed Learning With Integration and Application of Knowledge: Teamwork Group Projects.

Similar Datasets

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