Effectiveness of mobile learning across various settings

This paper reviews three ‘mobile learning’ projects to understand the nature of and extent to which learning is enhanced and facilitated by the inclusion of mobile technologies in the different teaching/learning activities that were carried out. Reviews will be taken from a number of projects; Mobile Learning in Informal Science Settings (MELISSA),Mobile Clinical Learning and Out There in Here (OTIH) projects. Melissa was a European project dealing with a range of learning systems. The Mobile Clinical Learning project investigated the potential of learning resources provided in Personal Digital Assistants (PDAs) and the ways in which clinical learning within two comparative health care institutions can be supported by using small handheld computers. OTIH is seeking to support collaborative remote experimentation where learners work together in different contexts. Within these projects a range of mobile devices (e.g. smartphones, laptops, ipads) were used to allow a broader understanding of a changing mobile device landscape. The research literature suggests that learning opportunities are more likely to arise in environments where interaction is facilitated. By reviewing these projects we are able to identify elements that are facilitated by mobile technologies and explore ways that learning is supported

Effect of Sequence of Simulated and Clinical Practicum Learning Experiences on Clinical Competency of Nursing Students

Two different sequences of blocks of simulated and clinical practicum learning experiences compared the clinical competency development of nursing students using a randomized crossover design. Competency was measured 3 times: after each block of simulated and clinical experiences and after a final simulated experience. No significant differences in competency scores between the 2 groups across the 3 time points were found. Using alternative models of clinical and simulation learning may help address barriers to the delivery of clinical education faced by schools of nursin

Developing clinical skill competency of undergraduate nursing students utilising a simulated psychomotor skill laboratory and model of self-directed learning : an evaluation research study : a thesis presented in partial fulfilment of the requirements for the degree of Master of Philosophy in Nursing at Massey University

Nursing education today emphasises higher-level thought processes than in the past. The requirement for Bachelor of Nursing students to also demonstrate competence in the core clinical skills is critical for safe professional practice. Balancing curricular emphases on technical knowledge, clinical and interpersonal skills, ethical decision-making, and other critical thinking skills is becoming increasingly difficult for nurse educators. Changes in the health sector have resulted in increased complexity of care, reduced numbers of venues for clinical practicum experiences, and increased financial costs associated with student practicum. The commitment to ensure that students have requisite clinical skills appropriate to each stage of their programme, prior to their clinical practicum involves curricular, pedagogical and financial considerations. Drawing on international literature and a Faculty committed to the development of nursing knowledge and skill, discovery, reflection and self-directed learning, the Eastern Institute of Technology (EIT) implemented the use of the Clinical Arts and Technology Centre and a cooperative model of self-directed learning into the Bachelor of Nursing curriculum in January 2000. The Clinical Arts and Technology Centre is an "enhanced" clinical simulation laboratory that provides students with the facilities and resources to support and enhance their knowledge and skills in preparation for clinical practicum. This Evaluation Research study explores and determines the effectiveness of the Clinical Arts and Technology Centre and the cooperative model of self-directed learning in terms of student clinical competency outcomes, and student satisfaction with the facility and model of self-directed learning. An extensive review of literature was undertaken in relation to the development and use of clinical simulation laboratories, clinical simulation, and models of self-directed learning in nursing education. A combination of qualitative and quantitative data collection methods were used including a pre piloted research questionnaire and a collation of student competency assessment outcomes. One hundred and fifty-six EIT Bachelor of Nursing students participated in the study. Statistical research findings and themes that emerged demonstrated a high level of overall student satisfaction with the facility resources and model of learning and provide direction for future facility and resource development, and ongoing quality improvement initiatives

Nurses as educators: creating teachable moments in practice

Effective workplace teaching is increasingly important in healthcare, with all staff being potential educators. The introduction of new roles and the need to create capacity for increased numbers of students can make it difficult to create a good learning experience. Despite the richness of clinical practice as a learning environment, creating capacity for teaching can be challenging. This article explores the possibilities for identifying and creating teachable moments in busy clinical environments and suggests a developmental model for incorporating these learning opportunities. Teachable moments linked directly to optimal patient care can potentially influence and shape a positive learning culture in clinical environments

Towards a New Science of a Clinical Data Intelligence

In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.Comment: NIPS 2013 Workshop: Machine Learning for Clinical Data Analysis and Healthcare, 201

Student Perceptions of the Clinical Education Environment

This Masters Project surveyed nursing clinical students at a University School of Nursing in the Pacific Northwest using a recently developed tool, the Student Evaluation of Clinical Education Environment (SECEE, version 3). Use of the SECEE (version 3) helped identify differences in student perceptions of various clinical learning environments. Results of nonparametric statistics were non-significant due to the small sample size; however there appeared to be consistent preference by students for clinicals at Magnet designated facilities. Additionally, higher instructor facilitation scores were also noted among students assigned to the university main campus (n = 31, M = 45.19, SD = 9.39) compared to students assigned to the distance campus (n = 9, M = 36.89, SD = 20.63). The findings have implications for nursing education, specifically the potential benefit of student learning at Magnet designated facilities and the importance of adequate support and engagement between university faculty and students in distance learning environments