LC-REHAB : randomised trial assessing the effect of a new patient education method - learning and coping strategies - in cardiac rehabilitation

Due to improved treatments and ageing population, many countries now report increasing prevalence in rates of ischemic heart disease and heart failure. Cardiac rehabilitation has potential to reduce morbidity and mortality, but not all patients complete. In light of favourable effects of cardiac rehabilitation it is important to develop patient education methods which can enhance adherence to this effective program. The LC-REHAB study aims to compare the effect of a new patient education strategy in cardiac rehabilitation called 'learning and coping' to that of standard care. Further, this paper aims to describe the theoretical basis and details of this intervention.

Transfer learning using the online FMM model

In this paper, we present an analysis on transfer learning using the Fuzzy Min-Max (FMM) neural network with an online learning strategy. Transfer learning leverages information from the source domain in solving problems in the target domain. Using the online FMM model, the data samples are trained one at a time. In order to evaluate the online FMM model, a transfer learning data set, based on data samples collected from real landmines, is used. The experimental results of FMM are analyzed and compared with those from other methods in the literature. The outcomes indicate that the online FMM model is effective for undertaking transfer learning tasks.

Managing learning evidence using eportfolio

This paper introduces ePortfolio and its use of managing learning evidence in an eLearning environment. The paper uses the outcomes of a recent project sponsored by Deakin University, Australia and examples from IT teaching practice based on CloudDeakin to explore how ePortfolios add value to personalized and reflective models of eLearning. ePortfolios are proved to be an effective tool for discussion, information collection and reflection, and new ways of thinking about learning evidence management.

Barriers and enablers to learning during team-based clinical simulations: reflective interviews with final year undergraduate nursing students

Background: Contemporary approaches to clinical simulation can enhance educational outcomes. However, simulation approaches do have limitations with possible compromises for learning and teaching. This paper aims to identify barriers
and enablers to learning in simulated clinical settings.
Methods: A generic qualitative design was applied. Semi-structured group video debriefing interviews were held with Australian final-year nursing students who completed three patient deterioration scenarios with a standardized patient.
Audio-recorded interviews were transcribed and analysed to identify emergent themes.
Results: Interviews with 15 teams of three students (n = 45) from three universities were analysed. Learning enablers were ‘Realism of the simulated environment’; ‘Practicing: we should do this at uni’; ‘Learning from reflection and expert feedback’, and ‘How to become competent: know the gaps’. Barriers to learning included ‘Increased stress from inexperience; ‘Expectations when pretending’ and ‘Lack of assistance’. Skills practice in team-based settings with applicable reflection and debriefing was regarded as beneficial. Simulated patients enhanced fidelity but were unable to replicate actual clinical signs. High stress levels were perceived as a barrier to learning.
Conclusions: Applicably designed high fidelity simulations with video-based reflective review offer repeated rehearsal of clinical situations to enable learning. This educational strategy may reduce the time it takes undergraduate students to
reach competency.

An online transfer learning RBF neural network for cross domain data classification

In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks. © 2014 The authors and IOS Press. All rights reserved.

Using iTextbook as an alternate frontend to learning management systems

Learning management systems (LMS) have been a popular tool for delivery of learning content as well as the management of learners and courses. In recent years, the ubiquity of mobile devices such as smartphones and tablets has seen the increased popularity of using them to consume eBooks. While the LMS is popular among administrators, accessing content on mobile devices appear to be the preference of our learners. Furthermore, there are reports on a number of shortcomings with learners using the LMS, e.g., the experience of using LMSes on mobile devices falling short and learners are less engaged interacting with the LMS than with their mobile devices, etc. In this paper, we investigate the idea of using eBooks as an alternative frontend for learners to interact with the LMS. A proof of concept eBook was developed for a data management course to showcase how content on the LMS can be deployed via the eBook interface while connecting our learners to the LMS for learning management. We find that this approach delivers a rich and immersive experience to our learners, as they would expect from their devices. The outcomes also gave us food for thought regarding how LMSes may evolve in the future.

Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models

In this paper, two real-world medical classification problems using electrocardiogram (ECG) and auscultatory blood pressure (Korotkoff) signals are examined. A total of nine machine learning models are applied to perform classification of the medical data sets. A number of useful performance metrics which include accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve are computed. In addition to the original data sets, noisy data sets are generated to evaluate the robustness of the classifiers against noise. The 10-fold cross validation method is used to compute the performance statistics, in order to ensure statistically reliable results pertaining to classification of the ECG and Korotkoff signals are produced. The outcomes indicate that while logistic regression models perform the best with the original data set, ensemble machine learning models achieve good accuracy rates with noisy data sets.

E-learning opportunities and challenges for legal education in rural Victoria

Access to justice extends beyond consideration of the systems and institutions of justice; it includes infrastructure such as transport, health, education and communications. Rural, regional and remote (‘RRR’) communities are more likely to face difficulties in accessing advice and accurate information on laws and processes available for resolution of disputes. Perhaps more fundamentally, they rarely have a voice in effecting reforms in laws and related policies. For several decades, community legal centres, legal aid, courts, and a range of other institutions have used community legal education programs to improve knowledge and access to law and justice systems, services and organisations. The recent Productivity Commission Inquiry into Access to Justice Arrangements notes that, ‘Better coordination and greater quality control in the development and delivery of these [community legal education, legal information] services would improve their value and reach.’ At the same time, research into the professional needs of RRR legal practitioners has found that many of these practitioners face considerable difficulties accessing good quality continuing professional development (‘CPD’) and informal networking/support opportunities.6 Current and emerging internet-based technologies open up opportunities for legal organisations to better meet the educational needs of both rural communities and legal practitioners. Though limitations still exist at multiple levels, relatively low-cost, media-rich, synchronous and tailored education programs can now be delivered effectively in many rural and remote areas. However, complex layers of decisions are required to critically assess, harness and optimise technologies to best suit the needs of users, and to utilise teaching and learning techniques that best match the technologies and participant needs. Getting these elements — needs, technology and learning technique — right, nevertheless offers extraordinary opportunities. Sound decisions and good practices should enable state-wide and specialist law and justice-related services interested in improving their engagement with RRR communities to dramatically improve the reach and quality of outcomes, not only for distant participants but the spectrum of stakeholders.

Popularity of reinforcement-based and belief-based learning models: an evolutionary approach

In an evolutionary model, players from a given population meet randomly in pairs each instant to play a coordination game. At each instant, the learning model used is determined via some replicator dynamics that respects payoff fitness. We allow for two such models: a belief-based best-response model that uses a costly predictor, and a costless reinforcement-based one. This generates dynamics over the choice of learning models and the consequent choices of endogenous variables. We report conditions under which the long run outcomes are efficient (or inefficient) and they support the exclusive use of either of the models (or their co-existence).

Self-regulated learning strategies & academic achievement in online higher education learning environments: a systematic review

© 2015 Elsevier Inc. All rights reserved. As enrolments in online courses continue to increase, there is a need to understand how students can best apply self-regulated learning strategies to achieve academic success within the online environment. A search of relevant databases was conducted in December 2014 for studies published from 2004 to Dec 2014 examining SRL strategies as correlates of academic achievement in online higher education settings. From 12 studies, the strategies of time management, metacognition, effort regulation, and critical thinking were positively correlated with academic outcomes, whereas rehearsal, elaboration, and organisation had the least empirical support. Peer learning had a moderate positive effect, however its confidence intervals crossed zero. Although the contributors to achievement in traditional face-to-face settings appear to generalise to on-line context, these effects appear weaker and suggest that (1) they may be less effective, and (2) that other, currently unexplored factors may be more important in on-line contexts.

The impact of an authentic, simulated learning activity on student preparedness for work-integrated learning

Student preparation for work-integrated learning using simulated learning experiences is an under researched field in occupational therapy. In 2013 the Deakin University occupational therapy degree introduced a simulated learning experience for students aimed at preparing them for work-integrated learning experiences. The session gave students an opportunity to practice fundamental skills of the discipline. A Likert scale survey was written and critically reviewed by the authors. Students rated the extent to which they felt that they could communicate effectively, build rapport, safely transfer clients, apply occupational health and safety principles and write case notes, prior to and after participation in the simulated learning experience. A statistically significant improvement was found for all outcomes measured. Students also reported improved confidence and valued opportunities to practice and receive feedback on skills. The results demonstrate that participation in a simulated learning activity improves confidence and skills in a range of areas that are relevant to work-integrated learning placement.

Transformation from student to occupational therapist : using the Delphi technique to identify the threshold concepts of occupational therapy

BACKGROUND/AIM: Understanding and facilitating the transformation from occupational therapy student to practitioner is central to the development of competent and work-ready graduates. However, the pivotal concepts and capabilities that need to be taught and learnt in occupational therapy are not necessarily explicit. The threshold concepts theory of teaching and learning proposes that every discipline has a set of transformational concepts that students must acquire in order to progress. As students acquire the threshold concepts, they develop a transformed way of understanding content related to their course of study which contributes to their developing expertise. The aim of this study was to identify the threshold concepts of occupational therapy. METHOD: The Delphi technique, a data collection method that aims to demonstrate consensus in relation to important questions, was used with three groups comprising final year occupational therapy students (n = 11), occupational therapy clinicians (n = 21) and academics teaching occupational therapy (n = 10) in Victoria, Australia. RESULTS: Participants reached consensus regarding 10 threshold concepts for the occupational therapy discipline. These are: understanding and applying the models and theories of occupational therapy; occupation; evidence-based practice; clinical reasoning; discipline specific skills and knowledge; practising in context; a client-centred approach; the occupational therapist role; reflective practice and; a holistic approach. CONCLUSION: The threshold concepts identified provide valuable information for the discipline. They can potentially inform the development of competencies for occupational therapy and provide guidance for teaching and learning activities to facilitate the transformation to competent practitioner.

Development, evaluation and use of a student experience survey in undergraduate science laboratories: the advancing science by enhancing learning in the laboratory student laboratory learning experience survey

Student experience surveys have become increasingly popular to probe various aspects of processes and outcomes in higher education, such as measuring student perceptions of the learning environment and identifying aspects that could be improved. This paper reports on a particular survey for evaluating individual experiments that has been developed over some 15 years as part of a large national Australian study pertaining to the area of undergraduate laboratories—Advancing Science by Enhancing Learning in the Laboratory. This paper reports on the development of the survey instrument and the evaluation of the survey using student responses to experiments from different institutions in Australia, New Zealand and the USA. A total of 3153 student responses have been analysed using factor analysis. Three factors, motivation, assessment and resources, have been identified as contributing to improved student attitudes to laboratory activities. A central focus of the survey is to provide feedback to practitioners to iteratively improve experiments. Implications for practitioners and researchers are also discussed.

A new fuzzy peer assessment methodology for cooperative learning of students

In this paper, a new fuzzy peer assessment methodology that considers vagueness and imprecision of words used throughout the evaluation process in a cooperative learning environment is proposed. Instead of numerals, words are used in the evaluation process, in order to provide greater flexibility. The proposed methodology is a synthesis of perceptual computing (Per-C) and a fuzzy ranking algorithm. Per-C is adopted because it allows uncertainties of words to be considered in the evaluation process. Meanwhile, the fuzzy ranking algorithm is deployed to obtain appropriate performance indices that reflect a student's contribution in a group, and subsequently rank the student accordingly. A case study to demonstrate the effectiveness of the proposed methodology is described. Implications of the results are analyzed and discussed. The outcomes clearly demonstrate that the proposed fuzzy peer assessment methodology can be deployed as an effective evaluation tool for cooperative learning of students.