Integration of learning style theory in an adaptive educational hypermedia (AEH) system

Adaptive educational hypermedia (AEH - a branch of web-based learning) systems seek to personalise the learning experience for their users. User modelling can be performed using various criteria, such as prior ability or domain-specific knowledge, in systems such as WHURLE, AHA! and MOT. These user preferences, forming a user profile, are usually stored in a database, and integrated with the AEH learning environment. The learner is then presented with material that is best suited to them, with adaptation occurring at either the content or link level, or both. WHURLE (Web-based Hierarchical Universal Reactive Learning Environment) is an AEH system that has been used with many types of students, from secondary schools to those in Higher Education. It is a hypermedia-rich educational tool, suitable for all subjects, that seeks to address the pedagogical limitations of existing commercial Virtual Learning Environments. Its current user model is broadly based upon domain-specific knowledge. Investigations are under way to implement a user model based on learning style theory. This may be integrated with the early user model, or developed simply as a stand-alone module. Uniquely, WHURLE can change the user model used, as it is not a ‘hard-wired’ part of the system, but rather a component that can easily be interchanged. Learning style theory advocates that since individuals are all different, they should learn in different ways; this suggests a natural integration with the principles of adaptive educational tools. There are many different learning styles in use around the world, such as the Dunn and Dunn model, Gardner’s Multiple Intelligences, Kolb’s theory of experiential learning and Riding and Rayner’s Cognitive Styles Analysis. We will be discussing how we have implemented the Felder-Silverman Inventory of Learning Styles into the WHURLE architecture in an attempt to enhance the learning experience for users

Financial Risk Management in Commonwealth Organisations

In the last decade financial risk management in public sector organisations has become of greater interest to the public, politicians and regulators. Derivatives are commonly used to manage financial risk but little is known about the reasons why financial risk is managed, particularly through the use of derivatives. Furthermore, little is known about the reasons for and extent of derivative use in public sector organisations. To the authors knowledge this paper represents one of the first studies into the use of derivatives in Australian Commonwealth public sector organisations. A sample of Commonwealth organisations is surveyed on attitudes towards the use of derivatives for hedging. A variety of tests including ANOVA and t-tests are used to analyse the results. The two most important issues in the use of derivatives for hedging in the Commonwealth public sector include budgeting and reducing risks faced by management. Reducing the risks faced by management is often cited as a reason for derivative use in the private sector. It is unclear if budgeting is linked to this. Respondents from Commonwealth organisations rank other private sector reasons for derivative use, such as reducing bankruptcy and taxation relatively unimportant. Results also indicate that there are significant differences in the level of importance in some issues regarding derivative use across different organisations, particularly those with and without a documented risk management plan

The use of derivatives in a public sector setting

Existing private sector models of derivative use do not readily translate into the public sector that faces the joint objectives of value maximisation and provision of a privately unprofitable mission good. This paper develops and tests a model explaining public sector derivative use in terms of budget discrepancy minimisation. Hypotheses are developed and tested using logistic regression over a sample of Australian Commonwealth Government entities. It is found that public sector derivative use is positively correlated with liabilities and size of the organisation. This is consistent with management of budget discrepancies

The Cyclical Behaviour of the IPO Market in Australia

Initial public offerings have been examined typically in the context of short-term and long-run stock price performance of individual issues. In this paper, the aggregate market for IPOs is examined. There has been some prior suggestion that the IPO market exhibits cyclical patterns which are characterised by a high volume of new issues and substantial underpricing, such that 'hot issue periods' exist. This paper tests for the existence of such periods in the Australian market using a Markov regime-switching model on a variety of constructed IPO activity measures. The results demonstrate that hot periods do exist but that they do not possess homogeneous features. A number of distinguishing features are also identified between industrial and resource sector IPOs. Further, a lead-lag relationship is identified for the industrial sector such that underpricing leads IPO volume for up to six months. The paper offers explanations for these findings that appear related to general stock market conditions and regulatory features

AnswerPro: Designing to Motivate Interaction

This paper describes the design and initial testing of AnswerPro, a mobile academic peer support system for UK Key Stage 3 and 4 pupils (11-16 year olds). AnswerPro is a web application that enables pupils to seek support from their knowledgeable peers on various subjects. This paper correlates the findings from a previous requirements-gathering exercise, and from research into academic motivation, to propose design elements embedded within AnswerPro. A pilot study was conducted with 7 school pupils over 3 weeks. Participants then engaged in a focus group which discussed their experience using AnswerPro and the motivational elements embedded within it. Findings from their use of AnswerPro, and from the subsequent discussion, highlighted some problems with the embedded motivational features. As a result, suggestions for potential solutions and their merits are proposed for the next version of AnswerPro

Designing a mobile academic peer support system

In this paper, we discuss work in progress into the design of a mobile academic peer support system that enables 11-to-14 year old children to request and provide academic help to each other. Our proposed system was designed based on background research into the areas of peer learning, child development, help-seeking and academic motivation. Several methods, such as focus groups, interviews and Wizard of Oz, were used during the requirements gathering and initial testing stages. The proposed system is currently under development and will be tested in a study with school-pupils, over an extended period of time, in the next few months

Towards computation of novel ideas from corpora of scientific text

In this work we present a method for the computation of novel 'ideas' from corpora of scientific text. The system functions by first detecting concept noun-phrases within the titles and abstracts of publications using Part-Of-Speech tagging, before classifying these into sets of problem and solution phrases via a target-word matching approach. By defining an idea as a co-occurring pair, known-idea triples can be constructed through the additional assignment of a relevance value (computed via either phrase co-occurrence or an `idea frequency-inverse document frequency' score). The resulting triples are then fed into a collaborative filtering algorithm, where problem-phrases are considered as users and solution-phrases as the items to be recommended. The final output is a ranked list of novel idea candidates, which hold potential for researchers to integrate into their hypothesis generation processes. This approach is evaluated using a subset of publications from the journal Science, with precision, recall and F-Measure results for a variety of model parametrizations indicating that the system is capable of generating useful novel ideas in an automated fashion

Modelling and simulation techniques for supporting healthcare decision making : a selection framework

The development of this workbook has been led by a team of researchers from five UK universities with a grant from the UK Engineering and Physical Sciences Research Council (EPSRC). They are investigating the use of modelling and simulation in healthcare as part of the RIGHT (Research Into Global Healthcare Tools) project. The workbook was developed following an extensive review of literature on the application of modelling and simulation in healthcare and other safety- critical industries, supplemented by the team’s extensive expertise of modelling and simulation in healthcare. In order to produce this summary guide, thousands of articles were categorised according to the techniques used, when they were used, and with what resources.peer-reviewe

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707