Learning in Virtual Worlds: Research and Applications

Three-dimensional (3D) immersive virtual worlds have been touted as being capable of facilitating highly interactive, engaging, multimodal learning experiences. Much of the evidence gathered to support these claims has been anecdotal but the potential that these environments hold to solve traditional problems in online and technology-mediated education—primarily learner isolation and student disengagement—has resulted in considerable investments in virtual world platforms like Second Life, OpenSimulator, and Open Wonderland by both professors and institutions. To justify this ongoing and sustained investment, institutions and proponents of simulated learning environments must assemble a robust body of evidence that illustrates the most effective use of this powerful learning tool. In this authoritative collection, a team of international experts outline the emerging trends and developments in the use of 3D virtual worlds for teaching and learning. They explore aspects of learner interaction with virtual worlds, such as user wayfinding in Second Life, communication modes and perceived presence, and accessibility issues for elderly or disabled learners. They also examine advanced technologies that hold potential for the enhancement of learner immersion and discuss best practices in the design and implementation of virtual world-based learning interventions and tasks. By evaluating and documenting different methods, approaches, and strategies, the contributors to Learning in Virtual Worlds offer important information and insight to both scholars and practitioners in the field. AU Press is an open access publisher and the book is available for free in PDF format as well as for purchase on our website: http://bit.ly/1W4yTRA

Agrarian learning processes in Switzerland 1918–1939

This paper examines the social impacts of weather extremes and the processes of social and communicative learning a society undertakes to find alternative ways to deal with the consequences of a crisis. In the beginning of the 20th Century hunger seemed to be expelled from Europe. Switzerland – like many other European countries – was involved in a global interdependent trade system, which provided necessary goods. But at the end of World War I very cold and wet summers in 1916/17 (causing crop failure) and the difficulties in war-trade led to malnutrition and enormous price risings of general living-standards in Switzerland, which shocked the people and caused revolutionary uprisings in 1918. The experience of malnutrition during the last two years of war made clear that the traditional ways of food supply in Switzerland lacked crisis stability. Therefore various agents in the field of food production, distribution and consumption searched for alternative ways of food supply. In that sense politicians, industrialists, consumer-groups, left-wing communitarians and farmers developed several strategies for new ways in food production. Traditionally there were political conflicts in Switzerland between farmers and consumers regarding price policies, which led mainly to the conflict in 1918. Consumers accused famers of holding back food to control extortionate prices while the farmers pointed to the bad harvest causing the price rising. The collaboration of these groups in search for new forms of food-stability made social integration possible again. In addition to other crisis-factors, weather extremes can have disastrous impacts and destroy a society’s self-confidence to its core. But even such crisis can lead to processes of substantial learning that allows a regeneration of confidence and show positive influence on political stabilization. The paper focuses on the process of learning and the alternative methods of food production that were suggested by various agents working in the field during the Interwar period. To achieve that goal documents of the various associations are analyzed and newspapers have been taken into consideration. Through the method of discourse-analysis of food-production during the Interwar period, possible solutions that crossed the minds of the agents should be brought to light.

Learning to drive: learners' self-reported cognitive failure level predicts driving instructor's observation rating of driving performance

OBJECTIVES Evidence increases that cognitive failure may be used to screen for drivers at risk. Until now, most studies have relied on driving learners. This exploratory pilot study examines self-report of cognitive failure in driving beginners and error during real driving as observed by driving instructors. METHODS Forty-two driving learners of 14 driving instructors filled out a work-related cognitive failure questionnaire. Driving instructors observed driving errors during the next driving lesson. In multiple linear regression analysis, driving errors were regressed on cognitive failure with the number of driving lessons as an estimator of driving experience controlled. RESULTS Higher cognitive failure predicted more driving errors (p < .01) when age, gender and driving experience were controlled in analysis. CONCLUSIONS Cognitive failure was significantly associated with observed driving errors. Systematic research on cognitive failure in driving beginners is recommended.

Fear-learning deficits in subjects with fibromyalgia syndrome?

BACKGROUND: Fibromyalgia syndrome (FMS) is frequently associated with psychiatric conditions, particularly anxiety. Deficits in contingency learning during fear conditioning have been hypothesized to increase anxiety and, consequently, pain sensation in susceptible individuals. The goal of this study was to examine the relationship between contingency learning and pain experience in subjects with FMS and rheumatoid arthritis (RA). METHODS: Fourteen female FMS subjects, 14 age-matched female RA subjects and 14 age-matched female healthy controls (HCs) were included in a fear-conditioning experiment. The conditioned stimulus (CS) consisted of visual signs, the unconditioned stimulus (US) of thermal stimuli. CS- predicted low-temperature exposure (US), while CS+ was followed by low or high temperature. RESULTS: In the FMS group, only 50% of the subjects were aware of the US-CS contingency, whereas 86% of the RA subjects and all of the HCs were aware of the contingency. CS+ induced more anxiety than CS- in RA subjects and HCs. As expected, low-temperature exposure was experienced as less painful after CS- than after CS+ in these subjects. FMS subjects did not show such adaptive conditioning. The effects of the type of CS on heart rate changes were significant in the HCs and the aware FMS subjects, but not in the unaware FMS subjects. CONCLUSIONS: Contingency learning deficits represent a potentially promising and specific, but largely unstudied, psychopathological factor in FMS. Deficits in contingency learning may increase anxiety and, consequently, pain sensation. These findings have the potential to contribute to the development of novel therapeutic approaches for FMS.

Tailored instructional methods for students with diverse levels of computer knowledge and skills

The purpose of this online course is to ensure new nursing graduate students know how to use computer technologies required to complete academic and research activities. Powerful computers, high speed internet, digitalized resources and databases are widely available in educational institutes. New renovation and updates are being released at faster pace than ever. All these developments are necessary for a student to utilize computer programs and synthesize large amount of data in a limited time for any given academic research project. [See PDF for complete abstract]

Learning curve for robotic-assisted laparoscopic colorectal surgery.

BACKGROUND: Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. METHODS: A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. RESULTS: The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m(2), and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 31.54 × case number - 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. CONCLUSIONS: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

Learning enjoyment in early adolescence

There is empirical evidence showing that positive emotional and motivational factors in formal learning contexts decrease at the stage of young adolescence. According to Stage-Environment-Fit Theory and Self-Determination Theory, this change should be explained by a non-fulfilment of students' needs. By combining two different methods (questionnaires and day-to-day diaries) and applying a longitudinal design, this study aimed to explore the change in and the determinants of habitual and actual learning enjoyment. The sample consisted of 356 students. Quantitative results indicated that learning enjoyment and classroom practices decreased between Grades 6 and 7. Path analyses revealed that classroom practices are the source of students' learning enjoyment, while self-efficacy functions as a partial mediator. Data from students' diaries showed that a teacher's neglect of students' needs for competence and relatedness were significant sources of impeded learning enjoyment. Practical implications suggest the relevance of adjusting learning conditions to the needs of young adolescents in order to provide a facilitating basis for learning enjoyment.

Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting

This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.

The Role of BDNF, Leptin and Catecholamines in Reward Learning in Bulimia Nervosa

Background: A relationship between bulimia nervosa (BN) and reward-related behavior is supported by several lines of evidence. The dopaminergic dysfunctions in the processing of reward-related stimuli have been shown to be modulated by the neurotrophin brain derived neurotrophic factor (BDNF) and the hormone leptin. Methods: Using a randomized, double-blind, placebo-controlled, crossover design, a reward learning task was applied to study the behavior of 20 female subjects with remitted BN (rBN) and 27 female healthy controls under placebo and catecholamine depletion with alpha-methyl-para-tyrosine (AMPT). The plasma levels of BDNF and leptin were measured twice during the placebo and the AMPT condition, immediately before and 1 h after a standardized breakfast. Results: AMPT-induced differences in plasma BDNF levels were positively correlated with the AMPT-induced differences in reward learning in the whole sample (p = 0.05). Across conditions, plasma BDNF levels were higher in rBN subjects compared to controls (diagnosis effect; p = 0.001). Plasma BDNF and leptin levels were higher in the morning before compared to after a standardized breakfast across groups and conditions (time effect; p < 0.0001). The plasma leptin levels were higher under catecholamine depletion compared to placebo in the whole sample (treatment effect; p = 0.0004). Conclusions: This study reports on preliminary findings that suggest a catecholamine-dependent association of plasma BDNF and reward learning in subjects with rBN and controls. A role of leptin in reward learning is not supported by this study. However, leptin levels were sensitive to a depletion of catecholamine stores in both rBN and controls.

The mini-clinical evaluation exercise during medical clerkships: are learning needs and learning goals aligned?

OBJECTIVES The generation of learning goals (LGs) that are aligned with learning needs (LNs) is one of the main purposes of formative workplace-based assessment. In this study, we aimed to analyse how often trainer–student pairs identified corresponding LNs in mini-clinical evaluation exercise (mini-CEX) encounters and to what degree these LNs aligned with recorded LGs, taking into account the social environment (e.g. clinic size) in which the mini-CEX was conducted. METHODS Retrospective analyses of adapted mini-CEX forms (trainers’ and students’ assessments) completed by all Year 4 medical students during clerkships were performed. Learning needs were defined by the lowest score(s) assigned to one or more of the mini-CEX domains. Learning goals were categorised qualitatively according to their correspondence with the six mini-CEX domains (e.g. history taking, professionalism). Following descriptive analyses of LNs and LGs, multi-level logistic regression models were used to predict LGs by identified LNs and social context variables. RESULTS A total of 512 trainers and 165 students conducted 1783 mini-CEXs (98% completion rate). Concordantly, trainer–student pairs most often identified LNs in the domains of ‘clinical reasoning’ (23% of 1167 complete forms), ‘organisation/efficiency’ (20%) and ‘physical examination’ (20%). At least one ‘defined’ LG was noted on 313 student forms (18% of 1710). Of the 446 LGs noted in total, the most frequently noted were ‘physical examination’ (49%) and ‘history taking’ (21%). Corresponding LNs as well as social context factors (e.g. clinic size) were found to be predictors of these LGs. CONCLUSIONS Although trainer–student pairs often agreed in the LNs they identified, many assessments did not result in aligned LGs. The sparseness of LGs, their dependency on social context and their partial non-alignment with students’ LNs raise questions about how the full potential of the mini-CEX as not only a ‘diagnostic’ but also an ‘educational’ tool can be exploited.

Individual Video Training iVT - Development of a National Infrastructure for Video-Supported Learning

Introduction: Video‐Supported Learning is particularly effective when it comes to skills and behaviors. Video registration of patient‐physician interviews, class room instruction or practical skills allow it to learners themselves, their peers, and their tutors to assess the quality of the learner's performance, to give specific feedback, and to make suggestions for improvement. Methods: In Switzerland, four pedagogical universities and two medical faculties joined to initiate the development of a national infrastructure for Video Supported Learning. The goal was to have a system that is simple to use, has most steps automated, provides the videos over the Internet, and has a sophisticated access control. Together with SWITCH, the national IT‐Support‐Organisation for Swiss Universities, the program iVT (Individual Video Training) was developed by integrating two preexisting technologies. The first technology is SWITCHcast, a podcast system. With SWITCHcast, videos are automatically uploaded to a server as soon as the registration is over. There the videos are processed and converted to different formats. The second technology is the national Single Logon System AAI (Authentification and Authorization Infrastructure) that enables iVT to link each video with the corresponding learner. The learner starts the registration with his Single Logon. Thus, the video can unambiguously be assigned. Via his institution's Learning Management System (LMS), the learner can access his video and give access to his video to peers and tutors. Results: iVT is now used at all involved institutions. The system works flawlessly. In Bern, we use iVT for the communications skills training in the forth and sixth year. Since students meet with patient actors alone, iVT is also used to certify attendance. Students are encouraged to watch the videos of the interview and the feedback of the patient actor. The offer to discuss a video with a tutor was not used by the students. Discussion: We plan to expand the use of iVT by making peer assessment compulsory. To support this, annotation capabilities are currently added to iVT. We also want to use iVT in training of practical skills, again for self as well as for peer assessment.  At present, we use iVT for quality control of patient actor's performance.

Linking Applied Ethnobotany to Social Learning: A Participatory Tool for the Promotion of Indigenous Plants Use in Matutuíne, Southern Mozambique

In its search for pathways towards a more sustainable management of natural resources, development oriented research increasingly faces the challenge to develop new concepts and tools based on transdisciplinarity. Transdisciplinarity can, in terms of an idealized goal, be defined as a research approach that identifies and solves problems not only independently of disciplinary boundaries, but also including the knowledge and perceptions of non-scientific actors in a participatory process. In Mozambique, the Centre for Development and Environment (Berne, Switzerland), in partnership with Impacto and Helvetas (Maputo, Mozambique), has elaborated a new transdisciplinary tool to identify indigenous plants with a potential for commercialization. The tool combines methods from applied ethnobotany with participatory research in a social learning process. This approach was devised to support a development project aimed at creating alternative sources of income for rural communities of Matutuíne district, Southern Mozambique, while reducing the pressure on the natural environment. The methodology, which has been applied and tested, is innovative in that it combines important data collection through participatory research with a social learning process involving both local and external actors. This mutual learning process provides a space for complementary forms of knowledge to meet, eventually leading to the adoption of an integrated approach to natural resource management with an understanding of its ecological, socio-economic and cultural aspects; local stakeholders are included in the identification of potentials for sustainable development. Sustainable development itself, as a normative concept, can only be defined through social learning and consensus building between the local and external stakeholders.

Performance of undergraduate dental students on ICDAS clinical caries detection after different learning strategies

AIM This study aimed to evaluate the effect of a digital learning tool on undergraduate dental students' performance in detecting dental caries using ICDAS. METHODS An experimental digital learning tool (DLT) was created using digital photographs of sound and carious teeth. Thirty-nine students were divided into three groups (n = 13) and each assessed 12 randomly allocated patients before and after learning strategies: G1, ICDAS e-learning program; G2, ICDAS e-learning program plus DLT; G3, no learning strategy. Students (n = 32) reassessed patients 2 weeks after training. RESULTS Comparing before and after the learning strategies, any difference in the values of specificity and area under the ROC curve for all groups was found. Sensitivity was statistically significantly higher for G1 and G2. Comparing the groups, G2 showed a significant increase in sensitivity at the D2 and D3 thresholds. Spearman's correlations with the gold standard before and after the learning strategy were 0.60 and 0.61 for G1, 0.57 and 0.63 for G2, and 0.54 and 0.54 for G3, respectively. The Wilcoxon test showed a statistically significant difference between the values obtained before and after learning strategies for G1 and G2. CONCLUSIONS Use of the DLT after the ICDAS e-learning program tended to increase the sensitivity of ICDAS used by undergraduate dental students. The DLT appeared to improve dental students' ability to use ICDAS.

Undergraduate palliative care teaching in Swiss medical faculties: a nationwide survey and improved learning objectives

BACKGROUND In 2007, a first survey on undergraduate palliative care teaching in Switzerland has revealed major heterogeneity of palliative care content, allocation of hours and distribution throughout the 6 year curriculum in Swiss medical faculties. This second survey in 2012/13 has been initiated as part of the current Swiss national strategy in palliative care (2010 - 2015) to serve as a longitudinal monitoring instrument and as a basis for redefinition of palliative care learning objectives and curriculum planning in our country. METHODS As in 2007, a questionnaire was sent to the deans of all five medical faculties in Switzerland in 2012. It consisted of eight sections: basic background information, current content and hours in dedicated palliative care blocks, current palliative care content in other courses, topics related to palliative care presented in other courses, recent attempts at improving palliative care content, palliative care content in examinations, challenges, and overall summary. Content analysis was performed and the results matched with recommendations from the EAPC for undergraduate training in palliative medicine as well as with recommendations from overseas countries. RESULTS There is a considerable increase in palliative care content, academic teaching staff and hours in all medical faculties compared to 2007. No Swiss medical faculty reaches the range of 40 h dedicated specifically to palliative care as recommended by the EAPC. Topics, teaching methods, distribution throughout different years and compulsory attendance still differ widely. Based on these results, the official Swiss Catalogue of Learning Objectives (SCLO) was complemented with 12 new learning objectives for palliative and end of life care (2013), and a national basic script for palliative care was published (2015). CONCLUSION Performing periodic surveys of palliative care teaching at national medical faculties has proven to be a useful tool to adapt the national teaching framework and to improve the recognition of palliative medicine as an integral part of medical training.

Shallow Dialogue Processing Using Machine Learning Algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.