Social skills as predictors of communication, performance and quality of collaboration in project-based learning

The assumption that social skills are necessary ingredients of collaborative learning is well established but rarely empirically tested. In addition, most theories on collaborative learning focus on social skills only at the personal level, while the social skill configurations within a learning group might be of equal importance. Using the integrative framework, this study investigates which social skills at the personal level and at the group level are predictive of task-related e-mail communication, satisfaction with performance and perceived quality of collaboration. Data collection took place in a technology-enhanced long-term project-based learning setting for pre-service teachers. For data collection, two questionnaires were used, one at the beginning and one at the end of the learning cycle which lasted 3 months. During the project phase, the e-mail communication between group members was captured as well. The investigation of 60 project groups (N = 155 for the questionnaires; group size: two or three students) and 33 groups for the e-mail communication (N = 83) revealed that personal social skills played only a minor role compared to group level configurations of social skills in predicting satisfaction with performance, perceived quality of collaboration and communication behaviour. Members from groups that showed a high and/or homogeneous configuration of specific social skills (e.g., cooperation/compromising, leadership) usually were more satisfied and saw their group as more efficient than members from groups with a low and/or heterogeneous configuration of skills.

An investigation of computer literacy and attitudes amongst Greek post-graduate dental students

An accurate assessment of the computer skills of students is a pre-requisite for the success of any e-learning interventions. The aim of the present study was to assess objectively the computer literacy and attitudes in a group of Greek post-graduate students, using a task-oriented questionnaire developed and validated in the University of Malmö, Sweden. 50 post-graduate students in the Athens University School of Dentistry in April 2005 took part in the study. A total competence score of 0-49 was calculated. Socio-demographic characteristics were recorded. Attitudes towards computer use were assessed. Descriptive statistics and linear regression modeling were employed for data analysis. Total competence score was normally distributed (Shapiro-Wilk test: W = 0.99, V = 0.40, P = 0.97) and ranged from 5 to 42.5, with a mean of 22.6 (+/-8.4). Multivariate analysis revealed 'gender', 'e-mail ownership' and 'enrollment in non-clinical programs' as significant predictors of computer literacy. Conclusively, computer literacy of Greek post-graduate dental students was increased amongst males, students in non-clinical programs and those with more positive attitudes towards the implementation of computer assisted learning.

Sustained impact of a short small group course with systematic feedback in addition to regular clinical clerkship activities on musculoskeletal examination skills-a controlled study.

BACKGROUND The discrepancy between the extensive impact of musculoskeletal complaints and the common deficiencies in musculoskeletal examination skills lead to increased emphasis on structured teaching and assessment. However, studies of single interventions are scarce and little is known about the time-dependent effect of assisted learning in addition to a standard curriculum. We therefore evaluated the immediate and long-term impact of a small group course on musculoskeletal examination skills. METHODS All 48 Year 4 medical students of a 6 year curriculum, attending their 8 week clerkship of internal medicine at one University department in Berne, participated in this controlled study. Twenty-seven students were assigned to the intervention of a 6×1 h practical course (4-7 students, interactive hands-on examination of real patients; systematic, detailed feedback to each student by teacher, peers and patients). Twenty-one students took part in the regular clerkship activities only and served as controls. In all students clinical skills (CS, 9 items) were assessed in an Objective Structured Clinical Examination (OSCE) station, including specific musculoskeletal examination skills (MSES, 7 items) and interpersonal skills (IPS, 2 items). Two raters assessed the skills on a 4-point Likert scale at the beginning (T0), the end (T1) and 4-12 months after (T2) the clerkship. Statistical analyses included Friedman test, Wilcoxon rank sum test and Mann-Whitney U test. RESULTS At T0 there were no significant differences between the intervention and control group. At T1 and T2 the control group showed no significant changes of CS, MSES and IPS compared to T0. In contrast, the intervention group significantly improved CS, MSES and IPS at T1 (p < 0.001). This enhancement was sustained for CS and MSES (p < 0.05), but not for IPS at T2. CONCLUSIONS Year 4 medical students were incapable of improving their musculoskeletal examination skills during regular clinical clerkship activities. However, an additional small group, interactive clinical skills course with feedback from various sources, improved these essential examination skills immediately after the teaching and several months later. We conclude that supplementary specific teaching activities are needed. Even a single, short-lasting targeted module can have a long lasting effect and is worth the additional effort.

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

Validation of a novel robotic-assisted partial nephrectomy surgical training model

What's known on the subject? and What does the study add? One area of particular growth for robotic surgery has been partial nephrectomy. Despite a perceived notion that robotic-assisted partial nephrectomy is more easily adaptable compared to laparoscopic partial nephrectomy, there is nonetheless an associated learning curve. Validated training models with a corresponding assessment method for robotic-assisted partial nephrectomy were previously unavailable. We have designed and validated a RAPN surgical model appropriate for resident and fellow training.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Best Practices in Robot-assisted Radical Cystectomy and Urinary Reconstruction: Recommendations of the Pasadena Consensus Panel

CONTEXT Robot-assisted surgery is increasingly used for radical cystectomy (RC) and urinary reconstruction. Sufficient data have accumulated to allow evidence-based consensus on key issues such as perioperative management, comparative effectiveness on surgical complications, and oncologic short- to midterm outcomes. OBJECTIVE A 2-d conference of experts on RC and urinary reconstruction was organized in Pasadena, California, and the City of Hope Cancer Center in Duarte, California, to systematically review existing peer-reviewed literature on robot-assisted RC (RARC), extended lymphadenectomy, and urinary reconstruction. No commercial support was obtained for the conference. EVIDENCE ACQUISITION A systematic review of the literature was performed in agreement with the PRISMA statement. EVIDENCE SYNTHESIS Systematic literature reviews and individual presentations were discussed, and consensus on all key issues was obtained. Most operative, intermediate-term oncologic, functional, and complication outcomes are similar between open RC (ORC) and RARC. RARC consistently results in less blood loss and a reduced need for transfusion during surgery. RARC generally requires longer operative time than ORC, particularly with intracorporeal reconstruction. Robotic assistance provides ergonomic value for surgeons. Surgeon experience and institutional volume strongly predict favorable outcomes for either open or robotic techniques. CONCLUSIONS RARC appears to be similar to ORC in terms of operative, pathologic, intermediate-term oncologic, complication, and most functional outcomes. RARC consistently results in less blood loss and a reduced need for transfusion during surgery. RARC can be more expensive than ORC, although high procedural volume may attenuate this difference. PATIENT SUMMARY Robot-assisted radical cystectomy (RARC) is an alternative to open surgery for patients with bladder cancer who require removal of their bladder and reconstruction of their urinary tract. RARC appears to be similar to open surgery for most important outcomes such as the rate of complications and intermediate-term cancer-specific survival. Although RARC has some ergonomic advantages for surgeons and may result in less blood loss during surgery, it is more time consuming and may be more expensive than open surgery.

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.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.