Exploring the effectiveness of development research with a monitoring and learning approach

There is a growing demand for better understanding of the link between research, policy and practice in development. This article provides findings from a study that aimed to gain insights into how researchers engage with their non-academic partners. It draws on experiences from the National Centre of Competence in Research North-South programme, a development research network of Swiss, African, Asian and Latin American institutions. Conceptually, this study is concerned with research effectiveness as a means to identify knowledge useful for society. Research can be improved and adapted when monitoring the effects of interactions between researchers and non-academic partners. Therefore, a monitoring and learning approach was chosen. This study reveals researchers' strategies in engaging with non-academic partners and points to framing conditions considered decisive for soccessful interactions. It concludes that reserachrs need to systematically analyse the socio-political context in which they intervene. By providing insights from the ground and reflecting on them in the light of the latest theoretical concepts, this article contributes to the emerging literature founded on practice-based experience.

An innovative blended learning approach using virtual patients as preparation for skills laboratory training: perceptions of students and tutors

BACKGROUND Currently only a few reports exist on how to prepare medical students for skills laboratory training. We investigated how students and tutors perceive a blended learning approach using virtual patients (VPs) as preparation for skills training. METHODS Fifth-year medical students (N=617) were invited to voluntarily participate in a paediatric skills laboratory with four specially designed VPs as preparation. The cases focused on procedures in the laboratory using interactive questions, static and interactive images, and video clips. All students were asked to assess the VP design. After participating in the skills laboratory 310 of the 617 students were additionally asked to assess the blended learning approach through established questionnaires. Tutors' perceptions (N=9) were assessed by semi-structured interviews. RESULTS From the 617 students 1,459 VP design questionnaires were returned (59.1%). Of the 310 students 213 chose to participate in the skills laboratory; 179 blended learning questionnaires were returned (84.0%). Students provided high overall acceptance ratings of the VP design and blended learning approach. By using VPs as preparation, skills laboratory time was felt to be used more effectively. Tutors perceived students as being well prepared for the skills laboratory with efficient uses of time. CONCLUSION The overall acceptance of the blended learning approach was high among students and tutors. VPs proved to be a convenient cognitive preparation tool for skills training.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Facial Nerve Image Enhancement from CBCT using Supervised Learning Technique

Facial nerve segmentation plays an important role in surgical planning of cochlear implantation. Clinically available CBCT images are used for surgical planning. However, its relatively low resolution renders the identification of the facial nerve difficult. In this work, we present a supervised learning approach to enhance facial nerve image information from CBCT. A supervised learning approach based on multi-output random forest was employed to learn the mapping between CBCT and micro-CT images. Evaluation was performed qualitatively and quantitatively by using the predicted image as input for a previously published dedicated facial nerve segmentation, and cochlear implantation surgical planning software, OtoPlan. Results show the potential of the proposed approach to improve facial nerve image quality as imaged by CBCT and to leverage its segmentation using OtoPlan.

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.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

Improving Pediatric Basic Life Support Performance Through Blended Learning With Web-Based Virtual Patients: Randomized Controlled Trial

BACKGROUND E-learning and blended learning approaches gain more and more popularity in emergency medicine curricula. So far, little data is available on the impact of such approaches on procedural learning and skill acquisition and their comparison with traditional approaches. OBJECTIVE This study investigated the impact of a blended learning approach, including Web-based virtual patients (VPs) and standard pediatric basic life support (PBLS) training, on procedural knowledge, objective performance, and self-assessment. METHODS A total of 57 medical students were randomly assigned to an intervention group (n=30) and a control group (n=27). Both groups received paper handouts in preparation of simulation-based PBLS training. The intervention group additionally completed two Web-based VPs with embedded video clips. Measurements were taken at randomization (t0), after the preparation period (t1), and after hands-on training (t2). Clinical decision-making skills and procedural knowledge were assessed at t0 and t1. PBLS performance was scored regarding adherence to the correct algorithm, conformance to temporal demands, and the quality of procedural steps at t1 and t2. Participants' self-assessments were recorded in all three measurements. RESULTS Procedural knowledge of the intervention group was significantly superior to that of the control group at t1. At t2, the intervention group showed significantly better adherence to the algorithm and temporal demands, and better procedural quality of PBLS in objective measures than did the control group. These aspects differed between the groups even at t1 (after VPs, prior to practical training). Self-assessments differed significantly only at t1 in favor of the intervention group. CONCLUSIONS Training with VPs combined with hands-on training improves PBLS performance as judged by objective measures.

Differenzielles Lehren und Lernen: eine Kritik

Dieser Beitrag beschäftigt sich kritisch mit dem von Wolfgang Schöllhorn seit 1999 propagierten Ansatz des differenziellen Lehrens und Lernens. Nach einer Einordnung in die historische bewegungswissenschaftliche Debatte um den Informationsverarbeitungsansatz und die dynamische Systemtheorie zeigen wir, dass die von Schöllhorn behaupteten Praxiskonsequenzen theoretisch nicht fundiert sind, dass die Abgrenzung zu konkurrierenden Lerntheorien lücken- und fehlerhaft ausfällt, dass die präsentierte empirische Befundlage auf höchst wackeligen Füßen steht und dass der Ansatz sich auch aus Praxissicht als nicht tragfähig erweist. Mit Blick auf fatale Konsequenzen sowohl für die Sportpraxis als auch für die Sportwissenschaft empfehlen wir, in zukünftigen Publikationen zum differenziellen Lernen auf fehlerhafte und theoretisch wie empirisch unbegründete Praxisempfehlungen zu verzichten.

Reshaping Rural Extension: Learning for Sustainability (LforS): An Integrative and Learning-Based Advisory Approach for Rural Extension with Small-Scale Farmers

This publication offers concrete suggestions for implementing an integrative and learning-oriented approach to agricultural extension with the goal of fostering sustainable development. It targets governmental and non-governmental organisations, development agencies, and extension staff working in the field of rural development. The book looks into the conditions and trends that influence extension today, and outlines new challenges and necessary adaptations. It offers a basic reflection on the goals, the criteria for success and the form of a state-of-the-art approach to extension. The core of the book consists of a presentation of Learning for Sustainability (LforS), an example of an integrative, learning-oriented approach that is based on three crucial elements: stakeholder dialogue, knowledge management, and organizational development. Awareness raising and capacity building, social mobilization, and monitoring & evaluation are additional building blocks. The structure and organisation of the LforS approach as well as a selection of appropriate methods and tools are presented. The authors also address key aspects of developing and managing a learning-oriented extension approach. The book illustrates how LforS can be implemented by presenting two case studies, one from Madagascar and one from Mongolia. It addresses conceptual questions and at the same time it is practice-oriented. In contrast to other extension approaches, LforS does not limit its focus to production-related aspects and the development of value chains: it also addresses livelihood issues in a broad sense. With its focus on learning processes LforS seeks to create a better understanding of the links between different spheres and different levels of decision-making; it also seeks to foster integration of the different actors’ perspectives.

Learning for Sustainability - LforS: An extension approach in small scale farming

Description of LforS as a integrativ and learning oriented extension approach

Testing the 'Learning for Sustainabiliy' Approach in a Training for Trainers: Contribution to new learning theory and approaches

Mainstreaming the LforS approach is a challenge due to dive rging institutional priorities, customs, and expectations of classically traine d staff. A workshop to test LforS theory and practice, and explore how to mainstream it, took place in a concrete context in a rural district of Mozambique, focusing on agricultural, forest and water resources. The evaluation showed that the principles of interaction applied pe rmitted to link rational know ledge with practical experience through mutual learning and iterative self-reflection. The combination of learning techniques was considered usef ul; participants called for further opportunities to apply the LforS methodology, proposing next steps.

Simulation Games - A Creative Tool for Capacity Building: Experience from the Learning for Sustainability Approach

Games that simulate complex realities to be dealt with in teams are an effective tool for fostering interactive learning processes. they link different levels of decision-making in the household, community and societal contexts. Negotiation and harmonisation of different perceptions and interests, be it within or between different households, form the basis of a common strategy for sustainable development.

Integrated Disaster Reduction Approach: LforS Learning and Simulation Game

Main objective of the game is to increase the coping capacity of players and familiarise them with the Integrated Disaster Reduction Approach. The game is intended to prepare for and introduce the players to a subsequent Learning for Sustainability capacity building workshop for community leaders. The game represents a typical emergency situation resulting from a natural disaster. Before and after the event, adequate measures help to prevent or minimise potential damages. Once a disaster has occurred, concerted actions and immediate measures need to be taken to rescue as much as possible (human lives, livestock, material) and safeguard the village against further damage and losses. In the course of the game, each playing team can proof its knowledge on adequate measures that have to be taken in order to avoid or reduce losses related to natural disasters. Such measures relate to assessment and monitoring of risks, prevention and mitigation measures, preparedness and response as well as recovery and reconstruction.